Traffic Management Through Image Processing and Fuzzy Logic

Joy, Joel Joseph; Bhat, Manali; Verma, Namrata; Jani, Milind

doi:10.1109/iccons.2018.8662968

Cited by 5 publications

(2 citation statements)

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“…Input video diambil dan logika fuzzy diterapkan untuk menangani konsep kebenaran parsial. Hasil dari konsep kebenaran parsial dapat berkisar antara benar-benar benar dan sepenuhnya salah (Joy et al, 2018).…”

Section: Meskipununclassified

Deteksi Suhu Tubuh Dan Masker Wajah Dengan Mlx90614, Opencv, Keras/Tensorflow, Dan Deep Learning

Malik¹

2021

JEEMM

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<p><em>Digital image processing technology combined with sensors is currently being used. This technology can help various needs such as education, industry and health. During the COVID-19 crisis, people are required to wear masks for protection. The public is also required to check their temperature regularly, which will have a significant health impact. This can reduce the risk of transmitting the Covid-19 virus. In this study, the author uses a WebCam camera and a temperature sensor MLX90614 as a tool to monitor the use of masks and measure body temperature. The author uses OpenCV for digital image processing and Tensorflow as a deep learning method for mask detection. The result of this study is that Tensorflow can detect wearing a mask with 99% accuracy. The MLX90614 sensor can measure body temperature with 99% accuracy at a reading distance of 5 cm to 10 cm.</em></p>

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Section: Meskipununclassified

Deteksi Suhu Tubuh Dan Masker Wajah Dengan Mlx90614, Opencv, Keras/Tensorflow, Dan Deep Learning

Malik¹

2021

JEEMM

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“…The study [3] integrates fuzzy logic with image processing to propose a novel traffic management strategy. The system intends to improve traffic control and surveillance capabilities by utilizing currently installed closedcircuit television (CCTV) cameras.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Traffic Safety With Artificial Intelligence Using Helmet Detection and Zebra Crossing Obstruction

2023

IRJMETS

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The application of artificial intelligence (AI) in improving traffic safety is highlighted in this abstract through two key features: helmet identification and zebra crossing obstruction prevention. The application of AI technology in various fields proves its capacity to reduce traffic accidents and protect pedestrians. To encourage adherence to safety standards, the first component uses computer vision techniques to identify helmet use among scooter and motorcycle riders. To ensure safe pedestrian passage, the second part focuses on using AI-driven systems to detect and prevent obstructions on zebra crossings. This study helps to reduce total traffic accidents and improves the safety of both drivers and pedestrians by addressing helmet compliance and zebra crossing safety.

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