ADVANCE STOLEN PREVENT SYSTEM BASED ON REAL TIME
International Research Journal of Modernization in Engineering Technology and Science · 2024
This paper proposes an advanced stolen prevention system leveraging real-time data for enhanced efficacy.Traditional stolen prevention mechanisms often suffer from latency in detecting and responding to theft incidents, leading to significant losses for individuals and organizations.In response to this challenge, we present a novel system architecture that integrates cutting-edge technologies such as GPS, RFID, and IoT sensors to enable real-time monitoring and analysis of asset movement.Through a comprehensive literature review, we identify the limitations of existing systems and highlight the critical role of real-time data in mitigating these challenges.Our proposed system architecture encompasses data acquisition, processing, and analysis stages, facilitated by advanced algorithms and machine learning techniques.Alerts are generated in real-time based on anomaly detection algorithms, enabling swift response and mitigation actions.To validate the effectiveness of the proposed system, a case study implementation is presented, demonstrating significant improvements in theft prevention and asset recovery rates.The findings underscore the importance of realtime data in modern stolen prevention systems and provide valuable insights for future research and development in this domain.