Published Paper Details:

Inefficient energy control means that traditional tea processing machines waste too much electricity, resulting in high operational costs and resources waste. Error detection is manually delayed, leading to machine downtime, reduced productivity and increased maintenance costs. There is no real-time monitoring and prediction mechanism, resulting in electromechanical failures and electrical fires. The developed system combines IoT, intelligent sensors and adaptive control to efficiently optimize the energy consumption of the tea industry. Predictive analyses identify anomalies, promote timely interventions, and minimize energy waste for green tea production. IoT-based automation facilitates real-time monitoring, anticipated maintenance, and remote access for increased efficiency and reliability. AI-controlled data analysis reveals an understanding of behavioural patterns so that factory managers can make clear power optimization decisions. The integration of forecast expectations, real-time data recording and automated control systems provides a more sustainable and energy efficient tea production process in line with global initiatives for intelligent industry transition and energy saving