Application of AI-based Technique to Enhance Thermal Comfort Sensing for Smart Air Conditioner
Project Description

The human comfort, measured in terms of predictive mean vote (PMV) according to AHRAE standard, depends on both environmental parameters (such as air velocity, relative humidity (RH), radiant and air temperature) and personal factors (such as clothing insulation and human activity). Commercially, thermal comfort measurement system are available in the market. However, the cost of these comfort sensing systems is very expensive. The ultimate prerequisite for the applications of the thermal comfort scheme is to develop accurate thermal comfort sensing system at small expenditure. This project is to utilize MEMS motion sensor available in the smart phone to measure human metabolism rate which can then be integrated with other low cost (Temperature/Humidity/Velocity) sensors to measure thermal comfort in building

Supervisor
LEE Yi-Kuen
Quota
2
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles

The main task of the student will be focused on smartphone app development, MCU to smartphone communication, etc. The student(s) will develop a smart phone app which can send sensor data from phone online to a website/database. The student also needs to setup communication between smart phone and low-cost Arduino MCU to transfer data between phone and Arduino via wireless media (Bluetooth/wi-fi).

Applicant's Learning Objectives

Understand the basic principle of human thermal comfort index, the air conditioner,
Understand how to develop Smartphone App,
Understand how to develop the website/Database,
Understand how to develop the open-source programming for Arduino microcontroller unit (MCU),

Complexity of the project
Moderate