Our Distinguished Judges
Dr. Nur Najahatul Huda Binti Saris
Senior Lecturer, Faculty of Electrical Engineering (FKE), UTM
Ts. Dr. Jaysuman bin Pusppanathan
Senior Lecturer, Faculty of Electrical Engineering (FKE), UTM
Ts. Dr. Mohd Najeb bin Jamaludin
Senior Lecturer, Faculty of Electrical Engineering (FKE), UTM
Award Category Section
Winner Showcase
Team Name
MYRESCUE
Category
Engineering NextGen (AEN)
Award Title
Premier Award Winner
Winner Names
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Muhammad Airel Safwan Bin Azrul Azlan
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Muhammad Wafiy Haziq Bin Azmi
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Abdul Rahman Kashfi Bin Khairul Ikram
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Airiel Mariez Bin Ardy Suhaidy
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Muhammad Irfan Bin Mohd Rizal
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Muhammad Adam Danial Bin Azenan
A Child Safety Device in a Car
MyRescue is a safety device designed to prevent child fatalities in hot vehicles caused by Forgotten Baby Syndrome. It uses sensors to monitor engine status, weight, motion, and sound to detect a child’s presence. If the engine is off and at least two sensors are triggered, the system activates a buzzer and sends alerts to parents through GSM communication. The device is accurate, responsive, and powered by rechargeable batteries. It is installed behind the driver’s seat for effective detection. Future improvements include solar power and vehicle integration, with potential use in buses and taxis worldwide.
“Your device effectively addresses a critical, contemporary child safety issue in Malaysia, but an actual testing video would be very useful to prove how features like the engine-off verification function.”
“Your video presentation is very well-made and effectively captures attention right at the start, but we require more technical details to strengthen your design explanation.”
“I commend your courage to develop a solution for such a significant problem, but you need to equip yourselves with the latest technology skills to make the final product clearer.”
Team Name
AETHERINNOVATION
Category
Engineering NextGen (AEN)
Award Title
Premier Award Winner
Winner Names
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Luke Tie Hieng Zhe
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Amri Ikhsaan Yazdani
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Teoh You Le
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Kienan Pellegrino Alexcendar
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Syitarthaa Pillai
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Joel Ng Jun Xiang
An AI-Enabled System for Intelligent Waste Recognition and Automated Segregation
This project addresses rising waste generation and poor segregation by developing an AI enabled waste sorting system. It uses a webcam to capture images, which are sent to a laptop for classification into plastic, paper, or metal. A Raspberry Pi controls a rotating platform and servo mechanism to place waste into the correct compartment. The system also records disposal data and displays it on a dashboard. It is designed to be low cost and scalable. The solution can be applied in schools, workplaces, and public areas to improve recycling habits and support environmental conservation.
“I commend your project for addressing the global issue of environmental and waste management, but I recommend more training and testing to identify and sort more than just three types of waste.”
“Your clear technical explanation and strong foundational principles are excellent, but you should improve the professionalism of your video presentation, perhaps by using AI tools.”
“I admire your courage and determination to use image recognition on an advanced mini-computer, but your technical videos should have more annotations alongside the verbal explanations.”
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Universiti Teknologi Malaysia Johor Bahru
81310 UTM Johor Bahru,
Johor, Malaysia.
Email : ureka@fke.utm.my
