Latest revision as of 21:06, 29 October 2018

Preface

Group members

Name	Study	Student ID
Buijvoets D.C.J.T	Mechanical & Electrical Engineering	0902148
Cornet, N.	Industrial Design	1007926
Van Horssen, C.	Software Science	0885378
Mouw, F.A.	Applied Physics	1005735
Stokbroekx, D.L.M.	Mechanical Engineering	1010326

Initial robotic concepts

After discussing several subjects from different fields in society, we came up with the following list of robotic concepts which have potential to solve problems faced by certain users.

Fire fighter drone which can be used to aid fire fighters
Cleaning drone for difficult to reach spots in buildings
Pavement cleaning drone which can remove dirt from tiles
Avalanche rescue drone that helps rescuing teams search for victims in an avalanche using already available beacons
Weeding robot which can differentiate between wanted and unwanted plants in a garden and remove the weeds
Referee robot using image processing to determine the state of a match in e.g. soccer or tennis
Medical nanobots for drug delivery
Fruit harvest robots

Chosen concept: Fast Response Extinguish Drone, F.R.E.D.

Introduction

Eventually we agreed upon the concept of a fire fighter drone. Fire fighting is one of the most dangerous jobs and every year 12.300 people get injured and 2510 people are killed by home fires in the U.S.^[1]. Furthermore there is around 6.1 billion dollar of annual fire damage in the U.S. only from which it can be concluded that the financial damage and civilian casualties worldwide due to fire is even higher. Most injuries and deaths are the result of poor preparation and panic. Therefore good preparation and information on the fire site can make the difference between life and death. This is were the idea of F.R.E.D. comes in. F.R.E.D. is a fire fighting drone that works in a smart home environment where its goal is delaying fire spread while the smart home can focus on evacuating victims before the fire departement arrives.

Problem statement

How can drones be used in combination with smarthomes for fully autonomous fire fighting. In this project the focus will be on the fire extinguishing part of fire fighting.

Objectives

The system must have the ability to extinguish small fires or reduce the intensity of larger ones.
The smarthome needs to be able to evacuate all victims inside a building.
The system needs to be able to communicate the current state of the fire back to the fire department to inform and prepare firefighters.
The system has to be able to operate completely autonomous.

During this project the focus will mainly be on the first objective and some on the second objective. Also the main focus of the project is on home fires. Of course the system can be expanded towards larger (public) buildings but that can be seen as future research once the concept is proven in a home environment.

Project setup

Before actually starting the project, a setup is made on how it will be executed.

Approach

Doing research on the subject via a state of the art literature search and expert interviews
Mapping all relevant users of the system and their needs.
Determining the requirements for the system with the needs of the users in mind.
Making a design for the drone and the system.
Making a prototype of the drone.
Testing the prototype.

Milestones

For the duration of this course, the following milestones are selected:

Week 1: Every member will take the time to do research on robots and their interests, in order to broaden one's horizon on the possible subjects. Afterwards a subject for the project will be chosen.
Week 2: Literature study and further research will be completed
Week 3: USE analysis is finished
Week 4: Design for the first prototype will be finished
Week 6: First prototype will be finished
Week 8: Final Design, final prototype and all other deliverables will be finished

Deliverables

The following deliverables will be created during this course:

Thorough research and literature study
Design research process and report
A functional drone design
(several) Prototypes
Ethical evaluation
A wiki page (this page) on all our findings and progress

Notes of meetings can be found via a link in sources or by pressing here and not there, these may be in Dutch.

Planning: Who's doing what

The planning of the project can be found in the table below. This is just a guideline meaning that in reality the actual tasks or planning may be different.

Week	All	Dirk	Natanya	Chiel	Fabian	Daan	Undecided
1	Finding suitable projects + finding articles on the chosen subject		Basic user requirements			Formulating Problem statement
2			Further elaborating user requirements and USE analysis + making persona’s of the users	State of the art research	State of the art research	State of the art research	Further elaborating user requirements and USE analysis + start making designs for the robot
3	Checking wiki and correcting formulation if necessary						Continuing on design for the robot + finishing USE analysis
4		Work on USE requirements		Starting on control software for the robot	Starting constructing of the prototype	Starting constructing of the prototype	Finishing robot design
5	Checking wiki and correcting formulation if necessary	Create a specific situation for use			Construction of the prototype	Construction of the prototype
6	Testing and evaluating prototype + find and analyse flaws in the design + fixing the design flaws				First prototype finished	First prototype finished
7	Find and analyse flaws in the design + fixing the design flaws + checking wiki and correcting formulation if necessary		Preparing presentation	Preparing presentation		Test prototype
8	Final design and robot finished + Presentation of the result

USE analysis

Since main focus of this project revolves around the USE aspect, users are a very important part in this project. Therefore first all different stakeholders in the problems will be mapped. There are tree main users or stakeholders in the situation of a home fire, these are listed below with the most important issues for the particular stakeholder.

Relevant users and their requirements

This topic revolves around a few different stakeholders, which will be looked at down below. Through interviews with the fire department in Eindhoven, the Gezamelijke Brandweer Drone Unit in Rotterdam and the Brandwondencentrum Maasstad Ziekenhuis Rotterdam different insights from the different aspects have been gathered and needs of the stakeholders involved have been listed. An overview of the interviews can be found under Expert Interviews

Fire victims

The most important users of the system will be the actual victims. For a vicim being in the middle of a fire, is a very stressful and traumatic experience. Victims during a fire can either be conscious or unconscious. When conscious, the victim needs to be reassured that everything will be alright and that they can in most cases easily get to safety by listening to the advises of a third party. When asleep it is important that the victim is woken up as soon as possible. The most important things, however, is that a victim can leave the house alive and that they suffer the minimum amount of injury, both mentally and physically.

Building owners

Building owners are the people that own the property that is on fire. There are two different types of home owners: housing associations and also the fire victims when they actually own the house. Of course they both course value the safety of all people that are involved in the fire. However, they also value that the building sustains as little damage as possible, while repair could cost a lot if the fire gets out of hand. In the case that the home owner is also the victim they may also want that their precious belongings inside the building are saved. Also building owners would prefer a system that requires non to little maintenance and that the system is only visible when it's active.

Firefighters/fire department

The fire fighters taking acton on a fire alarm are tasked with multiple tasks. Since the system of drone and smart home is designed to work in concert with the fire departement the fire departement is a very important user. They need to be informed as soon as possible of the fire and get an accurate analysis of the situation on site in order to work most efficiently. The top priority for fire fighters in a home fire is to get all victims inside the building to safety as soon as possible. (Fire fighters don't care much if a building burns down or not as long as all people are out of the building.) Since firefighters value the safety of the victims above all, they go for fast and safe escape of the victims as soon as possible. As mentioned earlier, fire fighters need to be warned of a fire as soon as possible. However it is very important that the fire is confirmed to prevent false alarms as these cost both time and money. When it is possible to put some suppressant on a fire in the early stages of the fire this is very useful, this delays the development of the fire giving victims more time to leave the building in a save way. However the fire departments prefers victims not to suppressing fires themselves since victims often do not know what they are doing and in certain scenarios make the situation worse.

Discoveries through USE-analysis

Several things haven been discovered through the USE-analysis resulting in several changes to the overall system and its requirements.

Firstly, the initial design requirements have changed from a drone that is to be able to extinguish a fire, to a drone that can just control and suppress a fire as long as possible, and extinguish when capable. These accumulated insights came from the interviews with the Eindhoven Fire Department and the Gezamenlijke Brandweer Rotterdam, where they informed us that buying time by controlling a fire rather than try to extinguish it with the drone would be way more valuable. This way there is more time for victims to escape and for the fire department to arrive.

Secondly, the initial concept was just a drone that could extinguish a fire changed to a concept of a smart home cooperating with a drone. The reason the concept was changed is the importance that victims get safely out of the building as soon as possible. From the interview at the Brandwondencentrum Rotterdam, the conclusion could be made that there was more attention needed for the victims, therefore splitting the physical systems performing the tasks of informing the victims and controlling the fire will be a more beneficial. As a drone cannot be in 2 places at the same time. Most people, although less often with professionals, freeze or panic when in a stressful situation, as a indoors fire is often experienced. If there is a cool and calm third party (the smart home) giving them instructions of what to do when an emergency situation surfaces, people will have better faith, stay calmer and thus have a better chance of survival. This resulted in the creation of not only the F.R.E.D. but also the smart home application.

An example of a changed requirement is the change to system requirement RSM 5 (waking a sleeping victim) which was created directly after the meeting with the Gezamenlijke Brandweer Rotterdam.

Personas

This project is all based around users and the most important user group will be the actual victims of the fire. To get a better understanding of the potential victims of a fire two personas have been made. Andrea and Frank are two examples of average humans that could be living in a smart home with a the F.R.E.D system and portray different values that users of the system could believe in and act on. Both of them are quite different and the system should be able to deal with all these different personalities and everything in between.

Scenario

To create a functional and feasible design for F.R.E.D. the following scenarios have been taken into consideration. As mentioned before the focus is one a home fire and thus this will also be the scenario. An average one person household is considered. One or more people are in the house, in a random room. The fire starts as a small fire and develops normally meaning there is nothing present that speeds up the fire development. Two examples of a home fire in this scenario are illustrated in the cartoons below. These scenarios already illustrate a little bit how the entire system of drone and smart home will function.

scenario 1: A person is ironing the laundry, but leaves to go to the toilet. However the hot iron is left on the clothes which causes them to catch fire. The fire is detected by the smart home and the system is activated. The drone will combat the fire while the smart home will evacuate the person in the building.

scenario 2: People are in their house but a fire is starting in the kitchen because there is something unattended on the stove. The fire is detected and the smart home starts to evacuate all people in the building while the drone is called into action to combat the fire.

Hardware and design

Choices made on design and hardware of F.R.E.D. will be discussed and elaborated here. The system will be split into three parts: the overal system (this is mainly the smart home), the extinguish mechanism and the drone. All these parts have specific requirements from which an actual design for the system is made.

