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Title Real-time Internet of LoRa Things (IoLT)-based accident detection and prevention system in vehicular networks towards smart city
ID_Doc 40070
Authors Vinodhini, M; Rajkumar, S; Subramaniam, SK
Title Real-time Internet of LoRa Things (IoLT)-based accident detection and prevention system in vehicular networks towards smart city
Year 2023
Published
Abstract Vehicle utilization has increased on a broader scale in today's reality. Because of insufficient emergency services, increased motor traffic has resulted in the rise of traffic collisions, and widespread accidents lead to the demise of lives and property. Generally, the consequence death rate happens each year, originating from delays in rescue activities. However, vehicles are embedded with trend technology. Still, the accident count will rise day by day due to delays in transmitting the information to the concerned person or delays in rescue activities. The proposed work offers an effective solution to the aforementioned issue by assisting low-power and long-range (LoRa) architecture with edge node ultrasonic sensors for identifying the abnormalities and to provide an efficient transport ambulance from the unexpected mishap spot to the closest hospital where emergency well-being can be provided with the help of cloud technology. Also, emergency information can be sent to the cloud immediately, and its response is the way of alerting the surroundings and notifying the appropriate hospital with the aid of a GPS-enabled LoRa-shield. Further, comparing the proposed technology with other LPWAN (low-power wide area networks) in terms of coverage, cost, capacity, and energy consumption proves efficient communication in the development of intelligent vehicular networks towards a smart city. Using an efficient Internet of LoRa platform, an accelerometer sensor, a vehicle's sensor collects appropriate accident-related data. We suggest that the hospital depends on injury level, and it leads the rescue system. If abnormalities are sensed, the controller gives an emergency alert to reduce the response time in an emergency situation. LoRa has 128 bits of AES encryption keys to secure the sensor information between edge nodes and the LoRa server.image
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