Autonomous tractor with augmented mixed virtual reality to collect , access and analyse soil
process that makes IoT a worthy paradigm for end-to-end agricultural management systems . Agricultural data are collected by unmanned aerial systems ( UAS ) and various remote sensing devices , and are then processed and analysed via intelligent learning mechanisms for prediction ( i . e ., regression , classification and clustering ), data mining and pattern recognition or data analytics in general . Pest and disease recognition for plants , land and crop detection or classification , fruits detection and quality monitoring , and crop growth phenotyping are among agricultural IoT applications that use artificial intelligence ( AI ) to replace human know-how . These applications utilise vision and image classification as their core intelligent service , that has a direct impact on computational complexity , cost ( i . e ., data storage and processing ) and efficiency of transmission . The capacity of processing big data and optimising transmission efficiency requires additional levels of intelligent computational methods such as machine learning and deep learning .
This article discusses the characteristics of an agricultural IoT ecosystem and agricultural IoT applications that use intelligence to solve real problems . Later , we introduce the convergence of the Internet , intelligence and things , namely the concept of Intelligent Internet of Things ( I-IoT ).
We summarise some of the challenges and share future research directions for successful I-IoT applications toward intelligent agriculture .
CHARACTERISTICS OF AGRICULTURAL IoT ECOSYSTEMS
IoT Devices / Modules The first layer of technology stacks in an IoT ecosystem is the embedded systems , which interact with sensors and actuators through wireless connectivity . These systems are called IoT devices or IoT modules . The embedded system , that consists of field programmable gate arrays ( FPGA ) or microprocessor , communication modules , memory and input / output interfaces , act as a shield for connectivity . The connected sensors have the capacity to record measurements such as air temperature , soil temperature at various depths , rainfall , leaf wetness , chlorophyll , wind speed , dew point temperature , wind direction , relative humidity , solar radiation , and atmospheric pressure .
Another indispensable element of this layer is the actuators . Actuators are responsible for moving and actuating systems or mechanisms in agricultural operations . Imagine a smart watering system that can be activated based on soil
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