Overall system and Smart Home

F.R.E.D. works in a system, consisting of a drone and a smarthome. These two will work together to combat the fire and ensure the safety of the people in the house but have completely different tasks. The drone will focus on how to deal with the actual fire while the smart home will focus mainly on getting all people in the building to safety.

The smarthome must be able to detect a fire, this will be done with fire alarms as are now installed in most homes or heat camera’s. Since the smart home knows the location of the alarm in the house the system and thus the drone knows where to look for the fire. In order for this to work optimal a fire alarm should be placed in most rooms especially those with a higher risk of fire for example kitchens. The use of heat cameras is more expensive but they can be used for more tasks than just detecting afire, for example detecting the location of people in the house. To make sure that the smart home can evacuate all people inside the building it must keep track of the location of people inside the building as well as their status, awake or asleep for example. Therefore the smart home should frequently check if there are people in the house and were they are, as well as when they leave. The smart home must know the exact lay-out of rooms, and the furniture placed inside. It is also necessary for the house do an assessment of if and where there are materials that can be potentially dangerous in case of an fire (for example fire works or a gasoline filled Jerry-can).

After detecting the fire the main goal of the smart home is to safely evacuate the people from the buildng. This will be done with blue lights on the floor, like the lights in the floor of an airplane. These lights will guide the victims towards the nearest accessible exit. Besides the lights the smart home will also give vocal instructions to the victims and comfort the victims if need arises to prevent panic. An example of what the smart home could say to the victim is: "A fire has been detected, please follow the lights towards the nearest exit. The drone is en route to control the fire." The task of the drone is to delay and/or extinguish the fire to give the people more time to evacuate. This will be discussed in the following sections. For the drone to work properly the system must be able to create a clear path from the drone to the fire. This can be done by opening doors and/or keeping people away from the drone and its path.

Within half a minute after the alarm a connection must have been established with the fire department, in this half minute the system must confirm that it's an actual fire. For the fire department it's very important that the fire is confirmed before they are informed, false alarms cost them a lot of valuable time. Keep in mind that this must happen within half a minute so it can be much quicker. In this connection the following information is transmitted to the fire department:

That there actually is a fire.
A headcount and status of the people (and children) inside the building.
Providing schematics of the building with the location of the fire in it.
Actions taken by the house to bring people to safety and delay or extinguish the fire and if already taken steps have been successful.
In case of special fire (I.E. pressurized gas or electric) information on materials that are burning or close to the fire.

It's important that the user agrees with the system sharing and monitoring this information due to privacy since some aspects require continuous monitoring. Explicit agreement is required under the new European Privacy Regulations ^[2] since May 2018. Once there is explicit consent of the user for sharing certain information this is no issue. When the user doesn't want to consent to this for whatever reason the system should also be able to function. The difference is that the fire departement will not be notified of everything. In every case the fire department should be notified that there is a fire.

Communicating with the occupants of the house goes via the Smart Home and has the following goals.

Informing occupants there is fire and what they should do.
Keep occupants save/guiding occupants outside
Keeping occupants calm.

Off course there are a lot of existing houses that are not smart homes yet, these houses need to be converted to smart homes. A basic conversion to a smart home will cost at least 12.000 Euro ^[3], for the system of F.R.E.D. some elements concerning the interaction between smart home and inhabitants must be added for example the evacuation lights and speakers in all rooms. This will increase the costs even further and this is even without the drone. From this can be concluded that a system in which F.R.E.D. functions is at this moment with the current technologies possible but also expensive and not yet affordable for everyone. In the future the goal is to make the system available for everyone. When a new home is build the costs for making it smart are less of an issue since the costs are already in the building budget and may replace certain classical elements.

This all leads to a list of requirements for the entire system of F.R.E.D. and the Smart Home, these are listed in the table below. Also the priority of the requirement is given. The priority scale is 1 = system won't work without it, 2 = important for system to work properly, 3 = not critical to functioning of the system.

Number	Requirement	Comments	Priority
RSM 1	Detect fire	The fire needs to be detected before the other steps can be taken.	1
RSM 2	Make fictim feel safe	The smart home needs to try to keep the victim as calm as possible, by assuring that help is on its way and to explain every action it is taken. The victim should not feel threatened by the smart home or drone.	2
RSM 3	Give instructions	After analysing a situation, the smart home needs to, if possible, give instructions to the victim of possible actions to improve chance of survival of the victim, this can be a possible path of escape to the emergency exit.	1
RSM 4	Cannot (lethally) harm victim in any way	The drone and smart home are not allowed to harm the victim in any way, or do something that brings lethal injury to the victim.	2
RSM 5	Wake the victim	If the victim is asleep, it is very important that they are to be woken up as soon as possible. Preferably though a manner that is both fast but also keeps people from panicking.	1
RSM 6	Save victim	The victim needs to leave the house alive and preferably unhurt	1
RSM 7	Alert fire departement	The smart home needs to automatically sent a notice of fire to the fire department the moment the fire is confirmed. This needs to be done within 30 seconds from the start of the fire. The notice needs to include as much information about the current situation as possible (what room is the fire in, what is burning, who is still in the building, expected situation and planned actions are just a few examples). In case of changes in the situation the notice needs to be adjusted accordingly.	1
RSM 8	Escape of victims	Victims should escape the burning building as soon and safe as possible	1
RSM 9	Building should sustain as little damage as possible	The less damage there is the better	3

Response Time

The most common types of fire in and around homes are: kitchen fires, electrical fires, heater fires and smoking related fires. In the end a drone capable of responding to all these fire types is preferable. Most fires get out of control fast, usually within minutes. Therefore, it’s important that the drone can be on side very fast. The response time of the drone depends on several aspects: the location where the drone is stationed in the building, the speed at which it can move through the building and the way the fire is reported to the drone.

Placement in building

When placing F.R.E.D. in a building it is important for a small response time that the drone is located close to rooms or areas with higher risks of fire. In regular homes with inhabitants that do not smoke the kitchen has the highest risk of hosting a fire. But when there are people who live in the house that smoke indoors the number of rooms with high risk of fire increases drastically. Every room where a person smokes inside is a potential fire hazard. From our conversation with the TU/e fire department became clear that houses where elderly people live are also more likely to catch fire.

When finding a suitable location to place the drone one very important user requirement must be considered. This requirement is that the user doesn’t constantly want to see or bump into the drone in his home, or in other words the drone should only be visible when it's active. Therefore, the drone should be placed on a discrete location preferably close to all high-risk areas in the house. From now on the assumption will be made that the inhabitants do not smoke or do not smoke inside their house since this is dangerous and unhealty. This means that the highest risk of fire is in the kitchen. Because the entire system is in a Smart Home this means the drone knows his way around the house and is able to remotely open doors inside the house for it to move from room to room. When a new Smart Home is built with F.R.E.D. integrated in it, there are a few good locations for placing the drone are:

The first possibility is to place the drone in the ceiling, in this way the drone will never hinder the user, but it may cause some difficulties for maintenance and routine checks of the drone. However ideally the system should require limited maintenance once correctly set up. The deployment time of this method is a few seconds and therefore very fast.

A different possibility is to place the drone inside a wall, this can be in a horizontal or vertical position. A drone may have some difficulties to lift of in a vertical position especially when it is heavy. Therefore, a mechanism is required that first brings the drone horizontal before it can be launched when placed vertical in the wall this is a big disadvantage because it costs valuable time. A disadvantage for the user is that a piece of wall must remain free and unblocked for the drone. When the drone is placed in the wall on an appropriate height, let’s say around 1.20 meters, it’s easily accessible for maintenance or routine checks when necessary.

The drone can also be placed inside the floor, this is comparable to placement in the ceiling but in this situation the drone is better accessible by the user when required. A major disadvantage of this is that some places of the floor can’t be used by the user for placing furniture. Also, it’s required that the drone isn’t located somewhere where there is a door, in a hallway or on the evacuation route because this may hinder the user in getting around in his own house.

Another way to place the drone is in empty spaces like a garage, storage room or attic. An advantage of these locations is that a drone here won't hinder the user in any way. However the user has to keep these spaces quite organized and tidy. When the surroundings hinder the drone to much it can't fly and be on time on the disaster area. When placed in these locations the drone is also more likely to be far away from the fire which means a larger flying time before the drone reaches the fire.

Considering these options the best spot to place the drone is in the ceiling of a building and the best location would be in the kitchen. However in existing buildings the ceiling may not always be an possibility for placement of the drone. When the ceiling is not an option first empty spaces like garages or attics must be considered. There can also be homes that don't have these spaces for example apartments. In these situations the best way of placing the drone would be in a specially designed box on the wall.

Reporting the fire

When a proper location for F.R.E.D. has been found a way of reporting the fire to the drone must be chosen. This can be done via an automatic fire alarm using smoke and/or heat detectors. Since a smart home environment is considered the drone knows the location of the fire when the alarm is initiated. A different possibility for reporting the fire is manually by using a switch on a wall or an app on your smart phone. Manual switches on walls to trigger the fire alarm can already be found in a lot of larger buildings. The only issue with these is that they don’t look very nice and a user might not want to have these switches in every room of his house. Therefore, an app on the user’s smart phone takes away this issue for the user. When a fire is reported via manual switches on the wall or via an app the drone also knows where the fire is located if the alarm is being sounded in the room where the fire is. However when the user can trigger the alarms manually this may increase the risk of false alarms.

For automatic fire detection there are two main types of alarms: photoelectric- and ionization smoke alarms. For the drone to respond fast there should be smoke detectors and alarms in as many rooms as possible. Ionization smoke alarms are usually more sensitive to flaming fires and photoelectric ones are more sensitive to smoldering fires ^[4]. Since most fatal home fires are a result of smoldering fires it’s best to use photoelectric detectors in the house. The time until the alarms goes off depends on the amount of smoke produced by the fire, but by analyzing fire development movies it’s safe to say that most alarms are triggered around 15 seconds after ignition. ^[5] ^[6] ^[7] ^[8] ^[9] Once the drone is near the fire it first has to localize and confirm the fire before it takes further action this might also take a few seconds but an exact number can't be given at this moment.

