Smart Irrigation Systems: Soil Monitoring and Disease Detection for Precision Agriculture

Abstract

Smart farming is an evolving concept in the field of information and communications technology. In this, the IoT sensors and image processing is used to establish transparent mechanisms of feedback about the growth and productivity of crops and the environmental surrounding conditions. In this paper, the solution of the aforementioned problem statement in the form of an accountable live information system of the cultivated crops to yield efficiency has been presented. The feedback mechanism consists of monitoring parameters like temperature, humidity, weather, soil and crop moisture, crop health, etc. It provides the information between the planting phase and the harvesting phase to facilitate soil management and climate forecasting in real time. The proposed paper suggests the use of an open data platform, namely Adafruit IO, for visualizing and analyzing real-time in the IoT integrated system. Further, image processing approach has been used for crop remotely health monitoring for 2 widespread diseases namely, Glomeralla Cingulata and Phaeoisariopsis Bataticola. Owing to the economical nature and the ergonomic design of the proposed system, it has the feasibility of being implemented on a large scale in water scarce economies aiming to build a sustainable smart farming infrastructure by automating existing irrigation systems.