Edge-Intelligent Smart Farming Architecture for Real-Time Soil, Crop, and Environmental Monitoring

Abstract

Contemporary farming demands rather smarter surveillance tools that would be able to enhance productivity, sustainability and environmental consciousness. Traditional production processes are usually characterized by a slow decision-making process, poor use of resources and a lack of real-time tracking. The current paper is a proposal of an Edge-Intelligent Smart Farming Architecture to monitor the soil, crop, and environment in real-time based on the built-in IoT, edge computing, and intelligent analytics. The suggested system is a collection of distributed agriculture sensor networks, wireless communication, processing of data at the edge, and cloud-assisted monitoring in a single smart agricultural system. The soil moisture, temperature, humidity, pH, light intensity and environment conditions are constantly tracked and computed at the edge layer to minimize the latency and network overhead. Experimental analysis proves that there is an increased monitoring accuracy, decreased response-latency, increased energy-efficiency, and reliable environmental-sensing performance with the application of experimental evaluation in contrast to the traditional cloud-based agricultural systems. The suggested architecture will be scalable to be used in precision agriculture, sustainable farming, automated irrigation management, and intelligent rural monitoring applications.