Remote sensors for hyperautomation in agriculture

Hyperautomation in agriculture plays an important role in meeting the huge demand for agricultural food crops, industrial raw materials, and fuels in highly populated countries like India. IoT-enabled crop, soil, weather monitoring systems, and plant disease prediction models are now becoming popular to meet the requirements of agriculture automation along with environmental sustainability. Remote sensing is one of the important steps of such agriculture automation that requires various types of sensors at different farming and crop production levels. Remote sensors embedded with IoT platforms are used in most of the processes of smart farming. The sensor must be able to adapt digital techniques and prediction models. Sensors are not only used in measuring the condition of soil moisture and temperature but also helpful in knowing plant health and disease predictions. Different types of active and passive sensors are available that are used in remote sensing and mainly work for communication, forecasting, biological research, weather monitoring, resource monitoring and assistance, etc. Such a sensor is compatible with modern techniques like artificial intelligence and machine learning or hyperspectral imaging embedded with IoT wireless features. This chapter provides an overview of the theory and fundamentals of smart sensors, remote monitoring, and a brief discussion on models and techniques for plant disease prediction. In addition, this chapter discusses different IoT platforms for remote sensing applications in agriculture that include crop monitoring, assessment of plants and animals, soil quality, water quantity, data analysis, industrial monitoring, and security applications. Lastly, the environmental impact and challenges of such remote sensing techniques are discussed to ensure a sustainable environment.