Development of Automated People Counting System using Object Detection and Tracking
The emergence of automation in the current economic trend promotes the usage of computer vision systems in various applications. Counting people in a specified area or on the street can bring many benefits in terms of security and marketing. The people counting system is one of the applications tha...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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iJOE
2023
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| Online Access: | http://eprints.uthm.edu.my/9568/ http://eprints.uthm.edu.my/9568/1/J16079_69a63a90b5cf03171b79b55bb5804973.pdf |
| _version_ | 1848889715700269056 |
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| author | Chee Jia Hong, Chee Jia Hong Mazlan, Muhammad Hazli |
| author_facet | Chee Jia Hong, Chee Jia Hong Mazlan, Muhammad Hazli |
| author_sort | Chee Jia Hong, Chee Jia Hong |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | The emergence of automation in the current economic trend
promotes the usage of computer vision systems in various applications. Counting people in a specified area or on the street can bring many benefits in terms of security and marketing. The people counting system is one of the applications that utilize the computer vision system to count people with higher reliability and accuracy. Thus, this project is to develop an offline automated people counting
system based on captured video file input using MATLAB software and a notification system to update and send notifications about the number of occupants in a target area using ThingSpeak. For project development, simulation and
development of coding for object detection that involves deep learning approach, object tracking and counting, and development of notification system have been done. Three videos were taken to be used for three trials to evaluate the functionality and performance of the developed system. Based on the results and analysis, the system can perform people detection, people tracking and people counting on
the recorded input videos with high accuracy of 94.45%, visualize the data on the ThingSpeak platform and send notifications through Twitter. |
| first_indexed | 2025-11-15T20:30:35Z |
| format | Article |
| id | uthm-9568 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:30:35Z |
| publishDate | 2023 |
| publisher | iJOE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-95682023-08-02T03:50:59Z http://eprints.uthm.edu.my/9568/ Development of Automated People Counting System using Object Detection and Tracking Chee Jia Hong, Chee Jia Hong Mazlan, Muhammad Hazli T Technology (General) The emergence of automation in the current economic trend promotes the usage of computer vision systems in various applications. Counting people in a specified area or on the street can bring many benefits in terms of security and marketing. The people counting system is one of the applications that utilize the computer vision system to count people with higher reliability and accuracy. Thus, this project is to develop an offline automated people counting system based on captured video file input using MATLAB software and a notification system to update and send notifications about the number of occupants in a target area using ThingSpeak. For project development, simulation and development of coding for object detection that involves deep learning approach, object tracking and counting, and development of notification system have been done. Three videos were taken to be used for three trials to evaluate the functionality and performance of the developed system. Based on the results and analysis, the system can perform people detection, people tracking and people counting on the recorded input videos with high accuracy of 94.45%, visualize the data on the ThingSpeak platform and send notifications through Twitter. iJOE 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/9568/1/J16079_69a63a90b5cf03171b79b55bb5804973.pdf Chee Jia Hong, Chee Jia Hong and Mazlan, Muhammad Hazli (2023) Development of Automated People Counting System using Object Detection and Tracking. -, 19 (6). pp. 18-30. https://doi.org/10.1016/j.procs.2015.08.064 |
| spellingShingle | T Technology (General) Chee Jia Hong, Chee Jia Hong Mazlan, Muhammad Hazli Development of Automated People Counting System using Object Detection and Tracking |
| title | Development of Automated People Counting System
using Object Detection and Tracking |
| title_full | Development of Automated People Counting System
using Object Detection and Tracking |
| title_fullStr | Development of Automated People Counting System
using Object Detection and Tracking |
| title_full_unstemmed | Development of Automated People Counting System
using Object Detection and Tracking |
| title_short | Development of Automated People Counting System
using Object Detection and Tracking |
| title_sort | development of automated people counting system
using object detection and tracking |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/9568/ http://eprints.uthm.edu.my/9568/ http://eprints.uthm.edu.my/9568/1/J16079_69a63a90b5cf03171b79b55bb5804973.pdf |