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Smart city article details
| Title | Design And Development Of An Intelligent Number Plate Identification System Utilizing Raspberry Pi Technology |
|---|---|
| ID_Doc | 18469 |
| Authors | Kumar M.; Pilania U.; Mittal V. |
| Year | 2023 |
| Published | International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings |
| DOI | http://dx.doi.org/10.1109/ICSSAS57918.2023.10331874 |
| Abstract | In many parts of the world, traffic law violations are a significant contributor to road accidents, particularly in developing countries. Despite the existence of rules and regulations to prevent such violations, the number of violators continues to rise due to inadequate enforcement by authorities in these regions. To enhance road safety and reduce accidents, a system must be developed to aid law enforcement agencies in enforcing these rules. The primary objective of this article is to use image processing to detect traffic violators by their number plates. The system comprises an IR sensor for detecting vehicles, which is connected to a microprocessor that records the time taken for the sensor to detect an object. When the time taken is below the minimum threshold, the camera captures the plate number, and the image is stored on a Raspberry Pi 4 for processing. OpenALPR dataset is selected for the proposed work. The Raspberry Pi 4 extracts the numbers from the image. Accuracy, time complexity, and cost are calculated for the proposed work to measure its performance. It is also compared with some states of artwork for its validation. Implementation of the proposed system can enhance road safety and traffic control in developing smart cities. Top of Form © 2023 IEEE. |
| Author Keywords | Accuracy; Cost Complexity; Image Processing; Number Plate Detection; Raspberry Pi 4; Time Complexity |
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