An Edge Computing–Enabled Smart Agriculture Framework for Real-Time Crop Monitoring

The growth in the use of Internet of Things (IoT) technologies in the Agricultural sector has allowed the large-scale population of crop surveillance and farm control data. Nevertheless, traditional architectures that are cloud-based are associated with high latency, bandwidth-dependent as well as poor real-time responsiveness whose limitation renders them ineffective in applications that require real-time performance in agriculture. In order to overcome them, this paper suggests an edge computing-based smart agriculture system, which will conduct local data processing and decision-making near the sensing layer. The suggested architecture incorporates a combination of the environmental sensors based on IOT and an edge gateway to preprocess data and perform smart decision logic and offer real-time notification of the agricultural activity, i.e. irrigation and crop status. The cloud receives only critical data and stores it in the long-term and visualizes it, minimizing the overhead on communication. The performance analysis proves the fact that the edge-based solution provides a significant decrease in latency and bandwidth utilization compared to cloud-only systems and enhanced response time and the stability of the system. The suggested scheme is affordable, extensively applicable, and real-time, and can be utilized in precision farming and sustainable agriculture.