The independent life of the individuals suffering from Alzheimer's disease (AD) is compromised due to their memory loss, and as a result they always depend on someone by their side to help them lead their daily life. In this situation, generally, either the family members or the caregivers extend their helping hands; they attach notes on every single object or take out the contents of a drawer, the family might need to make those visible when they leave the patient alone at home. The goal of this study is to provide some helping means for the patient and the family members through existing science and technology. This study reports preliminary results on an Ambient Assisted Living (AAL) realtime system, achieved through Internet of Things (IoT) and Augmented Reality (AR) concepts, to fulfil this goal. The system has two main sections: the first one is the smartphone or windows application that allows caregivers/family-members to monitor a patient’s status at home and be notified if patient are at risk. The second part allows patient to use smart glasses to recognize QR codes in the environment and receive information related to the tags in the form of audio, text or three-dimensional image. This work presents preliminary results and investigates the possibility of implementing such a system.

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Evaluating the Possibility of Integrating AR and
IoT Technologies to Help Patients with
Alzheimer’s Disease
Authors: Fatemeh Ghorbani, Mohammad Kia, Mehdi
Delrobaei, Quazi Rahman
Presenter: Fatemeh Ghorbani
K. N. Toosi University of Technology
Western University

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Outline
1. Introduction
2. Internet of Things implementation
3. Augmented Reality application
• General architecture of Ambient Assisted Living system
4. Scenarios of use
5. Results and analytics
6. Conclusion
7. Future works

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Introduction
I. Statement of the problem
II. Related works and their advantages and
disadvantages
III. The presented approach

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I. Statement of the problem
• Alzheimer’s disease (AD) is
the main common cause of
dementia.
• Approximately 5.8 million
Americans are suffering from
AD in 2019.

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I. Statement of the problem
• Loss of memory is the
main difficulty
experienced by patients
with AD.
• This can disrupt the
patients’ life and their
family’s daily life.
$

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II. Related works
• AR based system
• Ambient aNnotation
(ANS)
• IoT based system
• Ambient Assisted Living
(AAL)

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III. The presented method

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Internet of Things implementation
• MQTT protocol
• Published-subscribed message
transfer protocol
• Extremely lightweight
• Sensors, actuators and QR
codes
• Monitoring patients and
making interaction with them
• Platform
• HiveMQ as a MQTT messages
broker
MQTT Broker
Relay actuator
Flame sensor
Temperature sensor
Relay actuator
PIR motion sensor
Rain sensor
Android
smartphone
Google Glass
Laptop/PC
Publish to
specific topic
Subscribe to
specific topic

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 General architecture of AAL system
Relay
actuator
PIR motion sensor
Rain sensor
Temperature
sensor
Relay
actuator
Flame sensor

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Augmented reality application
• Google Glass
• Visualization device
• Lightweight
• Short-term training for
mild to moderate AD
patient
• Software implementation on
the smartphone
• ARCore platform
• Picture, audio and/or text
messages

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Scenarios of use
1) When a relay actuator is activated, the user receives an audio message.
2) If the user enters the kitchen and the PIR detects , the user can see a picture
and an audio messages.
3) If the temperature sensor detects that the indoor weather is cold, then a text
message is shown.
4) If the flame sensor detects a flame or fire, then the relay actuator is activated.

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Results and analytics
• QR code minimum size
1. Camera parameters
2. Number of modules
3. The distance between the code and the scanner
4. Scanning environment quality
• Based on 12MP camera and computational result: at least
21*21mm printed QR code

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Results and analytics (Cont.)
• Response-time
• Image message: an
average 106ms
• Audio message: an
average 364ms
• Playing audio message
instead of displaying image
message: better
performance and less
battery consumption.
• Using QR code: decrease the
response time

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Results and analytics (Cont.)
• Network latency: estimated to be 120ms
• System response-time evaluation
• No data loss
• Real-time performance
• Battery consumption: low
• The system makes AD patients live more independently through
interaction: reliable alarms based on patients memory difficulties
• Caregivers and family members can monitor patient via IoT platform

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Conclusion
• AAL system: integration of IoT and AR to help mild to
moderate AD patients
• Playing audio message instead of displaying image
message: better performance and less battery
consumption
• MQTT: adopted for a quick and reliable messaging
transport

16. Future works
• Implementing in AD patients’ real-life scenarios
• Take advantage of indoor positioning system instead
of QR codes
• Designing cloud decision-making engine by using
Fuzzy method
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