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[[File:Onderkant.jpg|thumb|300px|Fig. 1: Under side tullip]]
[[File:Onderkant.jpg|thumb|300px|Fig. 1: Under side tullip]]
=== 3D-model ===
=== 3D-model ===
The original tulip-model came from thingiverse: https://www.thingiverse.com/thing:1429882. It was edited in FreeCAD to make room for the electronics. The inside of the tulip was hollowed out to be able to install a speaker and a bunch of LEDs. A hole was made through the stem of the tulip all the way to the electronics to be able to wire everything. The rest of the electronics will be installed in the plant tray below the tulip.
The original tulip-model came from thingiverse: https://www.thingiverse.com/thing:1429882. The tulip is made from three elements, the stem, a leaf and the flower itself. The stem and the flower were edited in FreeCAD to make room for the electronics. The inside of the flower was hollowed out to be able to install a speaker and a bunch of LEDs (see figure 3). A hole was made through the stem of the tulip all the way to the electronics to be able to wire everything (See figure 1 and 2). The rest of the electronics will be installed in the plant tray below the tulip.


The model was printed with transparent plastic. This way the LEDs can make the tulip change colors.
The model was printed with transparent plastic. This way the LEDs can make the tulip change colors.

Revision as of 11:38, 20 May 2018

Group members

  • Isabelle Cooijmans | 1014516 | i.h.m.cooijmans@student.tue.nl
  • Ramon Hameleers | 0998964 | r.j.e.hameleers@student.tue.nl
  • Angelique Husson | 0956648 | a.c.e.husson@student.tue.nl
  • Marrit Jen Hong Li | 0963568 | m.i.jen.hong.li@student.tue.nl
  • Dana de Vreede | 1020836 | d.d.vreede@student.tue.nl

Previous idea

Our Previous Idea can be found on this page.

Introduction

Problem statement

Elderly suffering from dementia often have problems managing their daily activities and independent living can become difficult. The decline in memory forms a big problem and an interactive reminder system could help these people to create a daily routine based on certain events.

Objective

Our goal is to help elderly in the early stages of dementia. They will be helped in the form of an interactive system primarily focussed on letting the patient water its plants at specific times and let the plant be a reminder for certain periodical things, like eating and medicine. Firstly, by creating this repeated event, elderly will create a stronger daily routine. Such a routine provides consistency and a predictable time slot, in which to return to valued occupations [1]. Secondly, our objective is to research whether the shape of such a system contributes to the functionality of it.

Thus the main objective can be split into two sub-objectives:

  • A system that creates a routine for the patient.
  • Investigating the impact of shape on functionality.

These sub-objectives will be explained in more detail further in this wiki page.

Users

The users of the technology formulate certain requirements or wishes for the functioning of the technology. The users are a diverse group and therefore they will be split up into three kind of users: primary, secondary and tertiary users. The primary users are the users that come directly into contact with the technology and directly benefit from it. Secondary users will use the technology infrequently or not directly. Tertiary users are the users who are affected by the technology or make decisions about its purchase.

The primary users are:

  • Elderly in the beginning stages of dementia

The secondary users are:

  • The care takers
  • The family, friends and loved ones
  • The government

The tertiary users are:

  • The technicians

Requirements

The three different types of users described in the previous section all have requirements. These requirements are listed below. Requirements of primary users:

  • The elderly with a decline in memory need a system that will help them remember specific tasks
  • The elderly need a daily routine to improve their well-being

The specific tasks that the elderly can be remembered of are tasks such as:

  • A reminder to water the plants
  • A reminder to take in medicine
  • A reminder to have a meal

Requirements of the secondary users:

  • The secondary users need their elderly to be healthy
  • The secondary users need their elderly to be helped to remember basic tasks

Requirements of the tertiary users:

  • The tertiary users need a system that is easy to install and easy to maintain.
  • The tertiary users need a system that gives a notification in case of an error or when it needs maintenance.

