Non-Wearable IoT-Based Smart Ambient Behavior Observation System

Muhammad Irfan; Husnain Jawad; Barkoum Betra Felix; Saadullah Farooq Abbasi; Anum Nawaz; Saeed Akbarzadeh; Muhammad Awais; Lin Chen; Tomi Westerlund; Wei Chen

doi:10.1109/JSEN.2021.3097392

Non-Wearable IoT-Based Smart Ambient Behavior Observation System

Muhammad Irfan, Husnain Jawad, Barkoum Betra Felix, Saadullah Farooq Abbasi, Anum Nawaz, Saeed Akbarzadeh, Muhammad Awais, Lin Chen, Tomi Westerlund, Wei Chen^*

^*Corresponding author for this work

Electronic, Electrical and Systems Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

A growing number of advanced smart systems and solutions are being designed for the elderly, helping them to live longer at home. These systems need to provide unobtrusive monitoring and safety for their users and information for the healthcare professionals and family members. Multi-modal sensor data enables the possibility for in-depth behavioral analysis. To gather multi-modal data, we propose an IoT-based smart ambient behavior observation system (SABOS). SABOS provides unobtrusive monitoring of daily living activities by utilizing various sensors integrated into the residential house. To reduce the amount of data, we present a data reduction algorithm. The data reduction algorithm effectively reduces over 90% of the submitted data with full recovery in the cloud. Data is sent to ThingSpeak for MATLAB visualization and analysis to generate graphical illustrations of daily living activities. In an emergency, an “if this then that” (IFTTT) service combined with ThingSpeak triggers an applet to send a defined message to a healthcare professional or a family member.

Original language	English
Article number	9486939
Pages (from-to)	20857-20869
Number of pages	13
Journal	IEEE Sensors Journal
Volume	21
Issue number	18
Early online date	15 Jul 2021
DOIs	https://doi.org/10.1109/JSEN.2021.3097392
Publication status	Published - 15 Sept 2021

Bibliographical note

Funding:
This work was supported in part by the National Key Research and Development Program of China under Grant 2017YFE0112000 and in part by the Shanghai Municipal Science and Technology International Research and Development Collaboration Project under Grant 20510710500.

Keywords

Ambient assisted living
data reduction algorithm
the IoT
feeling factor
capacitive touch sensor

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10.1109/JSEN.2021.3097392

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title = "Non-Wearable IoT-Based Smart Ambient Behavior Observation System",

abstract = "A growing number of advanced smart systems and solutions are being designed for the elderly, helping them to live longer at home. These systems need to provide unobtrusive monitoring and safety for their users and information for the healthcare professionals and family members. Multi-modal sensor data enables the possibility for in-depth behavioral analysis. To gather multi-modal data, we propose an IoT-based smart ambient behavior observation system (SABOS). SABOS provides unobtrusive monitoring of daily living activities by utilizing various sensors integrated into the residential house. To reduce the amount of data, we present a data reduction algorithm. The data reduction algorithm effectively reduces over 90% of the submitted data with full recovery in the cloud. Data is sent to ThingSpeak for MATLAB visualization and analysis to generate graphical illustrations of daily living activities. In an emergency, an “if this then that” (IFTTT) service combined with ThingSpeak triggers an applet to send a defined message to a healthcare professional or a family member.",

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author = "Muhammad Irfan and Husnain Jawad and Felix, {Barkoum Betra} and Abbasi, {Saadullah Farooq} and Anum Nawaz and Saeed Akbarzadeh and Muhammad Awais and Lin Chen and Tomi Westerlund and Wei Chen",

note = "Funding: This work was supported in part by the National Key Research and Development Program of China under Grant 2017YFE0112000 and in part by the Shanghai Municipal Science and Technology International Research and Development Collaboration Project under Grant 20510710500.",

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AU - Irfan, Muhammad

AU - Jawad, Husnain

AU - Felix, Barkoum Betra

AU - Abbasi, Saadullah Farooq

AU - Nawaz, Anum

AU - Akbarzadeh, Saeed

AU - Awais, Muhammad

AU - Chen, Lin

AU - Westerlund, Tomi

AU - Chen, Wei

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AB - A growing number of advanced smart systems and solutions are being designed for the elderly, helping them to live longer at home. These systems need to provide unobtrusive monitoring and safety for their users and information for the healthcare professionals and family members. Multi-modal sensor data enables the possibility for in-depth behavioral analysis. To gather multi-modal data, we propose an IoT-based smart ambient behavior observation system (SABOS). SABOS provides unobtrusive monitoring of daily living activities by utilizing various sensors integrated into the residential house. To reduce the amount of data, we present a data reduction algorithm. The data reduction algorithm effectively reduces over 90% of the submitted data with full recovery in the cloud. Data is sent to ThingSpeak for MATLAB visualization and analysis to generate graphical illustrations of daily living activities. In an emergency, an “if this then that” (IFTTT) service combined with ThingSpeak triggers an applet to send a defined message to a healthcare professional or a family member.

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KW - feeling factor

KW - capacitive touch sensor

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DO - 10.1109/JSEN.2021.3097392

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JF - IEEE Sensors Journal

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ER -

Non-Wearable IoT-Based Smart Ambient Behavior Observation System

Abstract

Bibliographical note

Keywords

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