This paper proposes a real-time farm monitoring system intended to improve decision-making processes and resource utilization in agriculture. Using IoT devices such as camera devices and sensors for temperature, soil, UV, and humidity, the system provides constant monitoring of farm environments. The gathered data are cleaned, normalized, and preprocessed for feature extraction such as moisture and temperature of the soil, and then analyzed using the RF algorithm. This processed data helps in predicting important farming requirements for instance in irrigation and pest control. The refined information is then sent to a server using LoRa communication for storage and analysis. Farmers receive real-time information by using a convenient application to manage their crop and business. Some of the accounted features include accurate predictions, proper functioning of the sensors, and well-executed preprocessing task all of which show the efficacy of the system is the ability to use data analysis methods to enhance resource control and crop health.