ELEC FYP/T Best Midterm Poster Awards 2021-2022
The Champion - Piu Suen FUNG, Kam Hung WONG
"Sensor System using Wireless Energy Harvesting" (Final Year Project)
This project aims to design and build an IoT sensor system that is powered by ambient radio-frequency energy which allows the sensor system to not be required to connect to any external power supply like the battery. The project can be separated into two parts: the RF energy harvesting part and the IoT sensor system part. The RF energy harvesting part needs to build the rectenna to extract, the redundant radio frequency power from the environment, which means that we can reuse the redundant power of our wireless mobile phone network. The IoT sensor system part requires low power consumption due to the power from RF being very low. The power budget of the system will be critical. Combining two parts will form an IoT system that does not require an external power supply.
This project was supervised by Prof. Ross MURCH.
The Champion - Hon Hang Benny LEUNG, Yiu San LEUNG
"Motion Tracking Technology in Game Controllers" (Final Year Project)
It is a common fact that Hong Kong people are living a sedentary lifestyle, involving little or no physical activity. The threat to a person's well-being is further amplified in the lockdown period where most outdoor sports activity is prohibited as it poses a greater risk of spreading infection.
Our project aims to integrate motion capture technology into game controllers and gamify sport to create a dynamic and rewarding exercising experience.
In our project, we will utilize Kinect and IMU as tracking sensors. For IMU, in order to combine sensor data to perform pose recognition, sensor fusion algorithms, and signal filters are implemented to process raw data into the body part orientation and displacement. For Kinect, a game engine is developed to capture motion data and fuse it with IMU data.
A custom game will be developed to demonstrate the motion tracking capability of our controller.
This project was supervised by Prof. Vincent LAU.
The First Runner-Up - Chun Yu HO, Ka Yi KAN, Erqiang TANG
"Cloud Based Wireless Coverage Characterization" (Final Year Project)
This project aims to optimize the data collection process in the empirical measurements-based method through cloud computing and design a neural network which can accurately model the coverage of a wireless network. More specifically, the data required for modeling is directly collected from the end users through a mobile application and uploaded to a backend server on the internet, which is the cloud essentially. The cloud then feds the received data into the algorithm to train it. As more data gets collected, the algorithm can construct an accurate wireless coverage model of the target site.
This project was supervised by Prof. Vincent LAU.
The Second Runner-Up - Wai Ching TANG, Kin Kwan YEUNG, Ching Yuen YU
"Autonomous Docking and Recharging for Indoor Drones" (Final Year Project)
Drone is one of the cutting-edge technologies that bring us to the era of smart cities. Nowadays, drone application is becoming wider and more mature. However, short battery life is the major obstacle the slowing down drones’ evolution.
An autonomous charging system for indoor drones is proposed in the project to overcome the limitation caused by the shortage of battery life. The drone can navigate back to the dock and land automatically, while the charging dock will start charging the drone when the drone is successfully landed. When the charging process is finished, the drone can take off again and continue the mission. This is a fully automated and reliable solution for indoor drone operation.
This project was supervised by Prof. Wai Ho MOW.