Approach, milestones and deliverables

Having something to care for, keeps people busy and makes life more enjoyable. For example, having a plant and hence the responsibility to take care of that plant can serve as occupational therapy and ease the mind. Taking care of a plant could have a positive impact on someone’s life, especially when they feel lonely. Imagine that this plant is no ordinary plant but a robot plant, that can speak or give signals to the owner. This plant can give forgetful elderly people something they can nurture, but can also give the owner reminders of basic tasks. This robotic plant could for example remind the owner that the plant needs water to stimulate the nurturing aspect and compliment the owner when he or she does a great job caring for the plant. The plant can also give the owner a reminder at a specific time of the day in which the plant asks if the owner has already taken their medicine or to ask if the owner has already eaten. The owner can then respond by pressing a button. In return, the plant can then again complement the owner or stimulate the owner to do their daily activity and so the owner will create a daily routine. The plant is meant as a playful device from which the elderly will benefit, namely, increase their well-being and which they will also enjoy.

Our goal is to deliver a prototype of a robotic plant that will be tested with the involvement of the users and is capable of the following actions:

  • The robotic plant notifies the user that the plant needs care
  • The robotic plant gives positive signals when it is properly nurtured, or stimulates the user to nurture when it is not cared for
  • The robotic plant can remind the owner of small specific tasks
  • The robotic plant is able to interact with the owner

Other deliverables are:

  • A presentation which will be given in the last week of this quartile. In this presentation, we will present our prototype of the robotic plant, discuss our findings and show our progress.
  • A finished wiki page which will include all our findings and progress made during this project. This will be extensively discussed.

Other milestones and deliverables can be seen in the planning. Group8Q4Planning.png


About some of the topic that is discussed before only a little research has been done as can be seen later in the literature study. Therefore some things will be tested using hypothesis tests. A hypothesis will be stated and this hypothesis will then be tested for example by taking the robotic plant to nursing homes and then conducting some questionnaires. This will be explained further in the following section called ‘Research’.

Research

What are our hypotheses?

The first hypothesis is that the user will be more interactive with a robot which has the shape of a plant than a robot shaped like a box. In the literature part, the effect of the caring character of PARO, the robotic seal, is that people with dementia started talking to the robot. A box does not have a caring character, but a plant does. So taking a robot shaped as a plant would probably be prefered over a box-shaped robot.

The second hypothesis is that a daily routine would have the same effect on men as it will have on woman. As F.M. Ludwig had shown is that a daily routine will have a positive impact on women. However, this test never was executed on men, thus our second hypothesis is that this effect will be similar.

Test plan

This project is about testing two things. Namely, whether the shape of the robot makes a difference in how actively the users will interact with it and whether a daily routine has the same effect on men as it does on woman, since the article only proofs it to have a positive effect on woman above 70 years.

Test about the shape

This effect can be tested by a survey. By asking about the general impression of the product, to what extent the patient appreciated it having in its close environment and how much the product helped the patient with its daily routine, the effect can be tested for each of the shapes. This can then be analysed and processed.

Test about gender

By testing the product in homes both with male and female inhabitants and investigating the survey, a possible difference can be found and perhaps explained. If not, an in-depth interview can sort out these differences.

How should this project be implemented in real life?

How would primary users interact with the device?

Expected effect on primary users

How would secondary users interact with the device?

Expected effect on secondary users

How would tertriary users interact with the device?

Expected effect on tertriary users

prototype

Result

Literature Study

In order to obtain more insight about the topic a literature study about the state of the art will be conducted. ...

General literature study about dementia therapy

Horticultural therapy in dementia care: a literature review.[2]

This article about horticultural therapy in dementia care combines 15 research articles together and gives a review about their findings. These research articles conducted studies about how dementia therapy affects the quality of life. Horticultural means the art and science of growing plants. The article has several findings about emotional health, self-identity and engagement. . Findings of this article are for example that gardening in groups has a positive effect as the elderly can socialize and talk about the gardening. Elderly suffering from dementia often have anxiety, agitation and depression symptoms that can lead to depression. This can have a significant effect on the quality of life. Several of these 15 studies have shown that horticultural therapy has a positive effect on these health symptoms. Since not all studies support this statement, the therapy does not support guaranteed sustained wellbeing or reducing the distress for all people. However, it represents a means by which carers can encourage elderly living with dementia to engage in meaningful activity. The main conclusion of the article is that horticultural therapy can benefit elderly suffering from dementia in several ways.

