Three CDE teams did what engineers do best when faced with a challenge – rise to the occasion! They were recognised for their innovative projects submitted to the Engineering Innovation Challenge (EIC).
The EIC is a national engineering competition hosted by the Institute of Engineers Singapore that inspires students to tackle real-world challenges. Held as part of the activities around National Engineers Day, EIC 2024 hosted the highest number of participating student teams to date across four categories: Secondary School, Junior College, ITE & Polytechnic and University.
Projects submitted needed to demonstrate ideas or make innovative improvements contributing to Resilient City Living in areas such as Renewable Energy & Material, Digital Transformation, Health Innovation and Food Supply Chain.
More about the projects and the students below:
YAR: Smart Pendant – 1st runner up
YAR is a wearable pendant device that combines AI techniques such as object recognition, text recognition, and scene description. It captures surrounding audio and visual input and provides auditory feedback to help users navigate and perform daily tasks more independently. Activated by pressing a single button, the user asks a question, the pendant takes a picture, processes the query using AI, and responds. The device was developed in collaboration with the Singapore Association of the Visually Handicapped (SAVH), and user testing helped address critical use issues, making its use more intuitive.
![Sparsh using Version 1 Sparsh testing an early version of the YAR Pendant.](http://cde.nus.edu.sg/wp-content/uploads/2024/08/Sparsh-using-Version-1-1024x576.png)
“We learned a lot in terms of technical skills and soft skills like talking to users and team management. SAVH helped us narrow down a target group: older people who can easily use the device for tasks like distinguishing medicine labels, finding cans in the fridge, and picking colours while dressing.”
Team members:
- Sparsh (Computer Engineering)
- Manas Neelesh Bam (Computer Science)
Valorisation of municipal food waste into lactic acid – Merit
Driven to address the issue of food waste disposal and the high carbon costs of producing lactic acid from purpose-grown crops, this team explored the use of Singapore’s food waste in the sustainable production of lactic acid. The team’s key challenge in working on a project involving complex systems was continually revising their process flow blueprint. Selecting the appropriate solution meant revising testing principles, which involved some risk and required meticulous resource allocation planning.
![image00001 image00001](http://cde.nus.edu.sg/wp-content/uploads/2024/08/image00001-scaled.jpg)
“We were able to conduct a site visit at the waste management facility, which gave us a much better understanding of the root cause of the problem. In addition, we had much support from our professors and industry partners, which allowed us to proceed with this project.”
Team members:
- Adhvika Mohan (Chemical Engineering)
- Zhu Fangze (Environmental Engineering)
- Harini Ravichandran (Materials Science and Engineering)
- Felicia Tan (Chemical Engineering)
- Aditi Joshi (Civil Engineering)
OptiFridge: Optimised Precision Food Refrigeration and Expiry Date Intelligence – Merit
Cutting-edge technologies such as Convolutional Neural Networks (CNN) and Residual Neural Networks (ResNet), along with optical character recognition (OCR) are deployed in OptiFridge to enable accurate food recognition and freshness monitoring. Integrated recommendation algorithms powered by small language models (SLM) generate personalised recipes based on user preferences, optimising the use of existing food stored in the fridge.
![image00003 image00003](http://cde.nus.edu.sg/wp-content/uploads/2024/08/image00003-scaled.jpg)
“This journey has been challenging as we are all first-year students with limited knowledge in areas such as training an OpenCV model, artificial intelligence, and text recognition technology. Despite these challenges, we have conducted extensive research, reviewing numerous papers and summarising our findings into a comprehensive report. This process has significantly enhanced our understanding and skills, preparing us for the upcoming phases of the project.”
Team members:
- Chang Kian Yau (Physics)
- Lim Wei Jian (Electrical Engineering)
- Tong Jing Yen (Computer Engineering)
- Low Jun Jie (Electrical Engineering)
- Teh Wei Sheng (Mechanical Engineering)
Faculty members Dr Jovan Tan and Dr Elliot Law from the Innovation and Design Programme (iDP) were mentors to the teams.