Developed in 2020 NUS School of Computing Summer Workshop in Artificial Intelligence and Internet of Things (AIoT).
Tang Ningzhi from Southern University of Science and Technology
Chen ZiHan from Nanjing University of Information Science & Technology
Dr. TAN Wee Kek from National University of Singapore
- 11912521@mail.sustech.edu.cn (Tang Ningzhi)
- zihan.chen.cs@rutgers.edu (Chen Zihan)
Food culture plays an important role in Chinese culture. However Chinese dishes is usually cooked with much oil and stir-fried, which leads to harsh working conditions for cooks and waiters in the kitchen. Chinese kitchens, especially those in the restaurant, often have problems as high temperatures, high humidity, high smoke concentrations and the risk of fire in some situation.
Our project is a kitchen comfort monitoring system based on machine learning intelligent classification controlled by Raspberry Pi and cloud computer. We hope to improve the situation and solve these problems with our kitchen comfort monitoring system. It has three main functions:
- Real - time monitoring: monitor environment around from sensors
- Intelligetn classification: invoke machine learning model to classify the state of environment
- Automatic Control: automatically control the actuator by judging the state
For the specific system structure and implementation process, please read our poster and slide.