Contact with outdoor greenery can support competence among people with dementia. [3]

Dynamorph: Montessori Inspired Desing for Seniors with Dementia Living in Long-Term Care Facilities [4]

Robots that help elderly with cognitive problems

Paro [5]

Apathy, agitation, loneliness and depression are common behavioral and psychological symptoms of dementia. These symptoms can make life distressing for the person with dementia and can also make it challenging for care staff to meet the needs of the person. In recent years, social robots have been used as a means to reduce this. Both animalistic robots, such as Paro, or robotic toys make the patients enjoy their time more and thus improve their well-being. Such an effect can also be created using plants or other systems the elder has to take care of.

Robots who take care of plants

The Pet Plant: Developing an inanimate emotionally interactive tool for the Elderly [6]

The effect of pets on the health of elderly is widely known and this effect can also be summoned by robot pets. Another alternative is to use

Low cost colour sensors for monitoring plant growth [7]

A relatively new area of research is that of non-destructive methods to measure the health status of plants. Such as looking at subtle changes in the colour of the leaves. This paper mainly focuses on low cost colour sensor for monitoring leaf colour of plant tissues.

To implement this system a autonomous robotic arm containing RGB colour, environmental and proximity sensors are used, as well as a camera. The robotic arm uses five stepper motors controlled through a motor controller and a micro-step driver. Their system was either compatible with the ColorPAI or the TCS 3200 colour sensor and both were controlled with a Basic Stamp microcontroller. The ColorPai uses a RGB LED light source and records the quantity of light reflected back from the object to determine the color. The TCS3200 illuminates the object with two white LEDs and interprets the colour of the object by producing a square wave with a frequency proportional to the light reflected by the object. A completely different way of determing plant leaf colour is by using an image captured by the camera and determining through software the colour of each pixel. This may however lead to false colour. For example when shadows from overlapping leaves are misinterpreted as colours of the leaves itself.

They only tested the TCS3200 and calibrated it across a broad range of green and yellow colours. In the end it had an average error around the 4% when determining an RGB color in the range of green and yellow colours.

Effect of gardens on the mood of the elderly heart [8]

A research done on the impact of different garden design on the mood and functioning of an elderly's heart. Organised and structured gardens benefit the health of the elderly. This means that a structured placement of plants throughout a house or elderly home will also improve the health of the patient.

Garden greenery and the health of older people in residential care facilities [9]

In this article, the relation between greenery gardens in elderly homes and the self-perceived health of the patients is examined. This was done by a vast amount of questionnaires for the residents of many elderly homes. Also elderly were asked to report on their personal health and garden visits. Both tests showed a positive and strong relationship between patient well-being and the accessibility of a garden. Visiting such a garden gives a sense of being away and even wondering about them gives a positive impact on the patients health. This information shows the importance of accessible greenery in elderly homes

Plant growth monitoring system, with dynamic user-interface [10]

The paper develops a prototype for an efficient plant growth monitoring system. It provides data about the environmental parameters surrounding the plant and maps the changes in plant growth to the inputs given by person caring for the plants, such as the quantity of water or fertilizers. It can also measure the plants height.

The system consists of a Raspberry Pi which analysis the output of multiple sensors and sends this data via Bluetooth to someone's phone. They also developed a user-friendly app which displays all this data. The system does not take care of the plants itself, it only monitors a variety of environmental parameters

Robotics in protected cultivation [11]

Right now there is a lot of research to increase automation in protected cultivation. Production of high-value plants is facing an increase in problems such as increased costs for employees and decrease in skills. Robotics can help decrease these problems. The problems can be sorted into different groups. For seeding, grafting and cutting there are already products which can do this just as there are for transporting, sorting, packaging and cleaning. However, there is still a lot to win in the department of weeding, thinning, leaf picking, protection and harvesting. The technical challenges in robotics are the fact that technologies have to deal with complex environments. There are two solutions which can be used in this case, advancing technology or modifying the environment.

