2022 · 32 citations · 20 references
ComputingComputer ScienceArtificial IntelligenceInternet Of ThingsMachine LearningIntelligent Transportation SystemsIot Data AcquisitionPattern RecognitionRoad SafetySmart SensorsTraffic SafetyDriver Monitoring SystemsMachine Learning For IotRadio-frequency IdentificationRadio-frequency Identification TagsReal-time ProcessingRoad Hazard DetectionRoad Safety EngineeringTraffic Accident Detection
This paper explores the advancement of the Internet of Things (IoT) and Machine Learning in the field of Road Safety and accident prevention with a state-of-the-art review of various techniques adopted for implementing an intelligent road Safety System. In this review, emphasis is given on the behavior of drivers, the condition of vehicles (two-wheelers, four-wheelers), health condition of roads and bridges, and theft-related issues using Radio Frequency Identification (RFID). It is seen that, with the help of IoT, the safety system can be updated on a real-time basis which can help to create a smart, intelligent, and highly efficient Road Safety system. Artificial Intelligence (AI) is applied to enhance the technology further for detecting the driver's behavior like drowsiness with the help of real-time camera feed or high-resolution images. Additionally, the role of AI in detecting the condition of roads and bridges in preventing road accidents is also discussed. Though the paper provides a good insight into the application of IoT and Machine Learning in the smart Road safety system, certain limitations are highlighted.
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Deep CNN models-based ensemble approach to driver drowsiness detection
Mohit Dua, Shakshi, Ritu Singla et al. · Neural Computing and Applications · 2020 · 206 citations