Travel distance and time

The final step for determining the response time of the drone is the speed at which it can fly. But another very important factor for the speed on the response time is the distance the drone must travel. An average newly build Dutch house is 116 m2 ^[10], consider this house has 2 floors and is square this would mean the square has sides of 7.6 m. When the drone is located as far away from the fire as possible this would mean it has to travel to the other side of the building change floors and go back to the other side of the building. This would mean the maximum distance it has to travel in an average home also considering walls and moving up to another floor is around 25 meters. A drone that would be very capable to use as a basis for F.R.E.D. (unfortunately not available for this project) is the DJI Matrice 100, it can carry up to 1.2 kilos and has a top speed of 18 meters per second ^[11] . So, the top speed of the drone isn’t really an issue. But the drone also must make turns and should not further endanger the people in the house. Therefore, the top speed of the drone inside the house should be limited to 1 meter per second because the drone will still be able to reach the fire within 30 seconds when it’s furthest away from a fire in an average home and with the drone traveling at this speed user in the house can anticipate on the drone moving through the house. But since home fires are usually located in the kitchen and the drone is also stationed here the actual travel time would be much shorter.

Conclusion

When taking the deployment time, fire alarm response time and distance the drone must travel into account the overall maximum response time of F.R.E.D. in an average house will be around 55 seconds. But is this sufficient? From analyzing fire development movies some conclusions can be made ^[12] ^[13] ^[14] ^[15] ^[16]. Fire development goes very rapidly and accelerates over time. After around 1 minute most fires are still isolated and easy to extinguish. When the drone isn’t on site extinguishing within 2 minutes after ignition it cannot do much more. Usually in around 3 minutes the entire room ignites, and the home is lost. From this can be concluded that a maximum response time of 55 seconds for F.R.E.D. should be sufficient enough to completely extinguish the fire or slow the fire down and by doing so buy more time for people to leave the building. From our conversation with the TU/e fire department became clear that it’s vital to act in the first minute of the fire since this can severely delay the fire and when you are lucky already completely extinguish the fire. From the fire department perspective, the most important part is to get all people in the building to safety and not if the entire building burns down or not. Homeowners however also put a lot of value in to their belongings and an effort to extinguish the fire in the early stages of the fire might be able to safe their precious belongings. This is a very difficult dilemma that may be different for every specific home owner, however human lives are always more valuable than anything else.

Autonomous navigation and fire localization

Eventually, the drone will receive a signal from the smarthome indicating that a fire has initiated in some room in the house. After this, the drone should be able to navigate autonomously to the room in question and localize the exact position of the fire in order to effectively aim the suppressant.

Global navigation and obstacle avoidance

The real challenge of autonomous flight for this project is the indoor aspect. Two keys to autonomous navigation are localization of the drone itself and trajectory planning. Since the drone must operate in an environment without GPS signal, the localization has to be done using 3D cameras or laser scanners and mapping software. An egocentric map can be made using the actual feed from the scanners and can be compared with a global map (of the house) to localize the drone on this map. Once the localization has been established, a trajectory must be planned which guides the drone from its current position to the location of the fire while avoiding obstacles. Using the fire location provided by the smart home, the drone's current location (from the localization) and the global map of the house, a global trajectory can be planned. This trajectory only accounts for rough navigation through the corridors of the house to arrive in the correct room. The actual obstacle avoidance must be done continuously during flight by real time updating of the egocetric map and local trajectory planning.

During the state of the art literature study, it has been found that several studies have been able to succesfully integrate this method into a drone. It was proven that the drone was able to accurately localize itself, plan a global trajectory and update local trajectories for obstacle avoidance, even in dynamically changing environments. This research is however beyond the scope of this project and the technology is not commercially available yet. When F.R.E.D. will be built, either extra research on this technology can be done or some collaboration with the researchers from the discussed studies could be established.

Fire localization

Once the drone has safely arrived in the room which contains the reported fire, its job is to exactly localize the fire and eject its suppressant with the right aim. If the fire has been localized, its position can be communicated with the autonomous navigation system to set as new goal. A local trajectory can be made in the egocentric map which guides the drone to a safe distance from the fire, but also close enough for the suppressant be effective. This distance can be determined once the extinguish mechanism has been established and the limits of the fire resistance of the drone are known.

In order to localize the fire, heat cameras and RGB cameras can be used. In the state of the art literature study, different methods have been found which are capable of detecting fires.

Fire suppression

Extinguisher requirements

The main idea of the drone’s ability to suppress fires is that it can react quickly to small fires that have not gone out of control yet and by doing so prevent a lot of potential damage and injuries. The initial idea was to make a drone capable of extinguishing every home fire completely however from our talks with the fire departement and analysis of users it's way more important to get people to safety and buy them time to escape the building. This means the extinguish mechanism will also be designed to delay or extinguish starting fires instead of complete house fires because this is what users actually want.

One of the most common types of home fires are kitchen fires.^[17] Amongst these, grease fires occur frequently (type B in case of a normal pan or type F in the case of a frying pan ^[18]) and can be very hard to control. The first reaction of people is to poor water over these fires however in the case of grease fires this is the most stupid thing you can do. Other kitchen fires can include oven fires (type A or B) and electrical fires (type E) but they are less common. Since grease fires are among the most frequent types of home fires and one of the most challenging to suppress, the goal of the drone is being able to suppress an average grease (type B) fire (resulting from heating grease in a pan up to its auto ignition temperature).

If the drone is able to suppress common kitchen grease fires, the assumption is made that it will be able to suppress all fires of type A (paper, textiles and wood) and B (flammable liquids) of the same scale too. Though further experimentation might be needed to validate this assumption.

Before choices on how the design for the extinguish mechanism can be made first the requirements for the mechanism must be formulated keeping the user requirements in mind. In the table below the 7 main requirements for the extinguish mechanism are given with a short comment and priority. The priority scale is 1 = mechanism won't work without it, 2 = important for mechanism to work properly, 3 = not critical to functioning of the mechanism.

Number	Requirement	Comments	Priority
REM 1	Drone must be able to automatically activate the mechanism without human intervention	When the drone can't initiate the mechanism by itself it's useless to the user	1
REM 2	The drone must be able to extinguish for at least 1 minute	Since the goal is to delay the fire 1 minute of extinguish time should be sufficient	2
REM 3	The suppressant used may not cause damage to the drone or environment when using it	When using the suppressant immediately damages the drone and causes it to fail this is not very useful also considering REM 4	2
REM 4	The mechanism must be refillable after use	This means the drone is reusable after use, this very important since the definition of a robot is that it must be reusable ^[19]	3
REM 5	Weight should not exceed 0.6 kilo	Drones can only carry a certain amount of weight however there exist drones that can carry much more these drones are however way to large to operate inside a normal house.	2
REM 6	The mechanism should not disturb the stability and flying capabilities of the drone	When the mechanism makes it impossible for the drone to fly and/or get to the fire in time it's useless	2
REM 7	Mechanism can be used for Class A and B fires	Class A and B fires are the most common fires in and around house.	1

Now the requirements will be elaborated in an actual design for the extinguish mechanism of F.R.E.D.

Extinguish mechanism

Since the drone has to be able to extinguish fires unmanned, and preferably autonomous, it must have an electro-mechanical extinguish mechanism of some sort. An actuator attached to the drone should be able to control the stream of suppressant (at least on or off). Furthermore, the stream of suppressant should be ejected to the front (or sides) of the drone through a nozzle. Most drones cannot fly directly above fire since the air will be too turbulent and therefore the suppressant cannot just be dropped underneath the drone. There should also be a container to hold all of the suppressant.

The actual mechanism will depend on the suppressant that will be used. It could consist of a solenoid valve, since this type of valves can be controlled electronically. The driving force behind the suppressant can be a preloaded pressure in the container, a pump or a chemical reaction. This also depends on the used type of suppressant and the design of the container.

One very important point however is that the drone can activate the extinguish mechanism once is has localized and confirmed the fire (REM 1).

Extinguishing using a solid aerosol (blusstaaf)

One good possibility is a ‘blusstaaf’, this is a very good option for the extinguish mechanism since it only needs to be mounted on the drone with an electronic activation mechanism. A Blusstaaf is a complete aerosol extinguisher with an electrical activation. It weighs 250 grams, has 45 grams of suppressant, can extinguish for 30 seconds and cost 39,95 a piece ^[20]. Aerosol is a suppressant that can be certainly used for all type A and B fires (REM 7). It may have more difficulties to extinguish fires of type F but since the goal is to delay the fire aerosol can still be very useful.

An attempt has been made to get some Blusstaven for this project by contacting the Blusstaaf company, also questions about technical specifications on the blusstaaf and aerosol were asked. They responded quite a bit later and said they could provide us with some technical information about the blusstaaf and also make a discount deal for research. This discount deal wasn't very favorable for us since multiple blusstaven had to be bought for a limited discount and the information was also very limited, that is why the decision not to use the blusstaaf for the prototype has been made. However for the actual drone a Blusstaaf is the best option or an mechanism specially designed for F.R.E.D. that uses aerosol and has an more favorable suppressant weigh ratio compared to the blusstaaf. The big advantage of using a Blusstaaf is that it's already an proven concept that does not require much further development to integrate it in a drone. In order to meet requirement REM 2 the use of two Blusstaven is required.

Attachment of extinguish mechanism

Most drones makes use of an ultrasound sensors or other sensors, which are located at the center of the bottom, to determine its height. This limits our ability to attach anything to the bottom of the drone in the center. One option would be to attach two extinguishers on the bottom next to the center, as shown in the picture below.

