The production of bioethanol from agricultural waste presents a promising solution for sustainable renewable energy development while simultaneously mitigating the environmental burden of organic residues. Despite its potential, conventional bioethanol production methods particularly during fermentation and distillation are often hindered by poor process control, resulting in low conversion efficiency and excessive energy consumption.This study proposes the design and implementation of an Internet of Things (IoT)-based monitoring system aimed at optimizing the bioethanol production process. The system integrates temperature, pH, and turbidity sensors to enable continuous monitoring of critical parameters during fermentation and distillation. Data from these sensors are processed in real-time using an ESP32 microcontroller and transmitted to a cloud-based platform for visualization and control. Experimental results indicate that the proposed IoT system enhances the conversion efficiency of biomass to bioethanol by 35% and reduces energy consumption by 20% compared to traditional methods. These findings demonstrate that real-time monitoring through IoT integration significantly improves process efficiency, consistency, and sustainability in bioethanol production from agricultural waste. This research contributes to the advancement of intelligent control systems in bioenergy applications and supports the global transition toward clean, eco-friendly, and data-driven energy technologies.
                        
                        
                        
                        
                            
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