Real Time Crowd Counting System Using Machine Learning
Crowd counting is a critical task in public safety, event management, and urban planning. This paper presents a real-time crowd counting system leveraging machine learning to accurately estimate the number of people in a given scene. The proposed system employs a convolutional neural network (CNN)-b...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English English |
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INTI International University
2025
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2142/ http://eprints.intimal.edu.my/2142/1/jods2025_03.pdf http://eprints.intimal.edu.my/2142/2/685 |
| _version_ | 1848766931685867520 |
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| author | K., Helini B., Niharika B., Tejaswini D., Shriya K., Anjali |
| author_facet | K., Helini B., Niharika B., Tejaswini D., Shriya K., Anjali |
| author_sort | K., Helini |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | Crowd counting is a critical task in public safety, event management, and urban planning. This paper presents a real-time crowd counting system leveraging machine learning to accurately estimate the number of people in a given scene. The proposed system employs a convolutional neural network (CNN)-based deep learning model, optimized for processing images and video streams to identify and count individuals in diverse environments. Key features of the system include real-time inference, robust performance in varying lighting and density conditions, and adaptability to different camera perspectives. The model is trained on a diverse dataset, encompassing crowded events, open spaces, and public gatherings, ensuring its versatility and reliability. Post-training, the system is deployed using lightweight architectures, allowing seamless integration with edge devices and IoT platforms. |
| first_indexed | 2025-11-14T11:58:59Z |
| format | Article |
| id | intimal-2142 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:58:59Z |
| publishDate | 2025 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-21422025-06-19T09:18:55Z http://eprints.intimal.edu.my/2142/ Real Time Crowd Counting System Using Machine Learning K., Helini B., Niharika B., Tejaswini D., Shriya K., Anjali QA75 Electronic computers. Computer science T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Crowd counting is a critical task in public safety, event management, and urban planning. This paper presents a real-time crowd counting system leveraging machine learning to accurately estimate the number of people in a given scene. The proposed system employs a convolutional neural network (CNN)-based deep learning model, optimized for processing images and video streams to identify and count individuals in diverse environments. Key features of the system include real-time inference, robust performance in varying lighting and density conditions, and adaptability to different camera perspectives. The model is trained on a diverse dataset, encompassing crowded events, open spaces, and public gatherings, ensuring its versatility and reliability. Post-training, the system is deployed using lightweight architectures, allowing seamless integration with edge devices and IoT platforms. INTI International University 2025-06 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2142/1/jods2025_03.pdf text en cc_by_4 http://eprints.intimal.edu.my/2142/2/685 K., Helini and B., Niharika and B., Tejaswini and D., Shriya and K., Anjali (2025) Real Time Crowd Counting System Using Machine Learning. Journal of Data Science, 2025 (03). pp. 1-10. ISSN 2805-5160 http://ipublishing.intimal.edu.my/jods.html |
| spellingShingle | QA75 Electronic computers. Computer science T Technology (General) TK Electrical engineering. Electronics Nuclear engineering K., Helini B., Niharika B., Tejaswini D., Shriya K., Anjali Real Time Crowd Counting System Using Machine Learning |
| title | Real Time Crowd Counting System Using Machine Learning |
| title_full | Real Time Crowd Counting System Using Machine Learning |
| title_fullStr | Real Time Crowd Counting System Using Machine Learning |
| title_full_unstemmed | Real Time Crowd Counting System Using Machine Learning |
| title_short | Real Time Crowd Counting System Using Machine Learning |
| title_sort | real time crowd counting system using machine learning |
| topic | QA75 Electronic computers. Computer science T Technology (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.intimal.edu.my/2142/ http://eprints.intimal.edu.my/2142/ http://eprints.intimal.edu.my/2142/1/jods2025_03.pdf http://eprints.intimal.edu.my/2142/2/685 |