Innodragon is a high-quality soccer robots for teenagers, and adults who wish to enjoy the fun of robotics with their kids. Our robot utilizes high quality, long-lasting materials, including CNC aluminum, rubber and solid wood to ensure ease of control and robustness. It also unleashes creativity by allowing flexibility in programming and assembly of components.
Our robotic fish swimming across the harbour from Central to TST will prove its applicability in seawater.
Along with its prior speed record and additional features, it is beneficial to society because its biomimicry nature doesn’t interfere with marine life like other technology automation such as boats or submarines.
Compared to the previous model, it is much more energy efficient, less polluting, constructed with less material, and thus environmentally friendly.
HKU UAS is an Unmanned Aerial Systems team dedicated to forming a community of Unmanned Aerial Vehicles (UAV) enthusiasts and its associated systems, consisting of two technical teams: Mechanical Team and Computer Science Team. The team aims to join the AUVSI SUAS international competition, situated in Maryland, U.S.A. The competition requires the team to design a UAS capable of Autonomous Flight, Obstacle Avoidance, Object Detection, Classification and Localization, Airdrop and Package Delivery.
Sewage monitoring is an effective preventive measure to detect possible outbreaks early due to viral sheds in sewage systems. However, the current sewage monitoring system is labour-intensive, time-consuming, and lacks scalability. Here, we present our PERfECT viral sewage monitoring system, which is scalable, digital, and can detect viral presence in real time.
PERfECT is a personalized electronic reader for electrochemical transistors that detects viruses when a DNA aptamer is attached to its sensor. Once the virus is detected, the data will be uploaded to the cloud and alert authorities. PERfECT viral detection is much faster than PCR and is reusable. With PERfECT being customisable, it can also monitor the disease progression of different viruses.
Alertio is a danger alert app for deaf people. It utilizes the state-of-the-art Machine learning model to detect potential danger sounds. The sounds that we aim to detect include car alarms, bicycle rings, fire alarms, etc. Once the potential danger sound is identified, our app will send an alert to the user through intense vibration of the device as well as turning the app background into eye-catching light red color.
We use motion capture and face capture devices to track the skeletons and facial expressions of the actors. Then we use Unity to receive the motions and power characters(virtual idols) to deliver speeches, dance, sing, and so on.
The main aim of this training course is to equip students with practical experience and
a general exposure to (i) manufacturing processes, (ii) product design, and (iii) system
development.
The training course includes a number of modules, covering areas such as design
practice, manufacturing technology, measurement, quality control, assembly
technology, inspection, troubleshooting, testing, and modification, health and safety,
and environmental issues.
These modules are designed to motivate students to use creative thinking in the
projects, which help them become innovative and open-minded in solving
engineering problems.
In the current digital age digital advertising is becoming one the largest industries outside of manufacturing and production. Digital advertisement usually take many forms ranging from social media AD’s to celebrity endorsements. One of the main platform for advertisement, especially for the service industry, is online reviews.
Platforms such as Yelp and Google Reviews are major players in the online review industry, and as with all industries, businesses are willing to pay money for better privileges. Unfortunately, this also translates to situations where online reviews are artificially inflated by the platform or by AstroTurf companies.
The objective of this project is to create a proof of concept project which implements a “web-of-trust” system to allow reviews to be verified for authenticity. The project will also implement a time decay system to ensure reviews are a reflection of the most recent development rather than outdated events.
We will undertake two major projects in our SIG. The dual goals are to apply both eXtended Reality (XR) and Machine Learning (ML) to studying the human past with archaeology through an exploration of digital humanities potentialities. We will use XR to collect data and to present these data for education and public engagement to teach everyone about the past through archaeology and archaeological fieldwork. We will use ML to improve our ability to find and study ancient sites of the past.
Design, Build & Fly (DBF) is a regular capstone design project under the Department of Mechanical Engineering at the University of Hong Kong. In the past six years, DBF teams from HKU have participated in various competitions around the world.
For this academic year, DBF Team will once again participate in the American Institute of Aeronautics (AIAA) Design/Build/Fly Competition and the British Model Flying Association 2022 University and Schools Flight Challenges. Teams are expected to go through the process of designing, manufacturing prototypes, testing, redesigning and competing with other international teams over the globe.
HKU DBF team has shown passion and capabilities in each of the competitions. Coming to 2023, the team is eager in maintaining high ranking by adopting revolutionary design in our flying mechanism. We get to achieve better results and strive for perfection.