Traffic intensity monitoring using multiple object detection with traffic surveillance cameras
Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Tr...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
IEEE
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/60067/ http://irep.iium.edu.my/60067/20/60067%20Traffic%20intensity%20monitoring%20using%20multiple%20object.pdf |
| _version_ | 1848785426721013760 |
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| author | Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Emran, Shamsan |
| author_facet | Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Emran, Shamsan |
| author_sort | Hasan Gani, Muhammad Hamdan |
| building | IIUM Repository |
| collection | Online Access |
| description | Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded. |
| first_indexed | 2025-11-14T16:52:57Z |
| format | Proceeding Paper |
| id | iium-60067 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T16:52:57Z |
| publishDate | 2017 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-600672018-07-10T09:28:48Z http://irep.iium.edu.my/60067/ Traffic intensity monitoring using multiple object detection with traffic surveillance cameras Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Emran, Shamsan TK Electrical engineering. Electronics Nuclear engineering Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded. IEEE 2017-11-28 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/60067/20/60067%20Traffic%20intensity%20monitoring%20using%20multiple%20object.pdf Hasan Gani, Muhammad Hamdan and Khalifa, Othman Omran and Gunawan, Teddy Surya and Emran, Shamsan (2017) Traffic intensity monitoring using multiple object detection with traffic surveillance cameras. In: 2017 IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA 2017), 27th-29th Nov. 2017, Putrajaya. http://icsima.ieeemy-ims.org/17/ |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Hasan Gani, Muhammad Hamdan Khalifa, Othman Omran Gunawan, Teddy Surya Emran, Shamsan Traffic intensity monitoring using multiple object detection with traffic surveillance cameras |
| title | Traffic intensity monitoring using multiple object detection with traffic surveillance cameras |
| title_full | Traffic intensity monitoring using multiple object detection with traffic surveillance cameras |
| title_fullStr | Traffic intensity monitoring using multiple object detection with traffic surveillance cameras |
| title_full_unstemmed | Traffic intensity monitoring using multiple object detection with traffic surveillance cameras |
| title_short | Traffic intensity monitoring using multiple object detection with traffic surveillance cameras |
| title_sort | traffic intensity monitoring using multiple object detection with traffic surveillance cameras |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://irep.iium.edu.my/60067/ http://irep.iium.edu.my/60067/ http://irep.iium.edu.my/60067/20/60067%20Traffic%20intensity%20monitoring%20using%20multiple%20object.pdf |