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Detection of Automobile Accidents Through Satellite Navigation System

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Artificial Intelligence and Machine Learning in Satellite Data Processing and Services

Abstract

One of the most serious issues that foreign travellers face is traffic congestion. The proliferation of automobiles and a dense population are two major reasons for visitor risk. Reducing visitor dangers is a difficult task, as street injuries account for the bulk of deaths worldwide. Furthermore, many deaths have occurred because of a loss of communication following an accident, even while the victims were still alive. As a result, there is a desire to limit the number of individuals killed or injured on the street. Removing the communication barrier after a crash, particularly while the victims are unconscious, is one strategy to reduce deaths. However, there are numerous options. Main purpose of this tool is to detect car accidents. It is carried out by using a vibration sensor to detect a crash, after which the microcontroller/CPU system receives location data from the GPS and sends it to the GSM, where the system reports on the accident situation on a regular basis. GSM communication platform uses SMS format to send accurate location co-ordinates from GPS to nearby rescue groups such as police departments, hospitals, fire stations, and a few private cell phones. This will allow for quick action to save many people’s lives. In this way, we may break down communication barriers and provide regular contact using Wi-Fi telecom services. This data is likewise stored in a cloud namely ThingSpeak and intimated through satellite.

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Correspondence to Shakti Raj Chopra .

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Sowri, V.O.D., Chandra, B.E., MoniSwahith, K., Sarvani, P.V.S.M., Chopra, S.R. (2023). Detection of Automobile Accidents Through Satellite Navigation System. In: Kumar, S., Setia, R., Singh, K. (eds) Artificial Intelligence and Machine Learning in Satellite Data Processing and Services. Lecture Notes in Electrical Engineering, vol 970. Springer, Singapore. https://doi.org/10.1007/978-981-19-7698-8_4

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  • DOI: https://doi.org/10.1007/978-981-19-7698-8_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-7697-1

  • Online ISBN: 978-981-19-7698-8

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