AI-Assisted ESP32-CAM Based Smart Surveillance System for Precision Agriculture

Abstract

Agriculture plays a crucial role in ensuring food security and supporting the global economy. However, farmers often face challenges such as crop theft, animal intrusion, and lack of real-time monitoring of agricultural fields. Traditional field monitoring methods require continuous human supervision and are often inefficient for large-scale farms. With the rapid advancement of Internet of Things (IoT) technologies, intelligent surveillance systems have emerged as effective solutions for improving agricultural monitoring and farm security. This paper proposes an IoT-enabled Smart Agricultural Field Surveillance and Monitoring System using ESP32-CAM designed to provide real-time visual monitoring and remote access to agricultural field conditions. The proposed system utilizes an ESP32-CAM module equipped with a camera sensor to capture live images and video streams from the field. The device is connected to a wireless network, enabling farmers to remotely monitor crop conditions and field activities through a mobile application or web-based interface. The system also supports motion detection capabilities, allowing automatic alerts to be generated when unusual activities such as animal intrusion or unauthorized human presence are detected. The proposed system offers several advantages including low-cost implementation, energy-efficient operation, and real-time remote monitoring capabilities. By integrating IoT technology with embedded camera modules, the system enhances field security and helps farmers respond quickly to potential threats. Experimental evaluation demonstrates that the system can effectively provide continuous surveillance and reliable monitoring in agricultural environments. The proposed approach contributes to the development of smart farming infrastructure by enabling efficient crop monitoring, improving farm security, and supporting precision agriculture practices.