This would increase extinguish capability but also the weight. There are drones that can deal with the weight of 2 Blusstaven for example the DJI Martice 100. Tests on the drone must be done to determine if it is stable enough when lifting over 600 grams in this configuration.

Another option is to attach the extinguisher on the top of the drone, but far enough to the front that the suppressant will not be sucked into the propellers. The figure below shows how the blusstaaf could be attached to the top of the drone, using two attachment parts (blue). These parts can clamp around the cylindrical shape of the blusstaaf and can be attached to the drone using adhesive velcro tape, to ensure the extinguisher can be removed easily (REM 4). The attachment part in the back also has space for the electronics that will be used to activate the blusstaaf. Placing the electronics in the back also helps balancing the weight of the drone. It's very important that the drone is properly balanced since this increases the stability and therefore also the battery life of the drone.

The front part could be attached to the extension of this particular drone frame that holds the camera, but on a different drone a different design may be required:

The attachment parts must be made using a 3D printer. The advantage of having 3D printed parts is that they can be very lightweight (REM 5) and can have custom shape which will always fit the chosen drone and extinguisher. If 3D printing is not an option, laser cut wood can be used as an alternative. Wood can also be made relatively lightweight. It's very important to make the connection parts as light as possible since this means the extinguish mechanism could carry more fire suppressant.

Activation of extinguisher

To activate the blusstaaf, a button has to be pressed which makes a connection to the battery (for any solid aerosol extinguishers with electrical ignition, a connection has to be made to a power source). A better way to control the activation is to replace the button with a relay which makes a connection when it receives a high signal. This signal could be sent from a free channel on the receiver of the drone. The parrot AR drone, which is provided by the university to be used for the demo, is controlled with an app via wifi. This connection however can't be extended with a separate channel for the extinguisher activation. Therefore, a separate transmitter and receiver will have to be introduced. Of course the actual drone should be able to give this signal to activate the mechanism once the fire has been localized and confirmed (REM 1), for the prototype this will however been done manually since the focus of the project is on extinguishing a fire using a drone.

A schematic of an activation system for both the extendable drone (left) and the parrot AR (right) are shown below.

Reaction force on drone

When the extinguisher is activated, the suppressant will naturally exert a force on the drone as it is ejected. It is important to know this force in order to conclude whether the drone will be affected by it significantly. The drone has to retain its ability to move freely in all directions while the extinguisher operates.

The reaction of the ejected matter is determined by the rate of mass flow and the velocity of the suppressant as it leaves the nozzle. The force can be found using the expression:

Using the fact that the rate of mass flow is equal to the density of the matter multiplied with the rate of volume flow:

and that the velocity of the matter right after the nozzle is equal to the rate of volume flow divided by the area of the nozzle:

the force equation can be rewritten to:

In order to calculate the reaction of the blusstaaf, the density of the ejected aerosol, the rate of volume flow and the area of the nozzle need to be specified. These values can't be measured for now. However, an estimation can be made to get an idea of the order of magnitude of the force. Upon seeking contact with the retailer of the Blusstaaf a material safety data sheet had been acquired. In this document, it was stated that the aerosol has a density of 50 g/m^3. Futhermore, the description of the Blusstaaf states that it contains 45 g of suppressant and that it can extinguish for 30 seconds. From this, it can be estimated that the rate of mass flow is equal to 1.5 g/s. The rate of volume flow would then be 0.03 m^3/s. Upon close inspection of images of the Blusstaaf, the area of the nozzle can be estimated to have an order of magnitude of 10 mm^2. Using these values, a reaction of 4.5 N can be found.

To determine whether the drone can overcome this force, the maximum force of the drone in the opposite direction of the suppressant stream needs to be know. Since the suppressant will be ejected horizontally, the maximum horizontal force has to be determined. This force can be estimated using the maximum lift capacity of the drone and its current weight. The Figure below shows a schematic of the forces that are generated by the drone.

The force Fmax will be equal to the maximum lift capacity multiplied with the gravitational acceleration:

The component Fy must be equal to the gravitational force acting on the drone in order to keep the current altitude. This force is determined by the current weight of the drone multiplied with the gravitational acceleration:

The maximum angle of the drone follows from the relation between Fmax and its component Fy:

However, this is angle is limited to 35 degrees for most drones, as they will become unstable at larger angles.

The horizontal force can then be found using the angle and Fmax:

The Dji Matrice 100 is a drone that fits all our requirements^[21]. Its maximum take-off weight is stated to be 3.6 kg. The drone itself weights 2.4 kg and a extinguish mechanism with a maximum weight of 0.6 kg will be added. Using these values, a maximum horizontal force of 19.5 N can be derived, when the tilt would be 34 degrees. This force is more than three times higher than the estimated reaction of the Blusstaaf and more than double when 2 blusstaven are used. Therefore, it is concluded that the drone can still move in all directions while extinguishing (REM 6).

It must be noted that this method is not completely accurate since the maximum lifting capacity might change when the drone is at an angle. Also, the direction of the suppressant flow will change as the drone tilts. However, an estimation can still be made to get an idea of the order of magnitude. Furthermore, the maximum take-off weight that is stated for a drone has to be a weight with which the drone can still move in all directions, since moving is an essential feature of a drone. Therefore, it can be assumed that the drone can generate an even larger horizontal force.

Drone

Requirements Drone

For the user it's important that the drone works and operates as autonomous as possible. Also the drone requirements must be in consent with the requirements of the extinguish mechanism, for example the drone should be able to carry at least the maximum weight of the extinguish mechanism otherwise it won't work. Before choices on what drone will be chosen can be made first the requirements for the drone must be formulated keeping the user requirements in mind. In the table below the main requirements for the drone are given with a short comment and priority. The priority scale is 1 = drone won't work without it, 2 = important for drone to work properly, 3 = not critical to functioning of the drone.

Number	Requirement	Comments	Priority
RD 1	Drone must be able to carry 0.6 KG of weight.	Carry extinguishing mechanism and other equipment.	1
RD 2	Drone must fit in a box with dimensions 0.6x0.6x0.3 meters.	The dimensions of the drone matter for the storage and usability of the drone, a drone that is to large won't fit trough the door	1
RD 3	Drone must have it's propellers shielded.	Prevent injury in unlikely collisions with users. Prevent damage to drone on impact with anything.	1
RD 4	Drone must be able to fly for at least 7 minutes on one charge.	Fly out, do task, return to charger place.	1
RD 5	Drone must be rechargeable	This means the drone is reusable after use, this very important since the definition of a robot is that it must be reusable [2]	2
RD 6	Drone must be able to connect itself to a charging station.	Drone must be recharged after a mission	3
RD 7	Drone must have a Heat camera on board	Is required for the localization and confirmation of a fire	1
RD 8	Drone must have an RGB camera on board	Is required for the localization and confirmation of a fire	1
RD 9	Drone must have protection against smoke with particle size >7 µm	7 µm is the size at which smoke is visible to the human eye.	3
RD 10	Electrical components of drone must be protected against dust/water according to at least IP65 rating	Prevent damage of low pressure streams of liquid to prevent damage during extinguishing. High resistance to dust as the drone might not be used for a long time so it might collect quite some dust.	2

Important aspects

There are also some other aspects that must be considered when choosing a drone, these can be seen as design choices.

The drone must be reusable see also REM 4, if the drone isn't reusable it cant be classified as a robot ^[22].
After extinguishing or delaying the fire the drone should be able to keep flying around the area of the fire to monitor the current situation and sent this information to the fire departement.
Something else that is important to keep in mind is the law. Right now by law it's forbidden to fly drones autonomous in public space or to fly a drone in public space without a license. Therefore the drone must remain inside the building, in the future when the law changes the drone might be able to also operate outside.
The drone must be able to react to starting fires, in these fires the heat generated is not very high yet therefore the drone doesn't require to be build out of full heat resistant materials. However, it's smart to have some fire resistance therefore metals and carbon are better materials to use instead of plastics.

Possible candidate

In search for a drone, it was important that the majority of the requirements would be met. The DJI Matrice 100 is a drone that is compatible with the majority of the requirements only a RGB (RD 8) and heat camera (RD 7) must be added. It is able to carry more than a kilo (RD 1), it can fly continuously with an added weight of 1 kg for 13 minutes (RD 4) and its dimensions are smaller than the box that is described in the requirements (RD 2). However the DJI Matrice 100 isn't a cheap drone and costs around 3600 Euro for one drone ^[23]. Therefore also building F.R.E.D. from the ground up can be considered but since the cost of this drone will likely also be high or even higher than the Matrice 100 due to all the requirements it must meet the best decision is to use the DJI Matrice 100.

List of Materials for F.R.E.D.

Dji Matrice 100
Blusstaaf
5v relay module
Autonomous navigation controller
RGB Camera
Heat Camera

Demonstration and prototype

Since the project duration is only 8 weeks and there is a limited budget not all requirements or plans can be fully implemented in the prototype of F.R.E.D. In this chapter the prototype will be discussed and why it's different from the requirements for the actual drone.

Drone for prototype

We have borrowed a drone which can be controlled by hand. It is equipped with an ultrasound based altitude sensor and two cameras: one facing down and one facing forward. The drone can carry about 0.5 Kg for a really short time if and only if the battery is fully charged. A structure will be attached to it which can hold and use an extinguisher. The drone is not programmable unfortunately. There was an alternative drone available to use which could carry a bit more and is programmable, however it does not have out of the box control software present, so we would need to write code which controlls each propellor seperately and create our own stabilisation software and so on. The drone we use accepts instructions like "go forward", "rotate left" "lower altitude" ect. We think writing control software for the more advanced drone would take up (way) to much time, therefore we went for the simpler non programable drone. However during the test this drone turned out to be ineffective possibly due to bad batteries, that is why the prototype has been made using a different home made drone that works in the same way as the initial borrowed drone.

