Smart Farming: An Approach for Disease Detection Implementing IoT and Image Processing

1. Introduction

The advancement in Sensor nodes and evolution of 5G technologies has gained recent attention and the objective of this article is focused on considering the use of Internet of Things and smart sensor for the application of agriculture (Lin et al., 2018). The evolution of sensor networks and IoT has gained attention in agriculture domain and the deployment of sensor node in real time environment collects the field data at any time and collected data is analysed in real time basis through IoT analytics platform. The cloud platform provides the real time analysis of data for the detection of adversaries in data. The IoT is termed as the network of objects or smart devices, smart vehicles, smart home, buildings and each item which is embedded with electronics, smart sensors, network connection and software’s as these advancement in technologies enables these smart devices to collect and exchange data among each other. The Internet of Things is addressed as the global organization towards information society and provides advanced solutions and services through connecting physical and virtual smart devices (things) on the basis of their evolution and existence of communication approaches. The objective of this article is then collaborated with the image processing for the confirmation and detection of diseases in crops along with the concept of cloud computing for meeting the requirement analysis of obtained data in real time. Majority of the smart farming application has adopted Internet of Things and presents the benefits of using the advanced sensing and analysis for crop production (Gayatri et al., 2015). The adaptability of IoT in majority of applications has proved the potential of the technology for various areas that includes tracking of assets, industrial management, security aspects, energy utility and monitoring based on conditions. IoT serves variety of other applications such as smart transportation, smart homes, lifestyle, smart building, smart agriculture, healthcare and environment monitoring. IoT is often named as thing of things or network of networks and because of this, IoT technology can perform different tasks at the same time with more accuracy and much efficiently. Image processing is the process in which the images are processed by implementing some mathematical expressions. Image processing uses signal processing at which the input is any image or multiple images or videos whereas the output of an image processing can either be any image or the extracted characteristics which are related to that image or series of images and output image is often termed as digital image (Sharma et al., 2017). Digital image processing requires various algorithms for the operation of performing image processing at digital images (Dogra et al., 2020). The prime operation of digital image processing involves classification (identification of the class at which the new extracted observation belongs), pattern recognition (recognition of known and discovering unknown patterns), feature extraction (derivations which are made using initial information), signal analysis (processing of signals) and at last projection (formation of planar surface by conversion of three dimensional object).