Published Paper Details:

The Potential and Difficulties of Artificial Intelligence in Improving Internet of Things-Based Surveillance Systems Aaryan Agrawal*, Aasha Shah*, Ayush Bhardwaj*,D Abdul Rahaman*, M Dakshayini* * Department of ISE, B.M.S. College of Engineering, Bengaluru, Karnataka, India. Abstract: The integration of Artificial Intelligence with Internet of Things is revolutionizing the IoT-centric surveillance system, making it more agile and proficient in identifying, monitoring, and responding to all forms of threats within seconds. The varieties of sensors and drones continue to capture numerous data around them, and the AI algorithms calculate this data to identify patterns, alert anomalies, and predict potential security threats. The AI-driven system has the ability to autonomously detect intruders, monitor suspicious activities, and monitor environmental hazards like a fire threat. The advanced deep learning algorithms and computer visions have started to be used to help identify objects, support autonomous decision-making processes, and enable quicker responses. These surveillance drones now can be deployed and utilized for reconnaissance missions in highly vast areas and then send back autonomous responses. AI in IoT-based surveillance, though, brings forth challenges such as issues with data privacy, the need for robust energy-efficient devices, and complexity in real-time processing. However, AI and IoT together are creating smarter and more adaptive surveillance systems, offering advanced solutions in security within smart cities, industries, and public venues.