Extinguisher for prototype

Since the drone available for the prototype is only capable of carrying 0.5 kg requirement REM 5 can't be fulfilled. Due to this limitation in weight it is also harder to fulfill requirement REM 2 for the prototype, the longer the prototype can extinguish the better but an exact time for the prototype is still unknown. Due to budget limitations requirement REM 7can't be fulfilled so in the demonstration a mechanism based on water will be used. This means that the prototype drone is only capable of dealing with type A fires safely. All other requirements should be possible to realize in the prototype.

Extinguisher using waterpump

For the demonstration, a mechanism based on water will be used. Therefore, a small extinguisher using a waterpump has been made. This prototype consists of a bottle, a waterpump and a plastic tube. Since the pump that has been bought is an underwater pump, it will be placed inside the bottle. The power wires for the pump and the plastic tube will exit the bottle via a hole cut in the top of the bottle. A nozzle will be attached to the end of the tube to diverge the water stream and decrease the flow rate to get more extinguishing time. The entire mechanism will be attached to the protective cover of the drone using double sided adhesive tape and calbe ties.

In the picture below a schematic drawing of the design can be found. This design exists of a water container (blue box), power supply, remote activation mechanism, pump (yellow box), small water hoze (green), nozzle (orange) and air inlet for water container (red). This last piece is required to let the pump work, without it the pressure in the container will go to a vacuum and water cannot come out to extinguish.

To determine if this mechanism won't disturb the stability and flying capabilities of the drone (REM6) the same calculations as for the blusstaaf can be done. This extinguisher mechanism ejects water at a volumetric flow rate of 0.0052 L/s (measured) and the area of the nozzle is about 9 mm^2. Using these values, the density of water and the method that is described above, a reaction of 0.003 N is found. At this scale, it can be assumed that any drone that is capable of lifting an extinguishing mechanism is also capable of handling this reaction.

Activation of extinguisher

As discussed earlier, the extinguisher of the prototype will be activated with a seperate RF-channel. To this end, a small transmitter-receiver operating on 433MHz has been obtained. The receiver (which will be carried by the drone) has an operating-voltage of 3-6v, which corresponds with the small pump that is used. Therefore, the entire extinguisher will be powered by three AA batteries in series, adding up to 4.5v. Since the maximum power output of the receiver channel is too low for the power consumption of the pump, an NPN transistor has been used. This transistor will act as a switch for the pump, controlled by the receiver. This can be seen as the relay that was discussed in the previous chapter. A schematic of the electronic circuit of the extinguisher can be seen below.

Weight

The bottle and pump have a weight of 70 g and the receiver with the battery pack weigh 90 g, which gives a total of 160 g. If the bottle would be filled 2/3rd full, the water would add about 300g. The total weight would then be below 0.5 kg, which the drone should be capable of lifting. However, when testing the drone with the extinguisher attached, without water, the drone would not rise higher than 10 cm above the ground. Therefore, we will use a completely different drone which is capable of lifting 0.5 kg.

List of Materials for prototype

Tricopter
Cable tie and tape to connect mechanism to the drone.
Water bottle
Horizontal underwater pump
Tube for underwater pump
433 MHz RF remote with receiver
Transistor
Mechanical switch
Matrix board to solder electronics to
Batteries
Battery holder.

The actual prototype with all these components can be seen in the picture below.

Testing of the prototype

A prototype has been made using all materials listed above.This prototype has been extensively tested. Since it's quite dangerous the test won't be done with very large fires but smaller fires controllable fires instead. In the first test a small candle was used as the fire however the drone instantly blew to candle out when it came close. Therefore a larger more severe fire was required for the tests but still on a safe controllable scale. This has been achieved using a white firelighter cube normally used for lighting a BBQ. These cubes contain a little bit of kerosine and a lot of material that can burn which means they are also harder to extinguish once light up. The time the air flow of the rotors didn't blow the fire out before the extinguish mechanism could extinguish the fire. Two videos of the tests with the firelighter cubes can be found in the two links below (Integration on the wiki didn't work unfortunately).

"https://drive.google.com/file/d/1_PmKQV-AGCmHWsYrDN0TY5wLdk-JUwLd/preview"

"https://drive.google.com/file/d/1JS5eR1nxpRzQf1JPG1JE5WPBYQ2-cLJ9/preview"

From these videos can be concluded that the mechanism works and that a drone is capable of extinguishing small scale starting fires. Further tests can be done with larger fires or an upgraded prototype. However larger fires are more dangerous to create and water can't be used as a suppressant anymore in some cases. A second more capable prototype can be made for further testing. However in this project there wasn't enough time to go towards a second prototype. Also in a second prototype the autonomous element can be elaborated a bit more since this is quite limited in the prototype used for the tests.

Since the final demonstration of the project is inside only a very limited fire will be created due to safety reasons, the videos are proof that the drone can extinguish larger fires.

Conclusion

The main goal of this project was to proof that drones can be used to extinguish small home fires before they get very large, and the conclusion is that drones can do this in a properly designed system like F.R.E.D. . However currently the legal situation does not allow drones to fly outdoors, this means the drone can only operate inside the building. Also the system of a smart home and a drone is quite expensive at the moment, in the future this may get cheaper but when the first systems will be introduced they will likely only be available for people that are wealthier. But since the concept of a autonomous fire extinguishing drone is technological feasible as proven in this project the future of fire extinguishing drones looks bright.

Future Research

To make the entire system work future research can be done in two different subjects.

Navigation and autonomous flying
Autonomous fire detection
Interaction Smart Home with humans

Background/research

In this section the background information used for the previous section is elaborated upon.

Expert Interviews

Fire department TU/e

Currently the fire department is running a project with the innovation space, by accident a group member came in contact with someone involved with this. They had a demonstration/meeting with the TU/e fire department planned and we were invited to come and have a look on Monday the 24th of September. Also we received a contact within the fire department, this person is responsible for innovation and repression specifically in south-east Brabant.

Conclusies: (Interview met Brandweer Eindhoven)

The fire TU/e gave us as group a few tips/pieces of advice

Find fire development movies from demonstrations to determine the time when an alarm responds and when it's to late to act.

Keep in mind that the scenario isn't always positive, for example student housing can a drone navigate in your house?

It's very positive if a drone controls the fire but what about the people inside the building shouldn't they be evacuated?

Base your fire suppressant on the most common fires in and around house. Most fires are related to the kitchen or smoking.

Drone Unit Fire Department Rotterdam

A conversation was held with the director of the rotterdam fire department, which actually has a fire fighting drone in operation at the moment. This drone is autonomously navigated by another (controlled) vehicle which makes a 3D map of the inside of a building. We will have the opportunity to talk to the project leader of this drone about some points of improvement.

The “Gezamelijke Brandweer” in Rotterdam has been using their drone for 5 years. They are required, when using it, to always have the drone in line of sight. The drone has a reach of 5km, but the firefighters are restricted to a limitation of 500m and 120m high. It can fly on a single pack of batteries for 35 minutes and can lift 6kg. Most importantly, it flies stable, even above a fire. Which is something not every drone can do.

They are of the opinion that a drone is best used to gather information, while the drone is very mobile. Through a normal camera and a heat camera, they can investigate and assess the situation. That way the firefighters can go into the building more prepared and less casualties will fall. Fast response time is crucial when it comes to a rescue mission. It, however, does take 3 people now to fly the drone. (One keeps track of the location, one steers it, one steers the camera). Furthermore, the heat camera can be of a big help when locating and assessing the state of eventual victims. People who have passed away (colder) will have low priority than people who are still alive. Every operation starts with a headcount of people who are (supposed to be) in the building.

It is forbidden by law to fly for private use. Only people from Brandweer Nederland with a pilot license are allowed to freely fly right now.

Their recommendation was to focus on controlling fire with the drone, and not try to extinguish it. 1L of water produces 17L of steam, which is ideal to control fire with. Our choice of drone can carry up to around 0.5kg, which would produce 8.5L of steam.

Audio recording of conversation: https://storage2.cvhorssen.nl/s/MLJdKtEQ0PKYhcg (download available until 31-12-2018)

Audio can be played from browser without file download or account (click on the big icon in the center).

Brandwonden Centrum Maasstad Ziekenhuis Rotterdam

At the Maasstad Hospital, we spoke with after-care specialist Anneke Steenhoven.

Recently, a lot of home based fires have been happening. If someone is by accident on fire, the first thing one is supposed to do is roll on the ground. This minimizes the available oxigen for the fire to burn. However, in mids of panic people tend to forget this and start running around. Also a third party or experts tend to freeze or even panic in these situations.

If one finds out there is a fire in their home, the best idea is to stay calm and call 911. When burned, immediately cool with cold water. The burn should absolutely not be touched. The most severe burns are:

Open fire burns
Electricity burns
Ice burns

State of the art: Literature study

One of the most important facets of this project is to come to an understanding of the current state of technologic advancement that is relevant to the drone and its functionalities. Therefore, literature on different relevant catagories is studied to understand the state of the art. Here follows a list of the scientific research that was studied for this project, divided into the different relevant catagories.

Current smart-homes are mostly focused on creating a seamless living environment for the occupants of the house, or to create an energy efficient management system called “smart energy”. Whereas our project focuses on optimising the safety and mental state of the occupants in case of a fire.

State of the Art Smart Homes

MavHome (Managing An Intelligent Versatile Home)^[24]

The MavHome smart home project focuses on the creation of an environment that acts as an intelligent agent, perceiving the state of the home through sensors and acting upon the environment through device controllers. The agent’s goal is a function that maximizes comfort and productivity of its inhabitants and minimizes operation cost. In order to achieve this goals, the house must be able to predict, reason about, and adapt to its inhabitants.

The MavHome combines different technologies to understand it’s user (artificial intelligence, machine learning, databases, mobile computing, robotics, and multimedia computing). MavHome features include collection of activities in a database, prediction of inhabitant actions, identification of inhabitants from observed activities, mobility prediction, robotic assistants, multimedia adaptability, and intelligent control and visualization of home activities.