Thermostats and measurements of oxygen(state of the house)

NeoFox Oxygen:[12]

This oxygen sensor shows oxygen sensing using two methods. First of all, by making an electrochemical compound that will conduct current based on oxygen levels in the material. This is a relatively easy method and gives linear dependency between the oxygen level and the current created, but will also consume the oxygen. Secondly, by using a fluorescent material that will react to oxygen, different sorts of light will be radiated. Based on the frequency, amplitude, and phase of this emission, the amount of oxygen can be determined. This second method may be faster and more reliable, but also more difficult to produce.

PhO2: Smartphone-based Blood Oxygen Level Measurement Systems using Near-IR and RED Wave-guided Light [13]

Measuring a patient's blood oxygen level plays a critical role in healthcare practices. In the paper, they develop a phone-based oxygen level estimation system which uses the camera and flashlight functions of a smartphone. Since the camera and the flashlight of a smartphone aren't made for this purpose, they encountered many challenges in using them for this purpose.

Blood oxygen level is often indicated by oxygen saturation measurement (SpO2). Accurately measuring SpO2 with a high frequency is critical in monitoring the well being of key organs and also to provide warning signs of abnormalities. One of the most common ways to measure SpO2 is by using a pulse oximetry system. This system comprises dedicated hardware and software. It works by project light beams at specific wavelengths deep into the users' finger, toe, earlobe, or other location. This light hits dedicated photoelectrodes and the intensity of the light received carries information that can be used to determine the users' SpO2. This way of measuring SpO2 is very reliable but it requires the user to purchase one and to carry it with them during the day. Patients often forget to take the device with them or forget to charge it. Also, different patients have very different finger and earlobe sizes and the devices are thus not always a good fit.

There are already many applications for smartphone out there that use the flashlight and camera to determine various blood properties. However, none have the ability to accurately estimate SpO2. This low accuracy is a result of the fundamental challenges when one tries to repurpose the camera and flashlight for SpO2 measurements. Examples of these challenges are:

  • One needs an IR wavelength
  • One needs to work around the varying movement, pressure, contacting area of the users' finger

In the paper, they develop a hardware add-on (PhO2) designed to be snapped on the phone as a phone case which has optical filters of different wavelengths. The add-on helps stabilize the users' finger. Due to the limitations of the phone's hardware, the reflected light captured by the PhO2 is further processed by dedicated algorithms.

Smart device for gas range [14]

This is a smart device, which knows when the gas is on and whether the stove is left unattended. In case of an unattended stove, the device will send a message to the user, which can shut off the gas supply or call for relevant party's immediate attention remotely. When sending the message fails or when there is no response, the device will automatically shut off the gas supply.

Iot-Based Intelligent Modeling of Smart Home Environment for Fire Prevention and Safety [15]

Fire detection has become an issue since it caused severe damage including the loss of human lives. To reduce property damage and save lives, early detection of a fire event is very effective. The installation of a fire alarm system is the most convenient way to detect a fire early and avoid losses.

In the paper, they propose an efficient, IoT-based intelligent home fire prevention system using multiple sensors, which each uses its own mechanism for detection.

In the paper, problems and challenges related to the current approaches are identified, GSM communication is used to alert the user at early stages, star topology is used for the deployment of sensors and communication between sensors and main home sink and the system concerning energy consumption is evaluated.

Design and Development of a Low-Cost, Portable Monitoring Device for Indoor Environment Quality [16]

In this article, the design and development of a low-cost, portable monitoring system for indoor environment quality(IEQ) is described. A prototype is made with commercially available low-cost sensors and a do-it-yourself approach is provided. The designed system monitors temperature, humidity, PM2.5, PM10, TVOC(x3), CO2, CO, IAQ, illuminance, and sound levels. The biggest advantage of this design is the low cost, since it provides a comprehensive, portable, and real-time monitoring solution, for less than 200 dollars.


