Frost Prediction in Highland Crops Management Using IoT-Enabled System and Multiple Regression

Abstract

The magnitude of the effects of climate change in the agriculture-driven growth, countries, and regions in the world has expurgated the crop production and a decrease in agricultural productivity and eventual price surge. In 2014, it was accounted that agriculture is one-third of the global gross domestic product which was crucial to the country and global economic growth. With the recent problems in the agricultural sector, agriculturists and engineers have explored the advent of the cyber-physical system and automation age by using Precision Agriculture to address these issues and problems particularly in frost prediction in highland crops management. This chapter will discuss the concepts of Precision Agriculture and applications of the Internet of things (IoT) in agriculture, the design and challenges of an IoT-enabled system for highland crops management, and utilized multiple regression as a frost prediction technique. The remote sensing device deployed in the farm collects the frost climatic events including air velocity, temperature, and humidity, and transmitted to the web server. The system provides early warnings and frost forecast for the farmers using SMS. The system helped farmers as a useful resource to conduct frost protection activities on the farm, thereby reducing the frost harm to the crops.