MavHome predicts the user’s net action, through machine learning. By looking at how the user has acted and reacted in the past, it is able to conclude what is the most probable follow-up action.

The Georgia Tech Aware Home^[25]

This smart home focuses on Health and Well-being, sustainability, Entertainment and Connected Living. Although it does focus itself on Health and wellbeing, this is mainly focused on aging in place (assisted living for the elderly).

For localisation, they use PowerLine Positioning. It is very cost-effective and it uses tags that don’t alter the room itself to track products or humans. Through a low-resolution ceiling camera (watching the movements) the home is able to determine the “mood” of the room. This means whether people are busy or not.

MIT Intelligent Room^[26]

The Intelligent Room project is focused on the vision of creating an easy to install smart home environment. Not much should be changed to the environment to get it to work. They believe that the computer environment should be transported to the “real world”, instead of people into the virtual environment (WIMP/VR).

The Intelligent Room is able to detect people and determine their activities and gestures, and even if they are talking to each other or to the smart home.

Through a fixed wide-angle and steerable narrow angle camera the smart home software is able to detect if there are people present in the room. It does this through movement detection software.

The Neural Network House^[27]

This smart homes focuses itself on creating an smart environment that adapts itself to the occupants. The home needs to program itself to the user needs, the user has no task in this.

This system is called ACHE (adaptive control of home environments). ACHE both monitors user preferences, and then learns to execute these. Secondly, it focuses on being as energy efficient as possible (e.g. turn of the lights when not needed). ACHE can not visibly track the user. It only keeps track of the preferences in the home (e.g. termostat). It has no clue of the concept “human”. In that sense it also can’t accompany to different users with different preferences and needs.

Why Smart homes?

In our interview with burn after-care specialist Anneke Steenhoven, it became clear that even professionals sometimes fail to act coolly and professionally in situations of stress and panic (such as a fire). Even though they know what to do, they have a black-out or just freeze. Although not tested yet, it is very probable that if a third party would give advice or instructions, people can react faster and more thoughtful in such situations. People may not be able to come up with a solid plan themselves, but they can follow those of others. In our case this third party would be the smart home.

As also seen in the previous examples of the current state-of-the-art, it is already possible to sense where people are in the house or even in the room. In case of a fire, it is our mission to accompany the occupants of the house to the exit in the safest way. For this to happen, it needs to be known where the occupants are located in the house. Then it can be determined which route can be taken to the safest exit. Our definition of the safest exit is always the exit that is closest to the occupant and in another room than the fire.

It is our supposition that people will stay calmer because they are told exactly what to do, in a calm matter. This will create the idea that they are in safe hands, although they still have to execute the advices themselves.The smart home has already assessed the situation and drawn a plan for them.

Conclusion

The user localisation that already exist in current smart homes seems very practical, a component we could also use for our smart home. The action prediction, however promising, is not something we could use. The action prediction works through machine learning. The smart home observes the action and reaction of the users and can through that determine what the possible next action of a user could be. In a panic situation, however, people tend to act unpredictable and different from what they would normally do. In case of a fire the same holds true. That leads to us believing that this technology is not yet advanced for us to implement it in our concept.

None of the current promising smart homes focus itself on providing help in case of an emergency situation. Although research has been done by different parties^[28], it has never been implemented until now. This is why our research could prove to be a valuable asset in the current state-of-the-art.

Drones in firefighting

Drones and robots are already extensively used in firefighting but there are few examples of actual autonomous fire extinguishing drones. Most drones in firefighting are used to support humans by providing vital information on the emergency.

Drones provide information on how fires are spreading and developing to firefighters to increases the efficiency of the process by sending units to right places. The information gathered by these drones can also be further analyzed for a better understanding of how fire spreads for optimization of extinguishing techniques. One of the largest fire departments in the world the L.A.F.D. (Los Angeles Fire Department) is currently researching and using these kind of drones ^[29]. The drones have been used for the first time during the massive wildfires in December 2017 and have been a great help in the firefighting process. These drones do still require a human pilot and a human to analyze the information.

Drones also help emergency services with other non-fire related disasters. For example, during floods or earthquakes these drones can be in the disaster area much faster to collect information on the situation for the emergency services.

A different application for drones in firefighting is the localization of victims in fires that would otherwise never be found. Currently one of the best drones for this undertaking is the Firestorm UAV ^[30]. This drone can find victims inside burning buildings using a thermal camera also this drone can detect toxic gasses and inform firefighters on the situation in a building. Using bright LED lights, the drone can lead a localized victim along the safest path outside of the building.

The emergency services also use the drones to make emergency deliveries to certain disaster areas. The payloads of the drones can be extremely diverse, from AED machines, medical- and food supplies. One of the drones currently in development for this purpose by the company ZIPLINE ^[31]. The drone that is currently being tested in the USA and already operational in Rwanda for blood deliveries to rural hard to get areas drops the payload mid-air before it flies back to base to be resupplied and launched again.

Another way in which drones are used by fire departments is to make pre-fire plans for high risk or vital buildings. These drones can map escape routes and localize water supplies and potential problems for these buildings.

There are some drones that can also extinguish fire. But these drones are not autonomous and require a human pilot or firetruck for water supply and further support. An example of drones used for actual fire extinguishing are the drones produced by the company AERONES ^[32]. Although these drones are capable of combatting fires they cannot operate without the presence of a fire truck supporting the drone with water and electricity. This drone can reach heights of 300 meters which is much higher than the height a traditional fire truck can reach. However due to the hoses connected to the drone it can only be used for combating the fire from the exterior. This drone can be useful for fires in high-rise buildings or at other great heights that were traditionally hard to reach.

conclusion

Drones are already used in fire fighting quite often. But they are only used for providing information to the fire department and never operate fully autonomous, from our conversation with the drone unit of the Rotterdam fire departement we found out this is mainly due to legal reasons. There are no concrete examples of drones actually being able to extinguish an starting fire fully autonomous.

General Drone Information

A device has been designed which is able to gather different kinds of environmental information once thrown into a fire site. This device is also capable of providing victims with essential information which increases their change of safe evacuation.^[33]^[34] ^[35]

Autonomous drone navigation

Outdoor autonomous flight has been researched for some time now, since the use of GPS can be a great tool for this application. For a fire fighting drone however, indoor autonomous flight is the real challenge, since the drone has to fly to fires autonomously indoors. The localization of fires can be done by the smart home, and can be communicated with the drone. The drone itself however has to localize itself in its environment and has to be able to plan a trajectory to the fire while avoiding obstacles. Flying autonomous in a GPS-denied environment requires real-time tracking and mapping of the surroundings of a drone using sensors like 3D cameras or laser scanners.

A fully autonomous navigation controller has been made which uses a 3D laser scanner for omnidirectional environment perception. An egocentric grid map can be made an updated in real-time. This map is merged to an allocentric map (of the environment) to localize the drone. The controller can also generate global trajectories (from start to end) and local obstacle avoidance trajectories which together make for a safe autonomous navigation. It is shown that this multilayered navigation planning enables the controller to cope with dynamically changing environments, such as a house fire. ^[36]

Another approach to obstacle avoidance in indoor environments using only 2D imaging and on board inertial sensing has been researched. This approach makes use of patterns on the ground for localization (not ideal for unknown environments). It is shown that unknown obstacle avoidance using 2D imaging is feasible. ^[37]

Furthermore, a navigation controller that estimates location and trajectories based on imperfect sensory input has been developed. This controller contains parameters which allow to change the accuracy or speed of the trajectories. Safer navigation can be achieved using this controller. ^[38]

Autonomous victim detection

There are various ways in which victims can be detected, currently available; most optimal results are achieved by using a combination of approaches and also adding the height and pitch of the drone in consideration, hyperspectral imaging techniques are currently available to create maps of buildings by using cameras. By using the Viola-Jones algorithm, one can mark victims on these maps. The false positives on these victim detection results can be further reduced by using an improved version of the Markov Random Fields (MRFs). Another technique to detect victims is by using a pseudo-noise radar, whose signals get scattered by human bodies.^[39] ^[40] ^[41] ^[42] ^[43] ^[44]

Fire detection

Fire can already be automatically detected from colored images, by using image processing it is even possible to distinguish fire from smoke. Another method for detecting fire, or flames, is to use space-time fluctuations, which can also be detected on colored images. In combination with the use of Gaussian distributions and an infrared/heat camera an autonomous system is able to accurately mark fire and flames on camera images.^[45] ^[46] ^[47] ^[48]

Fire suppression

Today there exists a wide variety of methods to suppress fires. Since this project is based around a drone, one of the main concerns is the weight of the fire suppressant. It should be as light as possible per amount of fire that it can put out. Furthermore, our method should be able to extinguish an as wide variety of fires as possible. Especially fires of class A, B, C and F (European standard) seem to be most common in buildings.

The use of a pressurized water mist extinguisher seems to be impractical. Although an extinguisher of this type is able to suppress fires of type F (cooking oils and fats), next to ordinary fires, a lot of water is needed to put out an average fire. Typical amount of 9 litres are often required ^[49], which is much more than an average drone can carry next to its own equipment. Furthermore, the suppression of fires using water mist often results in a large fire cloud in the process, due to the increased heat transfer that is caused by the water droplets. This would be impractical as it could harm the drone.

Another method is the use of particulate aerosols. Often, particles are generated from a solid or gel and mix with the air. Particulate aerosols prove to be a very lightweight alternative for water, with results showing the same fire suppressing abilities at a 30 times lower volumetric flow, compared to normal water.^[50]^[51]^[52]

Fire resistant materials

There are some fire-resistant materials and techniques available for drones. There exist a potassium aluminosilicate (Geopolymer) matrix carbon fiber composite ^[53]. These Geopolymer can withstand a heat flux of 50 kW/m2, this is comparable to the heat flux of a well-developed fire and most materials spontaneously ignite exposed to this heat flux. However, the Geopolymer loses strength after it is having been exposed to this amount of heat.