A cheap and third-age-friendly home device for monitoring indoor air quality [17]

This article proposes a new methodology to analyze indoor air quality with a cheap and third-age-dedicated device. The researchers developed a prototype, which they called HOPES, Home Pollution Embedded System. This prototype gives simple and understandable information, also comprehensible for people with cognitive problems or that are not familiar with new technologies. The prototype gathers data about pollutants and displays the different air pollutants concentrations to the user. These air pollutants concentrations are from toxics gasses up to explosives. Furthermore, in the paper, an overall air quality index is elaborated and displayed by HOPES with lights and numerical information. HOPES is an internet of things device. Hopes works in real time and can be connected to a geographic information system platform and the web to add spatial information about each pollutant. The results highlighted how it is possible to get useful air quality information with a cheap device.

Medication reminders

Smart Home medication reminder system [18]

Many elderly people need assistance from nurses, housekeeping, and visitors that remind them to take their pills. New technologies can provide a medication reminder system. This article mainly focuses on the Open Home Automation Bus (openHAB). This is a software that integrates and thus combines different home technologies together. There are several smart technologies that help elderly people and this software can combine them and make it easy to use.

A WSN smart medication system [19]

It is very important that patients or elderly people take in their medicine correctly. However, for elderly, it often becomes difficult to remember whether or not they have already taken their medicine. Also when these people have lots of different pills it can become hard to remember which to take and when to take them. A wireless sensing network (WSN) system have been invented which can remind patients to take their medicine. The system consists of a master panel (MP) and portable smart pill-boxes (SPB). Magnetic sensors are used to detect whether or not there are pills in the (SPB). If not pill has been taken. This paper describes the three-state pill sensing mechanism and all other aspects of the wireless sensing network.

Medicine Reminder and Monitoring System for Secure Health Using IOT [20]

Elderly people sometimes tend to forget doing basic things among daily routine. This can lead to them forgetting to take their medicine at the right time of forgetting it entirely. Using the Internet of Things (IoT) network low-cost medical sensing can be produced. There have been multiple tests with technologies to find a way to decrease this problem. A monitoring system and sensor can send information using a wireless module. The information can be shared using IoT, however, since health information can be very personal an encryption or decryption purpose is recommended.

MESSAGE INA BOTTLE [21]

Medication reminders in the form of pill bottles are already available. The bottle can notify patients when they need to take their medication or missed a dose as well as seeing that the pills are almost out and notifying a pharmacy. This technology can not only increase the effectiveness of certain drugs but also reduce the readmission rates at hospitals. The pill bottle uses a sensor to detect opening and closing of the lit and compare its content. This is then sent to the startups server which can analyze the data. Using different colors of light the user is given an indication of when taking medication is necessary.

Robots who look at the eating of their users

An Intelligent Food-Intake Monitoring System Using Wearable Sensors. [22]

Researches are looking for accurate methods requiring less user-involvement to assess general food-intake. The paper proposes an intelligent foot-intake monitoring system that can automatically detect eating activities. An in-ear microphone with a miniature camera is combined in a light-weight wearable headset. The sound from the microphone is classified into different eating activities and the camera takes pictures of the food if a chewing activity is detected. The key images of food are then selected sequentially and a dietary assessment log is generated to reflect a user's dietary behaviour. Novelties in this design were:

  • Developing a noise-resilient sound activity detection method suitable for daily use
  • Introducing food images to improve assessment accuracy
  • Selecting key images automatically to minimize the size of the food-intake assessment log

Big fridge is watching you [23]

The smart kitchen is becoming reality. With the enormous increase of technology in everyday things one cannot deny the probability of a smart fridge. This fridge could use information from your wearables, agenda and smart devices to recommend meals. The used data can also be relayed to doctors or caregivers, for instance when an elderly is not eating enough. Furthermore, it can help people who tend to forget what is in the fridge with keeping an inventory and tracking expiration dates. This way an order could be placed for what is needed from the supermarket.

