A SCALABLE REAL-TIME IOT AGRICULTURAL FARM SENSOR-BASED APPLICATION MONITORING SYSTEM

Abstract

The persistent attacks on farmers by herdsmen, bandits, and unknown gunmen worldwide have significantly disrupted agricultural production and endangered farmers. This paper presents a scalable real-time IoT agricultural farm sensor-based application monitoring system aimed at enhancing agricultural productivity and improving farmer surveillance. Agriculture remains a critical economic driver for many countries. Leveraging the Internet of Things (IoT), this system seeks to boost farm efficiency and yield while minimizing losses and waste. The proposed system comprehensively monitors agricultural farms using smart devices, including sensors, cameras, and internet-enabled technologies. The application was developed using object-oriented languages such as C-Sharp, Python, and Django, integrating data from soil moisture, temperature, and humidity sensors connected to an Arduino microcontroller. Additionally, Django facilitated the development of a crop monitoring system employing sensor data and machine learning algorithms to detect crop diseases and pests. The deployment of this system enhances farmers’ confidence by providing real-time monitoring and control of agricultural farms from any location. The application delivers accurate and actionable information to users, particularly farmers, for effective farm management.