A different way of protecting fire material that have already been applied to drones is the use of aramid fibers and air buffers ^[54] ^[55], however this greatly increases the size of the drone due to the air buffers. This is a very light weight technique of making a drone fire resistant for a short period of time. The only materials that can be used for the mainframe of a drone entering a room with a well-developed fire are aluminum or titanium. ^[56] ^[57]

Sources

Usefull Links

Here notes taken during different meetings can be found, click on here otherwise it won't work.

↑ https://www.nfpa.org/Public-Education/Campaigns/Fire-Prevention-Week/Fire-Facts
↑ https://autoriteitpersoonsgegevens.nl/nl/onderwerpen/avg-europese-privacywetgeving/algemene-informatie-avg
↑ https://www.gearbrain.com/average-smart-home-build-cost-2589554626.html
↑ https://www.nfpa.org/Public-Education/By-topic/Smoke-alarms/Ionization-vs-photoelectric
↑ https://www.youtube.com/watch?v=9qu4GCch-dM
↑ https://www.youtube.com/watch?v=jQV_MJwYQ3k
↑ https://www.youtube.com/watch?v=ZM5zO3L76QU
↑ https://www.youtube.com/watch?v=piofZLySsNc
↑ https://www.youtube.com/watch?v=BtMmymOxdjc
↑ http://demographia.com/db-intlhouse.htm
↑ https://www.dji.com/matrice100/info
↑ https://www.youtube.com/watch?v=9qu4GCch-dM
↑ https://www.youtube.com/watch?v=jQV_MJwYQ3k
↑ https://www.youtube.com/watch?v=ZM5zO3L76QU
↑ https://www.youtube.com/watch?v=piofZLySsNc
↑ https://www.youtube.com/watch?v=BtMmymOxdjc
↑ https://www.nfpa.org/Public-Education/By-topic/Top-causes-of-fire/Cooking/Reports-and-statistics-about-cooking-fires-and-safety
↑ https://en.wikipedia.org/wiki/Class_B_fire
↑ Royakkers, Lamber, and Rinie van Est. Just ordinary robots: automation from love to war. CRC Press, 2015
↑ https://www.blusstaaf.nl/home/1-blusstaaf-aerosol-handblusser.html
↑ https://www.dji.com/matrice100/info#specs
↑ Royakkers, Lamber, and Rinie van Est. Just ordinary robots: automation from love to war. CRC Press, 2015
↑ https://store.dji.com/product/matrice-100
↑ Cook. D.J. et al. (2003). MavHome: An agent-based smart home. Retrieved from: https://www.researchgate.net/profile/G_Youngblood/publication/4011271_MavHome_An_agent-based_smart_home/links/5451065f0cf2bf864cba8691/MavHome-An-agent-based-smart-home.pdf
↑ Aware Home Research Initiative. (2018). Retrieved from http://www.awarehome.gatech.edu/drupal/
↑ Brooks. R.A. The intelligent room project: cognitive technology, in: Proceedings of the 2nd International Cognitive Technology Conference, Aizu, Wakamatsu, Japan, 1997, pp. 271–278 taken from: http://people.csail.mit.edu/brooks/papers/aizu.pdf
↑ Lee, K. (2018). Network-based fire-detection system via controller area network for smart home automation - IEEE Journals & Magazine. Retrieved from https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1362504&tag=1
↑ Robles. R.J., Kim. T.H. (2010). A Review on Security in Smart Home Development. Retrieved from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.178.1685&rep=rep1&type=pdf
↑ https://uavcoach.com/tipping-points/
↑ https://designmind.frogdesign.com/2014/03/drones-will-save-life/
↑ https://www.theverge.com/2018/4/13/17206398/zipline-drones-delivery-blood-emergency-medical-supplies-startup-rwanda-tanzania
↑ https://www.aerones.com/eng/drones/firefighting_drone/
↑ Kim, Y.-D., Kim, Y.-G., Lee, S.-H., Kang, J.-H., An, J. “Portable fire evacuation guide robot system” (2009) IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, art. no. 5353970, pp. 2789-2794.
↑ Remington, Raquel, et al. "Multi-Purpose Aerial Drone for Bridge Inspection and Fire Extinguishing." (Unpublished Thesis). Florida International University. Retrieved April 10 (2014): 2016.
↑ Suresh, Jayanth. "Fire-fighting robot." Computational Intelligence in Data Science (ICCIDS), 2017 International Conference on. IEEE, 2017.
↑ Nieuwenhuisen, M., Droeschel, D., Beul, M., Behnke, S. Autonomous Navigation for Micro Aerial Vehicles in Complex GNSS-denied Environments (2016) Journal of Intelligent and Robotic Systems: Theory and Applications, 84(1-4), pp. 199-216.
↑ Mac, T.T., Copot, C., Hernandez, A., De Keyser, R. Improved potential field method for unknown obstacle avoidance using UAV in indoor environment (2016) SAMI 2016 - IEEE 14th International Symposium on Applied Machine Intelligence and Informatics - Proceedings, art. no. 7423032, pp. 345-350.
↑ Pestana, J., Mellado-Bataller, I., Fu, C., Sanchez-Lopez, J.L., Mondragon, I.F., Campoy, P. A general purpose configurable navigation controller for micro aerial multirotor vehicles (2013) International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings, art. no. 6564733, pp. 557-564.
↑ ANDRILUKA, Mykhaylo, et al. Vision based victim detection from unmanned aerial vehicles. In: Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on. IEEE, 2010. p. 1740-1747.
↑ TRIERSCHEID, Marina, et al. Hyperspectral imaging or victim detection with rescue robots. In: Safety, Security and Rescue Robotics, 2008. SSRR 2008. IEEE International Workshop on. IEEE, 2008. p. 7-12.
↑ DE CUBBER, Geert; MARTON, Gabor. Human victim detection. In: Third International Workshop on Robotics for risky interventions and Environmental Surveillance-Maintenance, RISE. 2009.
↑ SUGIYAMA, Hisayoshi; TSUJIOKA, Tetsuo; MURATA, Masashi. Victim Detection System for Urban Search and Rescue Based on Active Network Operation. In: HIS. 2003. p. 1104-1113.
↑ KLEINER, Alexander; KUMMERLE, Rainer. Genetic MRF model optimization for real-time victim detection in search and rescue. In: Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on. IEEE, 2007. p. 3025-3030.
↑ SACHS, Jürgen, et al. Trapped victim detection by pseudo-noise radar. In: Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief. ACM, 2011. p. 265-272.
↑ CHEN, Thou-Ho; WU, Ping-Hsueh; CHIOU, Yung-Chuen. An early fire-detection method based on image processing. In: Image Processing, 2004. ICIP'04. 2004 International Conference on. IEEE, 2004. p. 1707-1710.
↑ YAMAGISHI, Hideaki; YAMAGUCHI, JUNICHI. Fire flame detection algorithm using a color camera. In: Micromechatronics and Human Science, 1999. MHS'99. Proceedings of 1999 International Symposium on. IEEE, 1999. p. 255-260.
↑ CELIK, Turgay, et al. Fire detection using statistical color model in video sequences. Journal of Visual Communication and Image Representation, 2007, 18.2: 176-185.
↑ NODA, S.; UEDA, K. Fire detection in tunnels using an image processing method. In: Vehicle Navigation and Information Systems Conference, 1994. Proceedings., 1994. IEEE, 1994. p. 57-62.
↑ Liu, Z., Kim, A.K., Carpenter, D. A study of portable water mist fire extinguishers used for extinguishment of multiple fire types (2007) Fire Safety Journal, 42 (1), pp. 25-42.
↑ Korobeinichev, O.P., Shmakov, A.G., Shvartsberg, V.M., Chernov, A.A., Yakimov, S.A., Koutsenogii, K.P., Makarov, V.I. Fire suppression by low-volatile chemically active fire suppressants using aerosol technology (2012) Fire Safety Journal, 51, pp. 102-109.
↑ Kibert, C.J., Dierdorf, D. Solid particulate aerosol fire suppressants (1994) Fire Technology, 30 (4), pp. 387-399.
↑ Kibert, C., Dierdorf, D. ENCAPSULATED MICRON AEROSOL AGENTS (EMAA)
↑ Lyon, Richard E., et al. "Fire‐resistant aluminosilicate composites." Fire and materials 21.2 (1997): 67-73.
↑ Myeong, W. C., Kwang Yik Jung, and Hyun Myung. "Development of FAROS (fire-proof drone) using an aramid fiber armor and air buffer layer." Ubiquitous Robots and Ambient Intelligence (URAI), 2017 14th International Conference on. IEEE, 2017.
↑ Myeong, Wancheol, Kwang Yik Jung, and Hyun Myung. "Development of a fire-proof aerial robot system for fire disaster." World Congress on Advances in Nano, Bio, Robotics and Energy (ANBRE). IASEM Conferences, 2017.
↑ Abbott, N. J., M. M. Schoppee, and J. Skelton. Heat Resistant and Nonflammable Materials. FABRIC RESEARCH LABS INC DEDHAM MA, 1976.
↑ Luo, Qiu-Sheng, Shi-Feng Li, and Hui-Ping Pei. "Progress in titanium fire resistant technology for aero-engine." Journal of Aerospace Power 27.12 (2012): 2763-2768

[1] ttps://www.nfpa.org/Public-Education/Campaigns/Fire-Prevention-Week/Fire-Facts

[2] ttps://autoriteitpersoonsgegevens.nl/nl/onderwerpen/avg-europese-privacywetgeving/algemene-informatie-avg

[3] ttps://www.gearbrain.com/average-smart-home-build-cost-2589554626.html

[4] ttps://www.nfpa.org/Public-Education/By-topic/Smoke-alarms/Ionization-vs-photoelectric

