Enhancing Security and Efficiency with Smart Surveillance Using Machine Learning
Deepjyoti Purkayastha, Saswasto Basak, Rabi Sankar Mondal, Saikat Gharami, Pushpita Roy, Prianka Dey, Tanmoy Ghosh · 2024
The proposed system presents a novel approach to tackle challenges related to crowd control, security, and worker tracking through the application of Artificial Intelligence and Ma-chine Learning. It is tailored to meet the needs of the Indian Rail-ways and related authorities, with the primary goal of boosting operational efficiency and security measures. The system's key feature is its advanced crowd management capabilities, achieved through ML algorithms that promptly notify authorities when predefined crowd thresholds are surpassed. Moreover, it employs Artificial Intelligence to recognize potentially violent or suspi-cious behaviors, offering real-time insights via a user-friendly dashboard for round-the-clock monitoring. The system's cloud-based infrastructure ensures easy integration, cost-effectiveness, and adaptability, especially in densely populated areas. However, its success hinges on the availability of high-quality video feeds, stable internet connectivity, user-friendliness, and seamless inte-gration with existing CCTV systems. In summary, this Artificial Intelligence and Machine Learning-based system provides a comprehensive, real-time solution for enhancing security and efficiency across both public and private sectors.