International Journal of Scientific Research and Engineering Development

Vehicle theft continues to pose a global challenge, with millions of vehicles stolen annually and recovery rates often below 50%. Traditional tracking systems, particularly those relying on GSM and SMS communication, suffer from latency, poor scalability, and security vulnerabilities, limiting their effectiveness in preventing theft in real time. This paper presents a systematic review of vehicle tracking and alerting systems published between 2014 and 2025, focusing on database-driven architectures and modern communication technologies. This review categorizes prior studies into four thematic groups: GSM/SMS-based tracking systems, IoT and cloud-integrated platforms, biometric and advanced security systems, and AI-enhanced monitoring approaches. Comparative analysis highlights recurring limitations, including reliance on SMS with delayed alerts, weak authentication protocols, and limited scalability in multi-user contexts. Conversely, emerging solutions leveraging LTE/4G connectivity, cloud databases such as Firebase, and geofencing algorithms have demonstrated significant improvements in terms of latency, reliability, and user accessibility. The findings reveal that database-driven systems provide a robust foundation for real-time monitoring, automated alerts, and historical data analysis, offering enhanced deterrence and recovery potential. However, gaps remain in predictive analytics, advanced security hardening, and integration with fleet-scale operations. This review concludes that future research should prioritize AI-based motion prediction, multi-vehicle tracking, and secure cloud architectures to improve the effectiveness of vehicle theft reduction technologies.

Musa Mamman, Abdoulie M. S. Tekanyi, Hassan Abubakar Abdulkareem, Aquila Nuhu Tanko,"A Systematic Review of Database-Driven Vehicle Tracking and Alerting Systems for Theft Reduction" International Journal of Scientific Research and Engineering Development, V9(2): Page(626-638) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.