Guest Editorial Special Issue on Smart Sensing for Agriculture

Seamless integration of sensor technologies with traditional agriculture has led to a revolutionary transformation in agriculture. This has motivated researchers to use sensor technology, GPS guidance, control systems, drones, and software services for ensuring optimal conditions for the crops and soil. For instance, unmanned surveillance on the agricultural field, automated soil and crop assessment, etc., assist the farmers by monitoring the soil conditions, environmental factors, and crop features. Smart sensing enables the objects to be sensed and controlled remotely using network model. Sensors help in collecting real-time data about the crops, soil, and surrounding conditions. The collected data can be used in managing the agricultural activities by performing predictive analysis using various machine learning and deep learning techniques. These advanced learning techniques mitigate the human errors by analyzing the large amount of sensory data and facilitate smart sensing in agriculture.