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

The persistent attacks on farmers by herdsmen, bandits, and unknown gunmen worldwide have significantlydisrupted agricultural production and endangered farmers. This paper presents a scalable real-time IoT agri-cultural farm sensor-based application monitoring system aimed at enhancing agricultural productivity andimproving farmer surveillance. Agriculture remains a critical economic driver for many countries. Leveragingthe Internet of Things (IoT), this system seeks to boost farm efficiency and yield while minimizing lossesand waste. The proposed system comprehensively monitors agricultural farms using smart devices, includingsensors, cameras, and internet-enabled technologies. The application was developed using object-oriented lan-guages such as C-Sharp, Python, and Django, integrating data from soil moisture, temperature, and humiditysensors connected to an Arduino microcontroller. Additionally, Django facilitated the development of a cropmonitoring 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 ofagricultural farms from any location. The application delivers accurate and actionable information to users,particularly farmers, for effective farm management.