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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.16012 |
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| _version_ | 1866909357706313728 |
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| author | Kumar, Abhijeet Singh, Unnati Chatterjee, Rajdeep Bandyopadhyay, Tathagata |
| author_facet | Kumar, Abhijeet Singh, Unnati Chatterjee, Rajdeep Bandyopadhyay, Tathagata |
| contents | An efficient system of a queue control and regulation in public spaces is very important in order to avoid the traffic jams and to improve the customer satisfaction. This article offers a detailed road map based on a merger of intelligent systems and creating an efficient systems of queues in public places. Through the utilization of different technologies i.e. computer vision, machine learning algorithms, deep learning our system provide accurate information about the place is crowded or not and the necessary efforts to be taken. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_16012 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Massimo: Public Queue Monitoring and Management using Mass-Spring Model Kumar, Abhijeet Singh, Unnati Chatterjee, Rajdeep Bandyopadhyay, Tathagata Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Applications An efficient system of a queue control and regulation in public spaces is very important in order to avoid the traffic jams and to improve the customer satisfaction. This article offers a detailed road map based on a merger of intelligent systems and creating an efficient systems of queues in public places. Through the utilization of different technologies i.e. computer vision, machine learning algorithms, deep learning our system provide accurate information about the place is crowded or not and the necessary efforts to be taken. |
| title | Massimo: Public Queue Monitoring and Management using Mass-Spring Model |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Applications |
| url | https://arxiv.org/abs/2410.16012 |