PRE2016 3 Groep12

Group members

• Bibi Huijgen - 0906203
• Jamiro Leander
• Jari de Kroon - 0888168
• Juan van der Heijden - 0898805
• Plamen Pasliev - 0890518
• Stan Roelofs - 0892914

Introduction

In the year 2015 over 500000 cases of burglary and theft were recorded in the Netherlands . It is by far the most common type of crime, around 57% of all crimes recorded in 2015 were related to burglaries. A recent trend is to setup neighbourhood prevention systems through mobile applications, however the effectiveness of this is limited due to the fact that most people will sleep at night when most burglary cases occur. Our aim is to reduce the big number of burglaries through the application of surveillance / security drones in areas where criminal rates are high. The drones should detect inappropriate behavior using an anomaly detection system.

Several issues arise in the application of drones:

• Legal issues regarding no fly zones and privacy.
• Technical issues related to the safety of the drone, since it will be flying near people.
• Using drones might be costly.

Besides the decreased rate of crimes, the introduction of this technology will allow for faster response times to other related crimes and hazards. The goal is to give the citizens an increased sense of security and safety.

Objectives

• Research what the effects on society will be when security drones are deployed.
• Research what the costs would be to deploy surveillance drones.
• Research the legal issues regarding surveillance drones.
• Find out what people think about surveillance drones.

Approach

• Research state of the art technologies using books and articles.
• Make an analysis of the current legislation regarding relevant topics such as filming humans and flying drones. Find out how privacy can be preserved and finally investigate if the current laws can be changed and how.
• Find out what people think of drones surveilling their neighbourhoods by making a survey and interviewing people.
• Make a financial model in Java where the input is an area and level of security and the output is the number of drones, cameras, or people that are needed to watch the area. To make the model we first have to use a drone to find out how high a drone can fly while still detecting humans without issues. We also need to know the costs of drones, security cameras, and people, and how long drones can fly before they have to be charged.

USE aspects

Users: Since these robots will most likely be used by our local police department, the primary users are police employees responsible for operating these machines. Currently, surveillance is mostly done using cameras or human security guards and it is very limited. Covering a large area is a challenge using those methods, so if a crime or a disaster happens, the response and reaction time of the police will not be optimal. This robot will deal with detecting and allocating the problem in a swift manner, which otherwise would cause a lot of problems to the responsible authorities. Furthermore, if more of these drones are deployed, we are going to have less human surveillance guards. Having less humans in a potentially dangerous area is an important factor.

Society: Surveillance drones are not stationary like a camera and in terms of mobility they are much better than a human walking around. That means a single device can cover a much larger area than humans or security cameras. Hence, if a crime or a disaster happens, the reaction time of the police department would be much faster. This means that more crimes can be prevented and criminals would be deterred from committing crimes because they are more likely to be caught. Society will benefit greatly in an environment with less criminal activity, and more prevented disasters like fires or leaking of gas. This would cause people to feel more secure and experience less stress in their everyday life.

Enterprise: Manufactoring, developing and maintaining such drones can initiate the beginning of many businesses.

Financial Model

Human detection software

For the Human detectin software we found a framework called openCV: http://opencv.org/

We are going to try and implement this framework so that we can see from how far the drone's camera can still recognize a human.

Costs

Listed below are the factors we think will play a role in the costs of implementing this system in society:

Drones One time costs

• Cost of a drone
• Cost of camera
• Cost of charging stations
• Amount of drones needed
• Amount of charging stations needed

Continues costs

• Range drone can search (height detection, speed)
• Battery life
• Cost of electricity
• Lifetime of a drone
• Detection efficiency

Cameras

-Cost of cameras -Lifetime of a camera -Amount of cameras needed -Percentage of ground covered -Detection efficiency

Police

-Police salary -Cost of police car -Amount of police needed -Amount of police cars needed -Covered ground -Detection efficiency

Planning

Gantt chart: https://drive.google.com/open?id=1bb1QMkg4TYDTVDhT7nHERBCg_1VZtb98BMwWiS9wT6I

Weekly logbook

Week 1 Starting here, the project was introduced and we formed groups. To generate an innovative and feasible idea, we held several brainstorm sessions. Coming up with a realistic approach to cure a relevant problem using technology, we shifted from several perspectives. In the end, we formulated a topic of research that entailed both security issues and privacy legislation. The basic ideas were covered in a presentation, to be given in week 2. We tried to create slides that were concise and complete, without too much text and with use of visuals.

Week 2 The presentation was completed and we started on the Wiki page. We figured that the regular update of the Wiki will contribute strongly to our progress. Besides, this logbook gives a good overview of our objectives and the aspects of the project that were already covered.

On Thursday, the presentation of the chosen project challenge will be given. Feedback from the other students and the expert panel can be implemented.

Week 3 After getting feedback on our first presentation, we had to change important aspects of our research plan. The most important parts that needed attention were stakeholders, privacy and benefit. We devided tasks, related to personal skill. You either work on programming or on the social/public part that considers law. In the future, it will be important to keep close communication between group members to ensure that everybody understands the progress in the two directions. It is obvious that the technology and society must work together to realize success.

Besides deviding tasks and narrowing down the procedure, time management was a very important part of this second week. The planning of the project needed a lot of time but it is a precondition for success. Now we know what, when and how to deliver parts and when we stick to the Gantt chart, we will realize an optimal research project.

We presented our time planning including the deadlines and tasks we defined. This is an important moment for feedback, as this is the last moment to check your project planning and idea in public. Something else that needed attention, was our resource allocation. It was important to check whether our ideas were feasible. After all, we planned out a detailed project and included our feedback.

Week 4 The division of tasks, created together with the Gantt chart, was executed this week for the first time. On Monday, the group was split in two, where three of us started to create the financial model and try the drone while the others focused on law and legislation. This second group tried to contact the police office, too. We suspected that officers would have a very realistic view on our project and their opinion should be taken seriously. Unfortunately, one of our group members had an accident so we were working with five most of the time this week.

On Thursday, we have planned a feedback session with our expert panel. Learning goals will be discussed and evaluated. Weekly feedback session between individual groups and expert panel. Feedback is on both learning goals (technical content and process).

Week 5 Weekly feedback session between individual groups and expert panel. Feedback is on both learning goals (technical content and process).

Week 6 Weekly feedback session between individual groups and expert panel. Feedback is on both learning goals (technical content and process).

Week 7 Weekly feedback session between individual groups and expert panel. Feedback is on both learning goals (technical content and process).

Week 8 Final presentation and demonstration