AAE Students MR. Chong Man Ho (1st left), Mr Yiu Cho Yin (2nd right) and Ms Lam Hok Sam (1st right) won the Outstanding Award in ASM Technology Award 2022. The group is supervised by Dr Ng Kam Hung (2nd left).
AAE students Mr CHONG Man Ho, Ms LAM Hok Sam and Mr YIU Cho Yin won the Outstanding Award in the ASM Technology Award 2022. The team was supervised by Dr NG Kam Hung. The title of their project is " Towards safe and collaborative aerodrome operations: Assessing shared situational awareness for adverse weather detection with EEG-enabled Bayesian neural networks".
The ASM Technology Award is launched by ASM Pacific Technology Limited (ASMPT) in 2015 for final year students in Hong Kong. It promotes excellent technology, and honours the best and brightest students with their outstanding final year projects on technology and innovation. Every year, five established local institutions, including The Chinese University of Hong Kong, The City University of Hong Kong, The Hong Kong Polytechnic University, The Hong Kong University of Science and Technology, and The University of Hong Kong, are invited to join the Competition by nominating two outstanding engineering Final Year Projects (FYP). The nominated teams made their impressive presentations on 30 June 2022. AAE team won the Outstanding Award and received HK$5,000 as a scholarship.
Inspired by the Tenerife airport disaster, their final year project aims to evaluate the impact of a proposed enhancement in communication protocol on cognitive workload. The team successfully developed a human-centred classification model to identify hazardous meteorological conditions using Bayesian neural network. Experiences were carried out to collect Electroencephalography (EEG) data from 30 groups of subjects in taxiing tasks under two different visibility conditions and two different communication protocols. Using the concept of explainable artificial intelligence, latent mental patterns were explored through Shapley Additive Explanations (SHAP) to reveal vital physiological indicators. The model can facilitate the decision to provide automation and decision-making aids to pilots under adverse weather conditions.
Our Department is proud of the outstanding performance of the PolyU AAE student team. Congratulations to the team!
