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Human presence detection system

This paper presents the development and evaluation of an IoT-based human presence detection system leveraging microwave sensors. Traditional methods of monitoring human activity in buildings are often slow, inefficient, and costly. To address these challenges, this project aimed to create a cost-eff...

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Bibliographic Details
Main Author:	Tai, Xi Yang
Format:	Final Year Project / Dissertation / Thesis
Published:	2024
Subjects:	HB Economic Theory T Technology (General) TD Environmental technology. Sanitary engineering
Online Access:	http://eprints.utar.edu.my/6525/1/fyp_IB_2024_TXY.pdf http://eprints.utar.edu.my/6525/
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id	my-utar-eprints.6525
record_format	eprints
spelling	my-utar-eprints.65252024-10-23T05:28:14Z Human presence detection system Tai, Xi Yang HB Economic Theory T Technology (General) TD Environmental technology. Sanitary engineering This paper presents the development and evaluation of an IoT-based human presence detection system leveraging microwave sensors. Traditional methods of monitoring human activity in buildings are often slow, inefficient, and costly. To address these challenges, this project aimed to create a cost-effective solution that offers real-time updates on human presence while addressing privacy concerns. The system architecture includes microwave sensors for improved accuracy and reliability, ESP32 microcontrollers for data processing, and cloud-based platforms such as AWS IoT Core, Timestream, and Grafana for data storage and visualization. Through meticulous design and integration, the system provides real-time detection of human presence. Moreover, the project delves into the critical aspect of determining optimal delay intervals for sensor status checks. Rigorous testing and experimentation were conducted to establish the most effective delay interval, ensuring reliable detection while minimizing false alarms. Additionally, the development of an automated calculation algorithm streamlines the testing process and enhances data collection efficiency. Challenges encountered during the project include addressing sensor faults, environmental interference, and optimizing hardware and software components also have been discussed. Overall, the project contributes valuable insights into the development of IoT-based human presence detection systems, paving the way for applications in occupancy monitoring and resource optimization. 2024-01 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/6525/1/fyp_IB_2024_TXY.pdf Tai, Xi Yang (2024) Human presence detection system. Final Year Project, UTAR. http://eprints.utar.edu.my/6525/
institution	Universiti Tunku Abdul Rahman
building	UTAR Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tunku Abdul Rahman
content_source	UTAR Institutional Repository
url_provider	http://eprints.utar.edu.my
topic	HB Economic Theory T Technology (General) TD Environmental technology. Sanitary engineering
spellingShingle	HB Economic Theory T Technology (General) TD Environmental technology. Sanitary engineering Tai, Xi Yang Human presence detection system
description	This paper presents the development and evaluation of an IoT-based human presence detection system leveraging microwave sensors. Traditional methods of monitoring human activity in buildings are often slow, inefficient, and costly. To address these challenges, this project aimed to create a cost-effective solution that offers real-time updates on human presence while addressing privacy concerns. The system architecture includes microwave sensors for improved accuracy and reliability, ESP32 microcontrollers for data processing, and cloud-based platforms such as AWS IoT Core, Timestream, and Grafana for data storage and visualization. Through meticulous design and integration, the system provides real-time detection of human presence. Moreover, the project delves into the critical aspect of determining optimal delay intervals for sensor status checks. Rigorous testing and experimentation were conducted to establish the most effective delay interval, ensuring reliable detection while minimizing false alarms. Additionally, the development of an automated calculation algorithm streamlines the testing process and enhances data collection efficiency. Challenges encountered during the project include addressing sensor faults, environmental interference, and optimizing hardware and software components also have been discussed. Overall, the project contributes valuable insights into the development of IoT-based human presence detection systems, paving the way for applications in occupancy monitoring and resource optimization.
format	Final Year Project / Dissertation / Thesis
author	Tai, Xi Yang
author_facet	Tai, Xi Yang
author_sort	Tai, Xi Yang
title	Human presence detection system
title_short	Human presence detection system
title_full	Human presence detection system
title_fullStr	Human presence detection system
title_full_unstemmed	Human presence detection system
title_sort	human presence detection system
publishDate	2024
url	http://eprints.utar.edu.my/6525/1/fyp_IB_2024_TXY.pdf http://eprints.utar.edu.my/6525/
_version_	1814061969518362624
score	13.211869

Human presence detection system

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