Diploma in Information Technology Students Project “Smart Well” Wins at I-RICE’25

Four Diploma in Information Technology students from Sunway College Johor Bahru proudly brought home top honours with a Gold Award and Special Award for Best Elite Technology at the 3rd International Research, Innovation, Creativity & Engineering Project Competition 2025 (I-RICE’25).

The exceptional team behind the winning project Smart Well, Siew Zi Xiang, Daryl Foo Zhi Sheng, Nick Chong Yao Cheng and Tan Yiew Kang were ably guided by IT lecturers Mr Wilson Low and Ms Rebecca Chin. Their success proved that their innovation was on par with international expectations, proving readiness to compete at a large-scale showcase.

Organised by Southern University College (SUC) in conjunction with its 50th Anniversary celebration, I-RICE’25 brought together innovators, researchers, industry leaders, and students from across the region. The competition took place at Sutera Mall, Johor Bahru from 28 to 30 August 2025 and featured multiple elements including a poster presentation and video submission followed by an on-site presentation.

Before the on-site judging, participants were required to submit a poster and video presentation summarising their project concepts. During the final stage, teams delivered face-to-face presentations before a panel of expert judges.

The team’s project, titled “Smart Well”, is a web-based health technology platform designed to promote proactive health management. The web-based system integrates artificial intelligence (AI), computer vision and machine learning to make health monitoring accessible to everyone.

Smart Well was a stand-out for incorporating multiple health assessment tools into a single, user-friendly platform that features three key functions:

• Food Quality Assessment

  Utilises computer vision technology to analyse images of food. The AI model grades meals from A to E based on their nutritional information offering quick, easy-to-understand feedback that helps users make better dietary choices.

• Stroke Symptom Detection

  Leverages computer vision to analyse a user’s facial features and identify early signs of stroke, such as facial asymmetry. If such indicators are detected, the system immediately alerts the user to seek urgent medical attention.

• BMI Calculation

  A straightforward feature allowing users to calculate their Body Mass Index (BMI) by entering height and weight details. The system categorises results according to standard health benchmarks (e.g., underweight, normal weight, overweight, obese) and provides information on potential health risks associated with each category.

The team demonstrated an understanding of how technology can contribute to public health and well-being. Their success reflects the emphasis of the college and academics behind the programme on delivering innovation-driven education, to nurture well-rounded, future-ready young innovators.

Click the link below to watch their project presentation video:

Video Presentation