Automatic Dietary Monitoring Using Wearable Accessories [24]

In this article, a lot of research is done on how they modeled a person dietary. However, this is not really relevant to our project. But, later in the article a discussion is given about the state of the art of sensing technologies, integration in accessory-based wearable devices and estimated parameters of different dietary dimensions. After which the researchers explain which challenges must be addressed to make ADM technology viable.

Prototype

Fig. 1: Under side tullip

3D-model

The original tulip-model came from thingiverse: https://www.thingiverse.com/thing:1429882. The tulip is made from three elements, the stem, a leaf and the flower itself. The stem and the flower were edited in FreeCAD to make room for the electronics. The inside of the flower was hollowed out to be able to install a speaker and a bunch of LEDs (see figure 3). A hole was made through the stem of the tulip all the way to the electronics to be able to wire everything (See figure 1 and 2). The rest of the electronics will be installed in the plant tray below the tulip.

The model was printed with transparent plastic. This way the LEDs can make the tulip change colors.

Electronics

There are multiple circuits inside the tulip. Every single one corresponds adds a different functionality to the tulip.

LED-strip

References

  1. FEROL MENKS LUDWIG. (1997) How routine facilitates well-being in older women Occupational Therapy International, 4(3),215–230, 1997
  2. Blake, M. and Mitchell, G. (2016). Horticultural therapy in dementia care: a literature review. Nursing Standard, [online] 30(21), pp.41-47. Available at: http://10.7748/ns.30.21.41.s44.
  3. Rappe, E. and Topo, P. (2007). Contact with Outdoor Greenery Can Support Competence Among People with Dementia. Journal of Housing For the Elderly, [online] 21(3-4), pp.229-248. Available at: http://10.1300/j081v21n03_12.
  4. Feng Y., van Reijmersdal R., Yu S., Rauterberg M., Hu J., Barakova E. (2018) Dynamorph: Montessori Inspired Design for Seniors with Dementia Living in Long-Term Care Facilities. In: Chisik Y., Holopainen J., Khaled R., Luis Silva J., Alexandra Silva P. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 215. [online] available at: https://link.springer.com/chapter/10.1007/978-3-319-73062-2_4#citeas
  5. W. Moyle E.R. Beattie B. Draper D. Shum L. Thalib C. Jones (2017). A SOCIAL ROBOT CALLED PARO AND ITS EFFECT ON PEOPLE LIVING WITH DEMENTIA. Innovation in Aging, Volume 1, Issue suppl_1, 1 July 2017, Pages 344, https://doi-org.dianus.libr.tue.nl/10.1093/geroni/igx004.1261
  6. Seeyle M., Sen Gupta G., Bailey D. (2011). Low cost colour sensor for monitoring plant growth in laboratory. Instrumentation and Measurement Technology Conference. [online] Available at: https://ieeexplore.ieee.org/document/5944221/
  7. Seeyle M., Sen Gupta G., Bailey D. (2011) Low cost colour sensor for monitoring plant growth in laboratory. Instrumentation and Measurement Technology Conference. [online] Available at: https://ieeexplore.ieee.org/document/5944221/
  8. Goto, S., Park, B-J., Tsunetsugu, Y., Herrup, K., & Miyazaki, Y. (2013). The effect of garden designs on mood and heart output in older adults residing in an assisted living facility. Health Environments Research & Design Journal 6(2), pp 27-42.
  9. Eva Dahlkvist RN Terry Hartig MPH PhD Annika Nilsson PhD RN Hans Högberg PhD Kirsti Skovdahl PhD RN Maria Engström PhD RN (2016). Garden greenery and the health of older people in residential care facilities: a multi‐level cross‐sectional study. Journal of Advanced Nursing Published by John Wiley & Sons Ltd, Pages 2065-2076.
