Research Article Open Access

Smart Ambulances for IoT Based Accident Detection, Tracking and Response

Amreen Ayesha1 and Komalavalli Chakravarthi1
  • 1 Department of Computer Science and Engineering, Presidency University, Bangalore, India


One of the main reasons for death among young people in the current era is based on road accidents. The goal of current research on accident detection systems is to shorten reporting times, increase accident detection accuracy and address them through our modern technology. Our primary goal is to recommend a system that can successfully aid in preventing any kind of accident and if such conditions exist, then how it detects and alerts the relevant authorities and people so that the problem can be handled and addressed swiftly. Automatic mechanisms for detecting traffic accidents must be put in place if assistance is to be given right away. The proposed system model Emergency Request Response and Management System (ERMS) takes the benefit of Vibration sensors (VC) and Accelerometers (AB) through the proposed phases namely AcciDet TracSys and AcciAddr TracSys. Wherein, the AcciDet TracSys helps in detection of the accident, explained in detail in this study and AcciAddr TracSys helps address the people met with an accident through technical ways that are explained in detail in this study, also tracing the location of smart ambulances. With the help of the global positioning system, the accident location is sent to the smart ambulance for timely arrival and is also tracked for further assistance through the internet. Finally, this information is communicated to the main contacts of the accident victim, so that they can reach the hospital on time. Our proposed work meets the need to assist the injured after an accident through the accident detection and addressing system, as just only notifying neighboring ambulances does not cater to the solution to the problem.

Journal of Computer Science
Volume 19 No. 6, 2023, 677-685


Submitted On: 10 February 2023 Published On: 12 May 2023

How to Cite: Ayesha, A. & Chakravarthi, K. (2023). Smart Ambulances for IoT Based Accident Detection, Tracking and Response. Journal of Computer Science, 19(6), 677-685.

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  • GSM
  • GPS
  • Accident Detection
  • IoT
  • Accelerometer
  • Smart Car
  • Smart Ambulance