AI Powered Audio Diary Analytics for Student Wellbeing Insights
VoiceSense is an AI powered audio diary analytics system that transforms short student voice reflections into actionable wellbeing insights. Through a mobile app, students record natural reflections that are transcribed, anonymised, and analysed to detect stress, motivation, emotion, and experience trends at scale. The technology offers a privacy conscious AI layer for student support, engagement analytics, and digital wellbeing solutions.
AI-Powered Crowd Management System for Optimised Flow and Enhanced User Experience
Managing crowds and optimising the flow of people in capacity-constrained environments, such as theme parks, shopping malls, convention centers, and sports arenas, can be challenging. Crowds lead to congestion, long queues, and poor user experiences if not managed effectively. Traditional crowd control systems often lack the flexibility to respond to real-time changes, making it difficult for operators to optimise the use of space and resources.
Breathing Mode Monitoring Using In-Ear Microphones
Breathing mode, whether oral or nasal, holds significance in both performance sports and sleep quality. Nasal breathing is favored during endurance activities like distance running due to its efficiency in air filtration, humidification, and warming, which enhances oxygen exchange and reduces respiratory discomfort. Nasal breathing encourages better pacing control and endurance through diaphragmatic breathing.
Web-Scale Discovery and Integration of Comparative Product Offers
Online shopping offers consumers a wide range of products from various e-commerce platforms. To compare prices, users need to search multiple sites, collect and organize data, and identify identical products. This manual process is tedious and time-consuming. Similarly, eCommerce marketplace providers, business entities, wholesalers face similar issues when sourcing products and getting their listings featured along with identical products.
Generative Pre-training Based Cooking Recipe Generation and Evaluation System
Advancements in AI have fueled a growing interest in the automatic generation of cooking recipes. With the abundance of online cooking recipes, a cutting-edge application called CulinAI—an intelligent system for recipe generation and evaluation has been developed that leverages AI to create innovative cooking recipes and instructions. CulinAI offers users two powerful modes. Firstly, instruction generation and secondly, ingredient generation from recipe.
Food Image Recognition for Asian Food
With greater emphasis on healthy living and healthier food choices, there is a need to track calorie and nutritional intake to better manage balanced diets and improve healthy lifestyle. Traditional and manual methods of identifying food types can be time-consuming and error prone. This technology aims to overcome these challenges by utilising advanced deep learning techniques for efficient and reliable food image recognition.
Wi-Fi based Indoor Positioning System
Indoor location tracking is a valuable capability for various applications, but existing solutions often require costly infrastructure investments or have limited compatibility with specific devices. There is a need for an indoor location system that works seamlessly with existing Wi-Fi infrastructure, without requiring additional costs or device-specific limitations.
Wearable-Based Consumer Activity Tracking for Eating & Retail
Researchers in healthcare and retail domains face challenges in capturing and analyzing personalized lifestyle data. Existing approaches require manual effort or extensive infrastructure deployment, resulting in inefficiency and privacy concerns. For example, tracking eating behavior relies on individuals manually uploading pictures or entering data into digital journals, while retail analysis relies on in-store cameras without customer identification.
An Intelligent (Machine Learning) AI Platform for Health and Fitness
Obesity rates have tripled since 1975 and are projected to reach 15% of the global and Singaporean population by 2024. Existing health and fitness apps have limitations, failing to make a long-term difference for users. Customers often opt out due to data input requirements, lack of personalization, and the non-motivating nature of the apps.