Enhancing Mushroom Yield Productivity and Cultivation Efficiency with Fuzzy Logic and Internet of Things

Abstract

This research presents the development and implementation of an intelligent assistant system to enhance the productivity and efficiency of oyster mushroom cultivation. The system utilizes Fuzzy Logic and IoT technologies to optimize environmental conditions in mushroom cultivation chambers. The research objectives include developing the intelligent assistant system and evaluating its impact on oyster mushroom productivity and efficiency. The study employs a Research and Development (R&D) approach, utilizing the Waterfall model for systematic development. The conceptual framework encompasses the analysis of existing challenges in mushroom cultivation, leading to the identification of solutions through the integration of Fuzzy Logic and IoT. The system comprises sensor nodes for data collection, a collector node for data processing, and an automated watering mechanism controlled by Fuzzy Logic algorithms. Deployment of the intelligent assistant system involves installing and configuring system components in mushroom cultivation chambers. Testing is conducted through black box testing, ensuring the functionality and effectiveness of the system. The implementation of this system demonstrated a significant improvement in yield productivity, with a 37.4% increase in total mushroom yield and notable enhancements in time and labor efficiency, both by 60%. These improvements highlight the system's effectiveness in achieving consistent and optimal growth conditions, underscoring the potential of combining IoT and Fuzzy Logic in agriculture. In conclusion, the research successfully achieves its objectives by developing an intelligent assistant system that enhances oyster mushroom cultivation productivity and efficiency. The findings suggest promising implications for integrating advanced technologies in agricultural practices.