Authors

Ramachandran M

Department of Artificial Intelligence & Data Science, Kumaraguru College of Technology, Coimbatore, Tamilnadu, India

Sathish Anbu

Department of Artificial Intelligence & Data Science, Kumaraguru College of Technology, Coimbatore, Tamilnadu, India

Abstract

Ensuring the safety of minors within educational institutions is a critical challenge that demands innovative technological solutions. This study presents a comprehensive IoT-based security framework integrating tamper detection, biometric logging, GPS-based route tracking with safe zones, and real-time health monitoring to enhance student safety and well-being. The system continuously monitors student activities, authenticates identities through biometric verification, tracks movement patterns, and provides instantaneous alerts to parents, school authorities, and emergency responders in case of potential threats or abnormal conditions. By employing low-latency wireless communication, cloud-based data storage, and intelligent decision-making algorithms, the platform enables real-time intervention and proactive risk management. Additionally, robust data security measures, including end-to-end encryption and privacy-preserving protocols, are implemented to safeguard sensitive student information. Experimental evaluations demonstrate that the system can reliably detect anomalies, reduce response times, and provide actionable insights, thereby fostering a secure and controlled educational environment. This research underscores the potential of combining IoT, GPS tracking, and biometric technologies to create scalable, intelligent, and ethical solutions for student safety.

Keywords

Tamper Detection Biometric Logger Safe Zone Health Condition Reporting Real-time Monitoring

Citation of this Article

Ramachandran M, & Sathish Anbu. (2024). ECloud-Connected GPS and Biometric-Based Safety Monitoring for Children in Schools. Journal of Artificial Intelligence and Emerging Technologies. 2(6), 17-24. Article DOI: https://doi.org/10.47001/JAIET/2025.206004

Licence Copyright (c) 2026 Journal of Artificial Intelligence and Emerging Technologies. This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International Licence.

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