Development of an IoT-Enabled Hybrid Bioreactor from Kitchen Waste and Bagasse for Decentralised Green Hydrogen Production

Background: Fossil fuel dependency and the growing burden of organic waste disposal present urgent challenges, particularly in developing nations where decentralised energy solutions are most needed. Objectives: This study describes the concept and preliminary proof-of-concept development of a low-cost, IoT-enabled hybrid bioreactor intended to convert kitchen waste and sugarcane bagasse into green hydrogen through anaerobic dark fermentation and thermochemical gasification. Materials and Methods: The work began with the construction of a glass model reactor, which allowed direct visual observation of fermentation activity. Kitchen waste and bagasse were mixed into a slurry and subjected to anaerobic conditions; maintaining stable temperature and pH proved difficult without automated controls, but visible gas bubble formation was observed between 16 and 36 hours after loading. Results: A flame test on the collected gas produced a pale blue flame, providing initial qualitative confirmation of hydrogen generation. Conclusion: Based on these prototype observations and relevant literature, a stainless-steel reactor design (Grade 316L, 10-litre working capacity) was proposed, incorporating a sensor suite -including DS18B20 temperature probes, industrial pH electrodes, piezo-resistive pressure transducers, and MQ-8 hydrogen sensors -coordinated by an ESP32 microcontroller with cloud-based data transmission via Thing Speak. Projected operational estimates for co-processing approximately 2 kg kitchen waste and 1.5 kg bagasse over a 48-hr cycle suggest a hydrogen production rate of around 0.7 L/hour, yielding roughly 19.2 L per kilogram of total waste input under stable mesophilic conditions (pH 6.8-7.2; 35-45ºC). The modular system architecture is designed for scalable deployment from households to community level. This article presents the prototype findings, proposed system design, and estimated performance data alongside a review of the relevant literature.