<![CDATA[This study presents an innovative intelligent system based on the Internet of Things (IoT) designed to monitor and classify the environmental conditions of Hermetia illucens larvae in real-time. This system integrates several sensors to measure important parameters such as temperature, humidity, and media height, which are then processed using the K-Nearest Neighbor (K-NN) algorithm. The K-NN algorithm groups environmental data into three categories: optimal, moderate, and poor, which will help identify the best conditions for larval growth. Data obtained from the system is automatically sent to a mobile application via an IoT network, allowing users to monitor the development of larval conditions anytime and anywhere. Testing showed a classification accuracy of 87.7%, making this system a potential tool in supporting the biodegradation process of organic waste more efficiently.]]>
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