IRO Journals
Journal of Artificial Intelligence and Capsule Networks

Smart Tourist Safety and Emergency Response System Using Rule-Based Risk Detection

Open Access
Published: 15 May, 2026
Pages: 135-146
  • Sowmiya M.N. , Sowmiya M.N.
    Department of Information Technology, Velammal Engineering College, Chennai, India
    Department of Information Technology, Velammal Engineering College, Chennai, India
  • Sureshkumar R. , Sureshkumar R.
    Department of Information Technology, Velammal Engineering College, Chennai, India
    Department of Information Technology, Velammal Engineering College, Chennai, India
  • Mukesh E. Mukesh E.
    Department of Information Technology, Velammal Engineering College, Chennai, India
    Department of Information Technology, Velammal Engineering College, Chennai, India
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How to Cite

M.N., Sowmiya, Sureshkumar R., and Mukesh E. 2026. “Smart Tourist Safety and Emergency Response System Using Rule-Based Risk Detection”. Journal of Artificial Intelligence and Capsule Networks 8 (2): 135-46. https://doi.org/10.36548/jaicn.2026.2.005.
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Keywords

Artificial Intelligence (AI)
Tourist Safety
Emergency Response
Risk Intelligence
GPS Tracking
Smart City Safety

Abstract

In this research paper, the increasing traveler safety issues due to the growth of tourism have been analyzed, and limitations in current safety systems used to detect traveler risks have been highlighted. For addressing these traveler safety issues, this research proposes Rule-Based Smart Tourist Safety and Emergency Response System, which will ensure monitoring of user safety through real-time data. This system estimates a risk score dynamically depending on multiple parameters like time spent on travel, distance from risk areas, nearby emergency cases, and user's movement pattern from their GPS data. According to the calculated risk score, there is a risk classification module based on rules which categorize the risk scores into Low, Medium, and High levels. In case of any emergency situations, the system can rapidly send the user's location, time stamp of incident along with any visual information related to the situation to a centralized monitoring system. There is also an Incident Visualization Module in the proposed system that ensures proactive decisions by identifying potential hazardous locations in real time. Experimental results indicate a successful detection rate of 90%-92% in negligible time intervals.

References

  1. Sonawane, G. V., Gaidhani, A., & Patil, V. Smart Tourist Safety Monitoring and Incident Response System. International Journal for Research in Applied Science & Engineering Technology 2026, vol.14, issue 5. 1492-1497.
  2. Brindha S, Subhashini N, Nikil Vardhan V "AI-Powered Smart Tourist Safety System with Geo-Fencing and Blockchain Identity," International Journal of Scientific Research in Engineering and Management 2026, vol. 10, no. 1.
  3. RK, Shanmugha Priya, V. P. Anushya, Kamalapadu Varsha, Santhosh Krishna BV, C. M. Harshith, and L. Balaji. "A Blockchain-Enabled AI and IoT Framework for Smart Travel Safety and Automated Emergency." In 2025 5th International Conference on Soft Computing for Security Applications (ICSCSA), 210-217.
  4. Bajwa, Ammar. "AI-Based Emergency Response Systems: A Systematic Literature Review on Smart Infrastructure Safety." American Journal of Advanced Technology and Engineering Solutions 2025, 1(01), 174-200.
  5. Suthahar, P., P. Sharmila, and Gioal A. Sabi. "Intelligent Road Safety System: AI-Based CCTV Surveillance." In 2025 International Conference on Computing and Communication Technologies (ICCCT), 1-6.
  6. Reddy, Medda Sreeketh, Chintala Vamsi, and P. Kathambari. "Rescue Me: AI Emergency Response and Disaster Management System." In 2024 2nd international conference on artificial intelligence and machine learning applications theme: Healthcare and internet of things (AIMLA), 1-5.
  7. Florido-Benítez, Lázaro, and Benjamín del Alcázar Martínez. "How Artificial Intelligence (AI) is Powering New Tourism Marketing and the Future Agenda for Smart Tourist Destinations." Electronics 2024, vol. 13, no. 21: 4151.
  8. Kushawah, Shreyash Singh, Amit Gupta, and Richa Gupta. "Smart Road Surveillance: An AI And ML-Based System for Automatic Accident Detection and Emergency Response." In 2024 International Conference on Cybernation and Computation (CYBERCOM), 776-780.
  9. Oyedokun, Imran Olaitan, Rafiu Adesina Ganiyu, Jonathan Ponmile Oguntoye, and Yusuf Olalekan Mojeed. "Development of an Enhanced Internet of Things-Based Wearable Human Tracking Security System with Integrated Distress Alert Mechanism." Journal of Engineering Research and Reports 2025, vol. 27, no. 12: 135-147.
  10. Fajri, Choirul, Norma Sari, Imam Karim Fathurrahman, Muhammad Najih Farihanto, and Dani Fadillah. "Artificial Intelligence-Based Risk Communication for Traveller Protection in Indonesia." COMMICAST 2025, vol. 6, no. 1: 159-173.
  11. Mishra, Dwipanita, S. Das, and Rabinarayan Patnaik. "Application of AI Technology for the Development of Destination Tourism Towards an Intelligent Information System." Economic Affairs 2024, vol. 69, no. 2: 1083-1095.
  12. Buhalis, Dimitrios. "Technology in Tourism-From Information Communication Technologies to eTourism and Smart Tourism Towards Ambient Intelligence Tourism: A Perspective Article." Tourism review 2020, vol. 75, no. 1: 267-272.