IoT-Based Emergency SOS System for Post-Accident Assistance

Year : 2025 | Volume : 12 | Issue : 02 | Page : 11 19
    By

    Swarup Adsul,

  • Omkar Salekar,

  • Sahil Waghmare,

  1. Student, Department of Computer Engineering, Shree Chhatrapati Shivajiraje College of Engineering, Pune, Maharashtra, India
  2. Student, Department of Computer Engineering, Shree Chhatrapati Shivajiraje College of Engineering, Pune, Maharashtra, India
  3. Student, Department of Computer Engineering, Shree Chhatrapati Shivajiraje College of Engineering, Pune, Maharashtra, India

Abstract

The increase in road accidents poses significant challenges for timely medical response, often leading to life-threatening delays. This project proposes an IoT-based accident wound detection system that utilizes a night vision camera mounted on either the interior or exterior of a vehicle. The system aims to detect injuries sustained by individuals during a collision and promptly alert emergency services. By employing a night vision camera, the system can operate effectively in low-light or nighttime conditions, ensuring round-the-clock functionality. When an accident occurs, the camera captures real-time images and videos of the vehicle’s surroundings or interior. These images are analyzed by an onboard processing unit that references a wound dataset specifically curated for detecting human injuries. The dataset contains various wound types, including cuts, bruises, and severe trauma, enabling the system to identify and classify the severity of injuries accurately. This detection process leverages machine learning algorithms trained on the wound dataset, ensuring reliable wound recognition. Upon detecting an injury, the system automatically initiates an emergency protocol, which includes either calling or sending an SMS to nearby medical services, police, or predesignated emergency contacts. This automated alert system reduces the response time by providing critical information to emergency responders, including accident location and potential injury details. The proposed system offers a proactive approach to accident response, minimizing human intervention and enhancing post-accident care. This innovative solution addresses the urgent need for faster medical assistance, potentially saving lives by bridging the gap between accident occurrence and emergency response.

Keywords: GSM, raspberry Pi, text to speech module, Crash detection sensor, night vision Camera module, GPS, CNN algorithm

[This article belongs to Journal of Microelectronics and Solid State Devices ]

How to cite this article:
Swarup Adsul, Omkar Salekar, Sahil Waghmare. IoT-Based Emergency SOS System for Post-Accident Assistance. Journal of Microelectronics and Solid State Devices. 2025; 12(02):11-19.
How to cite this URL:
Swarup Adsul, Omkar Salekar, Sahil Waghmare. IoT-Based Emergency SOS System for Post-Accident Assistance. Journal of Microelectronics and Solid State Devices. 2025; 12(02):11-19. Available from: https://journals.stmjournals.com/jomsd/article=2025/view=215168


References

  1. Abubakar A, Ugail H, Smith KM, Bukar AM, Elmahmudi A. Burns depth assessment using deep learning features. J Med Biol Eng. 2020 Dec; 40: 923–33.
  2.  Alzubaidi L, Zhang J, Humaidi AJ, Al-Dujaili A, Duan Y, Al-Shamma O, Santamaría J, Fadhel MA, Al-Amidie M, Farhan L. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. J Big Data. 2021 Dec; 8(1): 53.
  3.  Saikhu A, Hariadi V, Rochmah L. Mobile application for scheduling of medical staff in emergency condition using integer programming. In 2015 IEEE International Conference on Information & Communication Technology and Systems (ICTS). 2015 Sep 16; 215–218.
  4.  Fabito BS, Balahadia FF, Cabatlao JD. AppLERT: A mobile application for incident and disaster notification for Metro Manila. In 2016 IEEE Region 10 Symposium (TENSYMP). 2016 May 9; 288–292.
  5.  Masum SK. SMS/GPS Vehicle Tracking System. Doctoral dissertation. England: University of Portsmouth; 2013.
  6.  Al_Issa HA, Thuneibat S, Abdesalam M. Sensors application using PIC16F877A microcontroller. American Journal of Remote Sensing (AJRS). 2016; 4(3): 13–8.
  7.  Dafallah HA. Design and implementation of an accurate real time GPS tracking system. In The Third IEEE International Conference on e-Technologies and Networks for Development (ICeND2014). 2014 Apr 29; 183–188.
  8. L Lucas Y, Niri R, Treuillet S, Douzi H, Castaneda B. Wound size imaging: ready for smart assessment and monitoring. Adv Wound Care. 2021 Nov 1; 10(11): 641–61.
  9.  Nichols EL. Wound assessment part 1: how to measure a wound. Wound Essentials. 2015; 10(2): 51–5.
  10.  Gethin G. The importance of continuous wound measuring. Wounds UK. 2006 Jun; 2(2): 60–68.
  11.  Sheehan P, Jones P, Caselli A, Giurini JM, Veves A. Percent change in wound area of diabetic foot ulcers over a 4-week period is a robust predictor of complete healing in a 12-week prospective trial. Diabetes care. 2003 Jun 1; 26(6): 1879–82.
Regular Issue Subscription Review Article
Volume 12
Issue 02
Received 14/04/2025
Accepted 07/05/2025
Published 26/05/2025
Publication Time 42 Days
234

Login


My IP

PlumX Metrics