Electrical & Electronic Engineering student projects

Internet of Things House

Student's name: Vo Dang Hai Son

Program: Bachelor of Engineering (Electrical & Electronic) (Honours)

Course: Engineering Capstone Project Part B

Year: 4

This project aims to introduce an Internet of Things-based smart home system to help users monitor home electrical devices and manage them remotely.

The system consists of microcontrollers and sensors to collect environmental information, analyse data and make decisions automatically without the user’s intervention. Such environmental information covers, for example, human movements, room temperature, humidity and outdoor light intensity.

Through data analysis and fusion, the home controller can determine the current home status and then respond to environmental changes.

By using Wi-Fi connection to transmit data to the cloud server, the system has high mobility and expandability at low cost, as well as high flexibility in integrating with new electrical devices.


Bike location tracking system in tourist area

Student's name: Duong Thuan An

Program: Bachelor of Engineering (Electrical & Electronic) (Honours)

Course: Engineering Capstone Project Part B

Year: 4

This project provides a solution to the increasing problem of bike thefts in urban areas.

A tracking device attached to the bike gives owners the ability to track down stolen bikes and retrieve them as soon as possible.

By using the free LoRa (long-range) radio frequency technology instead of the GPRS/GSM cellular service, the development of this device helps to address the high cost of commercial bike tracking devices.

Also, this project aims to improve the Global Positioning System (GPS) accuracy indoor by using accelerometer, encoder and a digital compass attached on the bicycle – also known as the ‘Dead Reckoning’ method.


Machine Learning-Based System Management for Energy Efficient Buildings

Student's name: Nguyen Minh

Program: Bachelor of Engineering (Electrical & Electronic) (Honours)

Course: Engineering Capstone Project Part B

Year: 4

This project uses machine learning to automatically control the heating, ventilation and air conditioning system (HVAC) to reduce the rate of a building’s energy consumption.

A computer vision-based machine learning model and sensors are used to collect the occupancy status and thermal status of a room.

Based on the room status, the system then generates a specific demand for the room and adjusts the HVAC system to adapt to the new status.

Energy efficiency can be increased if the HVAC system is controlled by a smart control scheme instead of conventional fixed settings.

HVAC systems are a major source of energy use, taking up to 40% of a building’s total energy consumption.