ABSTRACT
Smart agriculture is present-day trend of farming. The usage of smart tractors mounted with global positioning system and other sensors as farming vehicles is a common fashion nowadays. Data visualization tools are currently in place with the ability to transmit real-time data. Drones are a big player in this setting where built-in sensors provide different types of aerial imaging, field survey, and location mapping. A range of mobile sensing technologies are being applied to provide a detailed analysis of field conditions in terms of soil layer, nutrient levels, and overall ambient environmental conditions. Smart irrigation by looking into the evapotranspiration parameter of plants is used to optimize the irrigation cycle. The smart scheduling of irrigation by analyzing the soil moisture content and temperature using sensors is being done. The Internet of Things (IoT)-based applications are in greenhouses and vertical farming integrated with emerging practices of aquaponics, aeroponics, and hydroponics. The use of wireless sensor networks (WSNs) for different environmental monitoring intended for diverse applications has been widely implemented. The objective of this chapter is to highlight the use of WSNs and IoT in agriculture and give a comprehensive review of the sensor and IoT data analytics using machine learning techniques for agricultural applications.
