Machine Learning for Autonomous IoT-Enabled Drones in Smart Surveillance

Abstract

Autonomous drones equipped with IoT sensors and machine learning algorithms are transforming surveillance and security operations. This paper explores ML models such as reinforcement learning, computer vision-based object detection, and neural networks for drone-based surveillance. It discusses challenges like real-time data processing, energy efficiency, and privacy concerns. Case studies highlight successful deployments of ML-driven autonomous drones in areas such as disaster response, wildlife monitoring, and border security, demonstrating enhanced situational awareness and decision-making capabilities.