Scope of Collaboration for JRI

o Research on Multimodal Big Data Analytics technologies for Smart Cities
Singapore’s Smart Nation Platform consists of three key areas:  
​• Connect: a pervasive high-speed scalable communications infrastructure,
​• Collect: real-time collection of data from a nation-wide mesh of sensors of various types,
​​• Comprehend: data analytics to generate relevant insights to enable the formulation of timely and appropriate plans and actions which result in more responsive, and even anticipatory, services for citizens.  
The research will focus on the Collect and Comprehend needs.  The challenges here include:
​• How to collect, interconnect, and analyze high velocity data steams (e.g. high definition video) from thousands and possibly millions of different sensors?
​• How to ensure that privacy is maintained as massive multi-sensor datasets are shared for various purposes?
​• How to automatically learn from such massive-scale data and develop intelligent tools that can act on them?
​• How to apply these insights to domains such as crime forensics, real-time surveillance, traffic monitoring and management, urban sustainability, etc.?
The research would include areas such as massive-scale machine learning, multi-sensor smart surveillance, multimedia forensics, video analytics, GPU-based computing, and data privacy.  This research work will be carried out via the ROSE Lab in NTU.

Click here for JRI@ROSE 

o Research on Human-centered technologies for Healthy Living and Life-long Learning
Today, our society is facing many challenges in areas such as global aging, healthcare and education. For instance, by 2025, it is estimated that one in eight of the world’s inhabitants will be over the age of 60; the national medical expenditures of both Singapore and China have been growing at more than 10% annually in the past five years; and education systems all over the world are striving for cultivating future leaders with disruptive online education more accessible than ever before.  The LILY Research Centre will pursue the following areas of collaborative research: 
​​• Healthy Ageing. Population aging is becoming an increasingly important and urgent issue for countries around the world. However, there is an insufficient of efforts in making our society elderly-friendly. This joint research will contribute to create elderly friend society by having novel designs, engineering and infrastructures that accommodate elderly’s needs. 
​​• Care in Place. The current mainstream healthcare systems are based on an institution-centred model (ICM). This model relies heavily on high cost medical staff and hospital infrastructures. Moreover, ICM is reactive and crisis-driven, i.e. a person seeks medical attention only when something is wrong. In contrast to ICM, home and community based healthcare promise to bring more cost-effectiveness, faster responsiveness and greater patient satisfaction to healthcare. With technologies developed in data science, ubiquitous sensing and Internet of services, novel homecare and community care models can be developed. We will jointly develop new care models which have the potential to fundamentally transfer our healthcare system to a new sustainable and effective paradigm.
​​​• Lifelong Learning. In recent years, advances in digital technologies have provided us with new tools for lifelong education and learning. Nowadays, online learning often complements traditional classroom learning – this is the blended learning approach. MOOCs are one of the latest trends in online education, making it easier for millions of learners to access free, high-quality university courses. However, scaling up class sizes to thousands of learners is not straightforward and involves many challenges. To address these challenges, we will develop smart artificial intelligence and educational data mining technologies that enable personalized MOOC and blended learning for lifelong learners.​​
Click here​ for JRI@LILY​


National Engineering Laboratory for Video Technology

Institute of Computer Network and Information System