[5] ttps://www.youtube.com/watch?v=9qu4GCch-dM

[6] ttps://www.youtube.com/watch?v=jQV_MJwYQ3k

[7] ttps://www.youtube.com/watch?v=ZM5zO3L76QU

[8] ttps://www.youtube.com/watch?v=piofZLySsNc

[9] ttps://www.youtube.com/watch?v=BtMmymOxdjc

[10] ttp://demographia.com/db-intlhouse.htm

[11] ttps://www.dji.com/matrice100/info

[12] ttps://www.youtube.com/watch?v=9qu4GCch-dM

[13] ttps://www.youtube.com/watch?v=jQV_MJwYQ3k

[14] ttps://www.youtube.com/watch?v=ZM5zO3L76QU

[15] ttps://www.youtube.com/watch?v=piofZLySsNc

[16] ttps://www.youtube.com/watch?v=BtMmymOxdjc

[17] ttps://www.nfpa.org/Public-Education/By-topic/Top-causes-of-fire/Cooking/Reports-and-statistics-about-cooking-fires-and-safety

[18] ttps://en.wikipedia.org/wiki/Class_B_fire

[19] Royakkers, Lamber, and Rinie van Est. Just ordinary robots: automation from love to war. CRC Press, 2015

[20] ttps://www.blusstaaf.nl/home/1-blusstaaf-aerosol-handblusser.html

[21] ttps://www.dji.com/matrice100/info#specs

[22] Royakkers, Lamber, and Rinie van Est. Just ordinary robots: automation from love to war. CRC Press, 2015

[23] ttps://store.dji.com/product/matrice-100

[24] Cook. D.J. et al. (2003). MavHome: An agent-based smart home. Retrieved from: https://www.researchgate.net/profile/G_Youngblood/publication/4011271_MavHome_An_agent-based_smart_home/links/5451065f0cf2bf864cba8691/MavHome-An-agent-based-smart-home.pdf

[25] Aware Home Research Initiative. (2018). Retrieved from http://www.awarehome.gatech.edu/drupal/

[26] Brooks. R.A. The intelligent room project: cognitive technology, in: Proceedings of the 2nd International Cognitive Technology Conference, Aizu, Wakamatsu, Japan, 1997, pp. 271–278 taken from: http://people.csail.mit.edu/brooks/papers/aizu.pdf

[27] Lee, K. (2018). Network-based fire-detection system via controller area network for smart home automation - IEEE Journals & Magazine. Retrieved from https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1362504&tag=1

[28] Robles. R.J., Kim. T.H. (2010). A Review on Security in Smart Home Development. Retrieved from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.178.1685&rep=rep1&type=pdf

[29] ttps://uavcoach.com/tipping-points/

[30] ttps://designmind.frogdesign.com/2014/03/drones-will-save-life/

[31] ttps://www.theverge.com/2018/4/13/17206398/zipline-drones-delivery-blood-emergency-medical-supplies-startup-rwanda-tanzania

[32] ttps://www.aerones.com/eng/drones/firefighting_drone/

[33] Kim, Y.-D., Kim, Y.-G., Lee, S.-H., Kang, J.-H., An, J. “Portable fire evacuation guide robot system” (2009) IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, art. no. 5353970, pp. 2789-2794.

[34] Remington, Raquel, et al. "Multi-Purpose Aerial Drone for Bridge Inspection and Fire Extinguishing." (Unpublished Thesis). Florida International University. Retrieved April 10 (2014): 2016.

[35] Suresh, Jayanth. "Fire-fighting robot." Computational Intelligence in Data Science (ICCIDS), 2017 International Conference on. IEEE, 2017.

[Nieuwenhuisen-36] Nieuwenhuisen, M., Droeschel, D., Beul, M., Behnke, S. Autonomous Navigation for Micro Aerial Vehicles in Complex GNSS-denied Environments (2016) Journal of Intelligent and Robotic Systems: Theory and Applications, 84(1-4), pp. 199-216.

[Mac-37] Mac, T.T., Copot, C., Hernandez, A., De Keyser, R. Improved potential field method for unknown obstacle avoidance using UAV in indoor environment (2016) SAMI 2016 - IEEE 14th International Symposium on Applied Machine Intelligence and Informatics - Proceedings, art. no. 7423032, pp. 345-350.

[Pestana-38] Pestana, J., Mellado-Bataller, I., Fu, C., Sanchez-Lopez, J.L., Mondragon, I.F., Campoy, P. A general purpose configurable navigation controller for micro aerial multirotor vehicles (2013) International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings, art. no. 6564733, pp. 557-564.

[39] ANDRILUKA, Mykhaylo, et al. Vision based victim detection from unmanned aerial vehicles. In: Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on. IEEE, 2010. p. 1740-1747.

[40] TRIERSCHEID, Marina, et al. Hyperspectral imaging or victim detection with rescue robots. In: Safety, Security and Rescue Robotics, 2008. SSRR 2008. IEEE International Workshop on. IEEE, 2008. p. 7-12.

[41] DE CUBBER, Geert; MARTON, Gabor. Human victim detection. In: Third International Workshop on Robotics for risky interventions and Environmental Surveillance-Maintenance, RISE. 2009.

[42] SUGIYAMA, Hisayoshi; TSUJIOKA, Tetsuo; MURATA, Masashi. Victim Detection System for Urban Search and Rescue Based on Active Network Operation. In: HIS. 2003. p. 1104-1113.

[43] KLEINER, Alexander; KUMMERLE, Rainer. Genetic MRF model optimization for real-time victim detection in search and rescue. In: Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on. IEEE, 2007. p. 3025-3030.

[44] SACHS, Jürgen, et al. Trapped victim detection by pseudo-noise radar. In: Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief. ACM, 2011. p. 265-272.

[45] CHEN, Thou-Ho; WU, Ping-Hsueh; CHIOU, Yung-Chuen. An early fire-detection method based on image processing. In: Image Processing, 2004. ICIP'04. 2004 International Conference on. IEEE, 2004. p. 1707-1710.

[46] YAMAGISHI, Hideaki; YAMAGUCHI, JUNICHI. Fire flame detection algorithm using a color camera. In: Micromechatronics and Human Science, 1999. MHS'99. Proceedings of 1999 International Symposium on. IEEE, 1999. p. 255-260.

[47] CELIK, Turgay, et al. Fire detection using statistical color model in video sequences. Journal of Visual Communication and Image Representation, 2007, 18.2: 176-185.

[48] NODA, S.; UEDA, K. Fire detection in tunnels using an image processing method. In: Vehicle Navigation and Information Systems Conference, 1994. Proceedings., 1994. IEEE, 1994. p. 57-62.

[Liu-49] Liu, Z., Kim, A.K., Carpenter, D. A study of portable water mist fire extinguishers used for extinguishment of multiple fire types (2007) Fire Safety Journal, 42 (1), pp. 25-42.

[Korobeinichev-50] Korobeinichev, O.P., Shmakov, A.G., Shvartsberg, V.M., Chernov, A.A., Yakimov, S.A., Koutsenogii, K.P., Makarov, V.I. Fire suppression by low-volatile chemically active fire suppressants using aerosol technology (2012) Fire Safety Journal, 51, pp. 102-109.

[kibert-51] Kibert, C.J., Dierdorf, D. Solid particulate aerosol fire suppressants (1994) Fire Technology, 30 (4), pp. 387-399.

[kibert2-52] Kibert, C., Dierdorf, D. ENCAPSULATED MICRON AEROSOL AGENTS (EMAA)

[53] Lyon, Richard E., et al. "Fire‐resistant aluminosilicate composites." Fire and materials 21.2 (1997): 67-73.

[54] Myeong, W. C., Kwang Yik Jung, and Hyun Myung. "Development of FAROS (fire-proof drone) using an aramid fiber armor and air buffer layer." Ubiquitous Robots and Ambient Intelligence (URAI), 2017 14th International Conference on. IEEE, 2017.

[55] Myeong, Wancheol, Kwang Yik Jung, and Hyun Myung. "Development of a fire-proof aerial robot system for fire disaster." World Congress on Advances in Nano, Bio, Robotics and Energy (ANBRE). IASEM Conferences, 2017.

[56] Abbott, N. J., M. M. Schoppee, and J. Skelton. Heat Resistant and Nonflammable Materials. FABRIC RESEARCH LABS INC DEDHAM MA, 1976.

[57] Luo, Qiu-Sheng, Shi-Feng Li, and Hui-Ping Pei. "Progress in titanium fire resistant technology for aero-engine." Journal of Aerospace Power 27.12 (2012): 2763-2768

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PRE2018 1 Group1: Difference between revisions

Latest revision as of 21:06, 29 October 2018

Preface

Group members

Initial robotic concepts

Chosen concept: Fast Response Extinguish Drone, F.R.E.D.

Introduction

Problem statement

Objectives

Project setup

Approach

Milestones

Deliverables

Planning: Who's doing what

USE analysis

Relevant users and their requirements

Personas

Scenario

Hardware and design

Overall system and Smart Home

Response Time

Placement in building

Reporting the fire

Travel distance and time

Conclusion

Autonomous navigation and fire localization

Global navigation and obstacle avoidance

Fire localization

Fire suppression

Extinguisher requirements

Extinguish mechanism

Extinguishing using a solid aerosol (blusstaaf)

Attachment of extinguish mechanism

Activation of extinguisher

Reaction force on drone

Drone

Requirements Drone

Important aspects

Possible candidate

List of Materials for F.R.E.D.

Demonstration and prototype

Drone for prototype

Extinguisher for prototype

Extinguisher using waterpump

Activation of extinguisher

Weight

List of Materials for prototype

Testing of the prototype

Conclusion

Future Research

Background/research

Expert Interviews

Fire department TU/e

Drone Unit Fire Department Rotterdam

Brandwonden Centrum Maasstad Ziekenhuis Rotterdam

State of the art: Literature study

State of the Art Smart Homes

Drones in firefighting

conclusion

General Drone Information

Autonomous drone navigation

Autonomous victim detection

Fire detection

Fire suppression

Fire resistant materials

Sources

Usefull Links

Navigation menu

Search