Enhancing Bamboo Dryer Using IOT Control

Farrah, Wong and Mohd Syaqir, Japarudin and Sariah, Abang and Hoe Tung, Yew and Mazlina, Mamat and Ing Ming, Chew and Aroland, Kiring and Jamal, Ahmad Dargham (2023) Enhancing Bamboo Dryer Using IOT Control. In: 8th International Symposium on Intelligent Informatics (ISl'23), 18-20 Dec 2023, Bangalore, India. (In Press)

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Abstract

The ideal temperature and humidity levels for the drying process of bamboo vary depending on the species of bamboo and desired product. This system has been designed to create an optimal and controlled drying environment within the temperature range of 50°C to 52°C encompassing three integral subsystems. At the core of this innovation lies the Control Subsystem, a pivotal entity responsible for maintaining the precise drying conditions required for optimal results. This subsystem integrates a range of components, including the NodeMCU-ESP32 microcontroller, DHT22 temperature and humidity sensors, 2 Channel 5V relays, AC Heater, and AC Fan. These elements collaboratively function to dynamically regulate the temperature and humidity parameters essential for efficient bamboo drying. The Communication Subsystem, seamlessly interfaced with the Blynk cloud platform, bridging the gap between the IoT components and user interaction. Through this innovative feature, the drying process becomes accessible from remote locations, enabling real-time monitoring and control via the Blynk mobile application. The Monitoring Subsystem through the I2C LCD Display provides users with a localized display of critical drying such as average temperature and humidity. On the experimental results, a comparative analysis between the traditional sun-drying approach and the IoT-Based Dryer method elucidates significant differentials in weight loss and moisture reduction trends. The latter consistently showcases heightened efficiency by achieving higher average moisture loss percentages, signifying its ability to rapidly reduce moisture content within bamboo samples by 5%. Furthermore, the IoT-Based Dryer method demonstrates enhanced time efficiency, predictability, and consistency due to its controlled and optimized drying conditions.

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