Big Data

Singapore continues to expand its capabilities in data and analytics. The knowledge created enables us to deal with priority issues such as healthcare and underpin our development towards being a Smart Nation and a regional analytics hub.

 

Internet of Things (IoT)

  • Pervasive, low-power, self-sustainable sensing, networks, actuating technologies, and applications for smart city, buildings and transportation.
  • Internet for serving general public, but with special emphasis on people with special needs (e.g., elderly, minors, and disabilities).
  • Research in real-time big data and multimedia analytics.
  • Cyber-physical system security.
  • Vehicular technologies or smart transportation.
  • Physical analytics beyond big data.


Achievement

  • Developed a non-GPS localisation technique to identify object’s locations for urban environments.
  • Developed indoor localisation service.
  • Implemented indoor energy harvesting for supporting sensing, networking, and actuating.
  • Successfully developed co-existence mechanisms for massive wireless devices.
  • Implemented crowd-sensing system development from both technological and social aspects.
  • Launched environmental monitoring with low cost sensing infrastructure.

Visual Analytics

  • New approaches and technologies for fast and rich mobile object search with constrained network and computational resources, compact and innovative feature coding, scalable indexing and search algorithms.
  • Large-scale image/video classification and search.
  • Large-scale 3D scene understanding and search.
  • Face recognition and retrieval, especially in social media contexts.
  • Deep learning for large-scale imagerecognition and search.
  • Semantic image segmentation and co-segmentation.
  • Large-scale image/multi-object search.
  • Cloud-based solution, fine-grained classification and retriveval

Cloud Computing

  • Emerging applications and use cases over cloud platform.
  • Cloud resource management and service orchestration via advanced optimisation algorithms.
  • Critical infrastructure (e.g. green data centre) for cloud computing and its enabling technologies (software-defined systems, new hardware, etc).
  • Real-time data analytics in the cloud.
  • Hardware accelerated heterogeneous cloud infrastructure.
  • Energy efficient cloud infrastructure.

 
Achievement

  • HPC cloud and its support for scientific computing: developed transformation-based monetary cost optimisations for scientific workflows.
  • Energy saving: leveraged smart power management and renewable energy to reduce the carbon footprint of cloud computing.