Smart Solutions Studio
The Smart Solutions Studio brings together like-minded students and staff who are interested in artificial intelligence (AI), edge computing, internet-of-things (IoT) systems and general automation.
Since our pilot run in 2022, the studio has worked alongside industry and technology partners across the engineering, logistics and healthcare industry to solve real world problems in which students are able to deploy and test what they have built out in the field.
We accept all students regardless of academic major. Self-proposed projects of the same theme are also welcomed.
Project supervisors:
- Mr Eugene Ee (wheee@nus.edu.sg)
- Prof Chan Tong Leong (chan.tl@nus.edu.sg)
Studio timeslot in Semester 2 AY2026/2027:
- Thursday 1 pm to 4 pm
Projects offered for CDE3301 in 2027
1. Smart ward technologies
Project partner: Alexandra Hospital
Singapore’s rapidly ageing population and ongoing healthcare manpower crunch have intensified challenges in inpatient care, particularly within subsidised wards of public hospitals, where one nurse may oversee 6-8 patients/beds within a ward cubicle. The need to maintain patient safety and care quality despite limited manpower underscores the urgency for innovative, technology-enabled solutions.
This project seeks to develop an AI-enabled vision system and intelligent agent to augment the nursing workforce in such settings. The system will leverage strategically placed video cameras to capture patient activity within the cubicle, enabling real-time monitoring of presence, movement, fall risks, and vital changes. Beyond passive monitoring, the same infrastructure can support ad-hoc teleconsultations when coupled with a bedside communication device, allowing clinicians or nurses to remotely assess patients and provide timely intervention.
Students will apply design thinking principles to co-design, prototype, and test the deployment strategy — from camera placement and privacy-preserving optics to user-interface design for alerts and remote interactions. Working closely with the Healthcare Redesign Team at Alexandra Hospital and relevant technology partners, the team will ensure the proposed solution aligns with the operational realities of subsidised wards while addressing key challenges in workforce efficiency, patient safety, and care accessibility.
2. Real-time voice translation for service industry
Project partner: Venture Corporation Ltd.
Front-facing staff in several service-related industries (hotel front desk, service staff at transit hubs, nurses to patients, etc.) often encounter situations in which they are unable to have an effective conversation with their customers due to a language barrier. Translation apps are typically used to facilitate these interactions, but they often do not allow conversations to be natural and in real time.
This project aims to enable real time conversations without the need to open an app or type on a keyboard, making the whole process more natural and seamless. The student team will explore various solutions to deploy real time voice translation onto small edge AI devices to reduce such communication barriers, allowing effortless communication between two parties.
3. AI solution to reduce errors in kitting operations
Project partner: TE Connectivity
Manual kitting (packing) is a labour intensive task that is often deployed in packing parts for a high mix, low volume environment. This process depends heavily on workers identifying, counting and packing parts across a wide variety of components which may result in errors.
This project aims to reduce these errors using AI vision solutions. Students who are keen on working on this project will be exposed to working with industrial PCs, cameras, and electronics working together with machine vision technologies to come up with a solution.
Past projects
Find My Way: app-less wayfinding solution (opens in new tab)
This project aims to improve navigation for elderly and tech-averse visitors by developing an app-less smart wayfinding system that provides personalised, real-time guidance.
VOTÉ: Vision on the Edge (opens in new tab)
In this project, we designed VOTÉ, an AI-powered edge computer vision inspection system, to enhance quality control in Top-Level Assembly by providing real-time, step-by-step assembly guidance and preventing defects through customizable, no-code model training.
w[AI]ter: voice AI ordering and personalisation
w[AI]ter achieves higher customer engagement, personalised service, and accurate real-time responses to customer queries at full-service restaurants.
Crystal Clear (opens in new tab)
Our product, Eclat, enhances the experience of wine appreciators through a hassle-free, autonomous, and reliable household product that thoroughly washes and polishes premium wine glasses.
InnoCell: accurate estimation nethod using EKF for 72V BMS in EV 2/3-wheelers (opens in new tab)
This project aims to enhance the accuracy of battery state-of-charge (SoC) and state-of-health (SoH) estimation for electric vehicles by developing a precise algorithm using Extended Kalman Filters (EKFs), targeting less than 2% margin of error.
Leak Hunter: non-invasive flow rate monitoring device for fluid pipelines
This project introduces a non-invasive device to monitor single-phase fluid flow rates in pipelines, alerting users when critical thresholds are reached for improved decision-making and operational efficiency.
VisionAI
This project aims to simplify the workflow of training and deploying AI models, specifically computer vision models to edge devices/ embedded systems.
AIoT predictive maintenance solutions for water pumps
Our project aims to design a predictive maintenance solution for water pumps utilising IoT, AI, and edge computing technologies.
Autonomous solution for blood transportation in hospital
In this project, we designed an autonomous solution to offer hospitals a streamlined and secure blood transportation solution, enhancing efficiency, saving lives in emergencies, and minimizing the reliance on manual labour.
EcoAir: IoT-enabled energy consumption monitoring in warehouses
For those managing large, cooled spaces who want higher efficiency, EcoAir provides an easy-to-install, retrofitted solution which can reduce the energy consumption of your cooling system while being significantly cheaper than hardware upgrades.
Go deep in green with Bang & Olufsen
This project aims to revolutionise the consumer electronics industry, specifically Bang & Olufsen, by designing both a sustainable packaging and an eco-friendly battery source, ensuring a greener and more environmentally responsible future for tech products.
Voice detection by bone conduction
In this project, we designed an earbud with the optimal bone conduction microphone position which aims to help users "discover their voice, amidst the noise".