This comparative review explores the advancements and applications of Artificial
Intelligence (AI) in agriculture, focusing on the developments in the United States (USA) and …

As per the FAO, the insect pest causes 30 to 40 percent loss every year across the globe.
The identification, classification and management of insect pest is very important to avoid …

The increasing food scarcity necessitates sustainable agriculture achieved through
automation to meet the growing demand. Integrating the Internet of Things (IoT) and …

The integration of deep learning and blockchain technologies has the potential to
revolutionize soil quality prediction in smart agriculture. Deep learning models, like neural …

International trade, through global supply chains, is central to global sustainable production
and consumption. Redistribution of environmental resources impacts through international …

Many smart applications, including smart cities, healthcare, smart agriculture, manufacturing,
etc., have widely adopted the Internet of Things (IoT). Smart Farming (SF) integrates a set of …

Blockchain (BC) represents a disruptive technology that has been extensively used to
ensure immutability of digital transactions. Starting as an underlying mechanism in the …

The increasing global population drives a rising demand for food, particularly fish as a
preferred protein source, straining capture fisheries. Overfishing has depleted wild stocks …

Blockchain (BC) and Computer Vision (CV) are the two emerging fields with the potential to
transform various sectors. BC can offer decentralized and secure data storage, while CV …

Smart farming is generally defined as an IT-based intelligent farming system that finds,
analyses, and manages field variability by carrying out crop production activities at the right …