  10. James J., Manu Maheshwar P. (2017) Plant growth monitoring system, with dynamic user-interface. Humanitarian Technology Conference. [online] Available at: https://ieeexplore.ieee.org/document/7906781/
  11. E.J. van Henten, C.W. Bac, J. Hemming, Y. Edan, Robotics in protected cultivation, IFAC Proceedings Volumes, Volume 46, Issue 18, 2013, Pages 170-177, ISSN 1474-6670, ISBN 9783902823441, https://doi.org/10.3182/20130828-2-SF-3019.00070. (http://www.sciencedirect.com/science/article/pii/S147466701534979X)
  12. Neofox oxygen
  13. Bui N., Nguyen A., Nguyen P., Truong H., Ashok A., Dinh T., Deterding R., Vu T. (2017) PhO2: Smartphone-based Blood Oxygen Level Measurement Systems using Near-IR and RED Wave-guided Light. Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. [online] Available at: http://mnslab.org/tamvu/paper/2017%20PhO2%20Nam%20Bui.pdf
  14. Huang, L. and Chen, C., Smart device for gas range, United States Patent, 12 February 2015, https://patents.google.com/patent/US9752783B2/en
  15. Saeed, F., Paul, A., Rehman, A., Hong, W. H. and Seo, H. IoT-based Intelligent Modeling of Smart Home Environment for Fire Prevention and Safety, Journal of Sensor and Actuator Networks, vol. 7, issue 1, 2018, [online] available at: http://www.mdpi.com/2224-2708/7/1/11/htm
  16. Tiele, A., Esfahani, S. and Convington, J. Design and Development of a Low-Cost, Portable Monitoring Device for Indoor Environment Quality, journal of sensors, volume 2018, Article ID 5353816, 14 pages, [online] available at: https://www.hindawi.com/journals/js/2018/5353816/
  17. Gugliermetti, L. and Astiaso Garcia, D. A cheap and third-age-friendly home device for monitoring indoor air quality, International Journal of Environmental science and technology, Volume 15, Issue 1, pp 185-198, January 2018, [online] available at: https://link.springer.com/article/10.1007%2Fs13762-017-1382-3
  18. Ramljak, M. (2017). Smart home medication reminder system. 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM). [online] Available at: https://ieeexplore.ieee.org/document/8115585/
  19. Hsu, W., Kuo, C., Chang, W., Chang, J., Hou, Y., Lan, Y., Sung, T. and Yang, Y. (2010). A WSN smart medication system. Procedia Engineering, [online] 5, pp.588-591. Available at: https://doi.org/10.1016/j.proeng.2010.09.178
  20. Samir V. Zanjal, Girish. R. Talmale, Medicine Reminder and Monitoring System for Secure Health Using IOT, Procedia Computer Science, Volume 78, 2016, Pages 471-476, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2016.02.090. (http://www.sciencedirect.com/science/article/pii/S1877050916000922)
  21. Page, D. (2013). MESSAGE INA BOTTLE. Hospitals & Health Networks, 87(12), 16. Retrieved from https://search.proquest.com/docview/1470884471?accountid=27128
  22. Liu J., Johns E. Atallah L. (2012) An Intelligent Food-Intake Monitoring System Using Wearable Sensors. Wearable and Implantable Body Sensors Networks. [online] Available at: https://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6200559
  23. S. Cass, "Big fridge is watching you [smart technologies monitoring food from production to consuption]," in IEEE Spectrum, vol. 50, no. 6, pp. 88-88, June 2013. doi: 10.1109/MSPEC.2013.6521045 keywords: {Food manufacturing;Food production;Food technology;Foreacasting;Internet;Technology forecasting;Waste management}, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6521045&isnumber=6521004
  24. Schiboni, G. and Amft, O. Automatic Dietary Monitoring Using Wearable Accessories, Seamless Healthcare Monitoring, 369-412, January 2018, [online] available at: https://www.researchgate.net/publication/321293922_Automatic_Dietary_Monitoring_Using_Wearable_Accessories