An Intelligent IoT-Enabled Vermiculture Monitoring and Control System Based on Fuzzy Inference Approach (Case Studi : Siscamling)
Abstract
Cultivating earthworms necessitates meticulous environmental control to ensure optimal growth, reproduction, and substrate integrity. Conventional vermiculture approaches depend significantly on manual monitoring, resulting in irregular moisture and pH management, hence diminishing production and resource efficiency. This research presents an intelligent Internet of Things (IoT)-facilitated monitoring and control system utilising a Sugeno fuzzy inference method for automated environmental management in vermiculture. The system amalgamates sensors for soil moisture, temperature, soil pH, water pH, and total dissolved solids with a microcontroller and cloud platform to facilitate real-time monitoring and remote oversight. Fuzzy logic is utilised to manage environmental uncertainty and ascertain suitable control measures, including irrigation, fertiliser application, and ventilation. Experimental findings indicate that the proposed system proficiently sustains substrate moisture within the ideal range of 15–30% and regulates pH values between 6.0 and 7.2. Automated reactions were effectively initiated under diverse environmental conditions, including irrigation activation at a 40% moisture threshold and nutrient correction in mildly acidic settings. The system attained dependable sensor functionality with negligible transmission latency and enhanced resource efficiency by minimising excessive irrigation and substrate waste. The amalgamation of IoT with fuzzy control offers a scalable, adaptive, and sustainable approach to smart vermiculture management.
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