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Published Date: 03-04-2025

IoT Enabled Innovative Accident Detection and Rescue System

This project describes a new accident and rescue system created by the Internet of things (IOT), which aims to improve road safety and improve emergency response times by adopting real-time data and connections.

Key features

  • Real - Time Monitoring: The system uses loT sensors driven into vehicles to monitor constantly driving conditions and immediately detect accidents.

  • Automatic Warning: After discovering an accident, the system automatically sends out alarms for emergency services, providing accurate information on the location and severity of accidents.

  • Analytic Data: The collected data is analysed to identify accidental areas, allowing authorities to implement preventive measures.

  • User Interface: A mobile application allows users to pursue their car status, receive alarms and communicate with emergency services.

  • Integration in Wise Cities: The system could be integrated with the city's wise infrastructure, allowing for coordinated reactions and distribution of resources during emergencies.

  • habitable technology: Integration with useful equipment can provide additional health monitoring for drivers and passengers, providing timely medical assistance.

  • Community Engagement: The system encourages community involvement by allowing users to report accidents and share information, promoting a safer driving environment.

This loT - equipped system represents an important progress in the discovery of accidents and rescue, ultimately aiming to save lives and reduce the impact of road accidents.


We have more details like Algorithm Information, Condition Checks, Technology, Industry & Human Benefits:


1. Title Page

  • Title Sources

2. Abstract

  • Summary of the Project
  • Key Findings
  • Keywords

3. Introduction

  • Background
  • Problem Statement
  • Research Questions
  • Objectives

4. Literature Review

  • Theoretical Framework
  • Review of Related Studies
  • Gaps in the Literature

5. Project Methodology

  • Research Design
  • Data Collection Methods
  • Data Analysis Techniques
  • Ethical Considerations

6. Project Results

  • Data Presentation
  • Statistical Analysis
  • Key Findings

7. Discussion

  • Interpretation of Results
  • Implications of Findings
  • Limitations

8. project Conclusion

  • Summary of Findings
  • Recommendations
  • Future Research Directions

9. References

  • References and Resources Links

10. Appendices

  • Final Source Code
  • Survey
  • Live environment/Real world Data Sets 
  • Additional Figures and Tables


The final table of contents depends on the project selection.


Project Delivery Kit


Project Source Code

Installation Guide

Data Sets and Samples

Usage Terms

Deployment Guide & More

Frequetly Asked Questions






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