Abstract
Abstract: Road accidents are increasing daily as the number of automobiles rises. An annual global death toll of 1.4 million and an injury toll of 50 million are reported by the World Health Organization (WHO). The absence of medical assistance at the scene of the accident or the lengthy response time during the rescue effort are the main causes of mortality. We can reduce delays in a rescue operation that has the potential to save many lives by using a cognitive agent-based collision detection and smart accident alarm and rescue system. To gather and send accident-related data to the cloud or server, the suggested system consists of a force sensor, GPS module, alarm controller, ESP8266 controller, camera, Raspberry Pi, and GSM module. The accident is then verified using cloud- based techniques for deep learning. accident is then verified using cloud-based techniques for deep learning. When the deep learning module notices an accident, it immediately alerts all nearby emergency services, including the hospital, police station, mechanics, etc.
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