Smart Sensing Technologies and Data Analytics for Precision Agriculture

摘要

The financial sustainability of traditional agricultural systems is being challenged by demand-based global competition in agricultural products, compelling the conception of new, innovative production techniques. Smart agriculture uses smart technologies like the Internet of Things, big data, sensors, robots, drones, and AI-based solutions. The field of smart agriculture has rapidly evolved over the past decades with the application of data analytics. Various aspects of precision agriculture, like crop image analytics, crop disease detection, environmental monitoring, soil monitoring, and irrigation system support, are automated at varied levels by adapting different data analytic techniques. The significance of the convergence of data analytics and smart agriculture is much required. Smart sensing technologies and data analytics are adapted to maximize productivity, profit, sustainability, and protection of land resources by minimizing production costs. In order to sustainably conserve natural resources like water, air, and soil quality while being commercially successful, it is essential to change agricultural management practices. Therefore, this chapter focuses on the application of data analytics to precision agriculture. It aims to explore the different facets of data analytics in agriculture sectors and present the challenges and opportunities of precision agriculture based on data analytics. The impact of data analytics adapting various methods and tools is presented to provide an insight into the importance of precision agriculture. The statistics obtained from the analysis enable the farmers to use the data to gather information from various farming operations. It allows farmers to estimate harvest yields and the requirements for light, water, fertilizer, and pesticides. Data analysis facilitates farmers being better equipped to anticipate farm activity and use techniques that are both healthier for their crops and more environmentally friendly.