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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/2405.00678 |
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| _version_ | 1866917655328325632 |
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| author | Poza-Lujan, Jose-Luis Uribe-Chavert, Pedro Posadas-Yagüe, Juan-Luis |
| author_facet | Poza-Lujan, Jose-Luis Uribe-Chavert, Pedro Posadas-Yagüe, Juan-Luis |
| contents | Detecting and characterising vehicles is one of the purposes of embedded systems used in intelligent environments. An analysis of a vehicle characteristics can reveal inappropriate or dangerous behaviour. This detection makes it possible to sanction or notify emergency services to take early and practical actions. Vehicle detection and characterisation systems employ complex sensors such as video cameras, especially in urban environments. These sensors provide high precision and performance, although the price and computational requirements are proportional to their accuracy. These sensors offer high accuracy, but the price and computational requirements are directly proportional to their performance. This article introduces a system based on modular devices that is economical and has a low computational cost. These devices use ultrasonic sensors to detect the speed and length of vehicles. The measurement accuracy is improved through the collaboration of the device modules. The experiments were performed using multiple modules oriented to different angles. This module is coupled with another specifically designed to detect distance using previous modules speed and length data. The collaboration between different modules reduces the speed relative error ranges from 1 to 5, depending on the angle configuration used in the modules. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_00678 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Low-cost modular devices for on-road vehicle detection and characterisation Poza-Lujan, Jose-Luis Uribe-Chavert, Pedro Posadas-Yagüe, Juan-Luis Signal Processing Machine Learning Detecting and characterising vehicles is one of the purposes of embedded systems used in intelligent environments. An analysis of a vehicle characteristics can reveal inappropriate or dangerous behaviour. This detection makes it possible to sanction or notify emergency services to take early and practical actions. Vehicle detection and characterisation systems employ complex sensors such as video cameras, especially in urban environments. These sensors provide high precision and performance, although the price and computational requirements are proportional to their accuracy. These sensors offer high accuracy, but the price and computational requirements are directly proportional to their performance. This article introduces a system based on modular devices that is economical and has a low computational cost. These devices use ultrasonic sensors to detect the speed and length of vehicles. The measurement accuracy is improved through the collaboration of the device modules. The experiments were performed using multiple modules oriented to different angles. This module is coupled with another specifically designed to detect distance using previous modules speed and length data. The collaboration between different modules reduces the speed relative error ranges from 1 to 5, depending on the angle configuration used in the modules. |
| title | Low-cost modular devices for on-road vehicle detection and characterisation |
| topic | Signal Processing Machine Learning |
| url | https://arxiv.org/abs/2405.00678 |