IoT-Based Smart Monitoring and Controlling System for Shallot Planting Medium Conditions Using a Combination of Context-Aware and Fuzzy Logic Algorithms

Abstract

Shallots are a high economic commodity that needs special attention because this plant is a high-risk horticultural commodity and is in the short-lived plant category. Moreover, shallot growth relies on environmental variables, such as temperature, soil moisture, soil pH, and humidity. However, Indonesian farmers have difficulties maintaining shallot growth since they only rely on the weather and do not use special equipment to measure the soil condition. Therefore, the monitoring and controlling system is required to be a solution for maintaining the growth parameters of shallot. This study proposed a system that could control and monitor the soil conditions of the shallot based on IoT technology and applied context-aware and fuzzy logic algorithms to control the actuator. The proposed system was developed to control the soil conditions using three specific liquids: neutral water, pH-lowering liquid, and pH-increasing liquid. These liquids were utilized to control the soil pH, soil temperature, and soil moisture. A microcontroller controlled them according to the context-aware algorithm analysis, and the data from the sensor was converted into context information. Then, fuzzy logic will use this information to control the liquid pump. The result can exhibit a high accuracy sensor with more than 0.9 of the coefficient determination, indicating that the sensor measurements perform similarly to the instrumentation devices as a reference. Moreover, the proposed system can successfully handle several conditions by utilizing the information processing of a context-aware algorithm and using it as control parameters of fuzzy logic.