IBM to Collaborate with Leading Singapore Institutions Using Analytics to Improve the Quality of Water, Transportation and Energy Services in a City

Economic Development Board, Land Transport Authority and IBM Establish a Research Collaboratory for Smarter Cities

SINGAPORE (December 17, 2010) – IBM (NYSE: IBM) today announced a research collaboratory in Singapore, where researchers from IBM intend to collaborate with scientists and engineers from public agencies in Singapore to improve the quality of its urban services. The focus of this research effort will be to use sensor networks to more effectively model, predict and manage the use of natural and physical infrastructure resources – water, transport and energy.  

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IBM will work with several agencies including the Economic Development Board (EDB) and the Land Transport Authority (LTA) to develop decision support tools to help Singapore more effectively manage its resources. As part of these efforts, IBM also intends to drive research collaborations with an ecosystem of research institutes and universities in Singapore.  

The collaboratory will enable world-class researchers in Singapore and IBM’s mathematical experts, renowned for applying advanced analytics to solve real-world issues, to share skills, assets, and resources to achieve common research goals.

Singapore is one of the most advanced cities with extremely high demands placed on its urban infrastructure (water, transport and energy) due to its geography, size, population and dependence on neighbors for natural resources such as water and power. The country has also been at the forefront on the global stage in rallying for liveable and sustainable cities for the future. Besides promoting a learning network through the hosting of the biennial World Cities Summit, Singapore also aims to serve as a living lab for companies to test-bed innovative solutions for densely populated, compact urban environments. The research collaboratory for smarter cities will advance this endeavor.

The collaboratory will focus on research in advanced analytics-based solutions. The understanding of water, energy and transport systems requires science-based models of resources (e.g. hydrology for water) and behavior (e.g. economic models for demand response for electricity and transport). These models need to assimilate data from sensor networks at the right scale and resolution to capture the observed events and the interaction between the different systems. Such models may be used to understand the behavior and develop policies for the management of these systems.  

“The IBM Smarter Cities Research Collaboratory will enable IBM to design, develop and test innovative urban technological solutions for global markets. By working with public agencies like LTA, IBM will be able to work on real-life urban problems to help create relevant, workable solutions,” said Dr. Beh Swan Gin, Managing Director, EDB. “We are glad that IBM has chosen Singapore to be the location for this collaboratory. It is a strong vote of confidence for Singapore, and in particular, for our Living Labs program. This investment also reflects the strong alliance that Singapore and IBM have forged over the years, an alliance that is underpinned by a shared vision where innovation is a key driver for sustainable growth.”  

One of the first projects with the LTA will focus on smarter transportation to mitigate traffic congestion. The research will build upon the work already done by IBM Research to provide traffic prediction and will aim to provide decision support analytics for improved traffic management.

“IBM is one of our research partners in the Singapore Urban Transport Solution (STARS) program which we launched in 2008 to leverage on advance technologies to develop new ideas and solutions. This includes the development of a Bus Arrival Prediction tool to help enable the delivery of more accurate bus arrival times for commuters,” said Dr. Chin Kian Keong, LTA Group Director of Transport & Ticketing Technology. “Today, we are delighted to reaffirm the alliance with both IBM and EDB. We look forward to working closely with them to develop new solutions as we continue to enhance our land transport system to ensure that our people stay connected to their goals, aspirations and lifestyles.”

The collaboratory also aims to build strong research alliances with leading universities in Singapore. It is the aim of the collaboratory to build a vibrant research community that is engaged in creating leading-edge solutions, testing them locally, and deploying them worldwide.  Initial discussions with the Nanyang Technological University (NTU) are underway to build the first such collaboration.

Other areas of potential research for the collaboratory are aimed at energy and water management and may include:

  • Distributed and mobile energy resources management including electric vehicles, storage, renewables and demand response;
  • Analytics and optimization-based techniques for managing the supply and demand of energy on a SmartGrid;
  • Building energy use forecasting and management;
  • Water quality monitoring and early event detection; and
  • Modeling energy use over the water cycle and designing control strategies.  

“At IBM Research it is important to be able to test solutions in real-world settings, outside the walls of a traditional laboratory, and the collaboratory facility in Singapore allows us to do that,” said Dr. Jayant Kalagnanam, Research Director, Research Collaboratory, IBM Singapore. “Singapore hosts a rich ecosystem of leading research institutes and universities. Our work with the LTA around traffic analytics presents a great launch pad and we plan to transfer this research to build advanced systems and solutions that will help create smarter urban systems.  This in turn will provide a reference to cities around the world on how to manage and optimize their scarce resources.”  

This is the seventh IBM collaboratory. Other worldwide IBM collaboratories are located in Dublin, Ireland; Shenyang, China; Shanghai, China; Taipei, Taiwan; Hyderabad, India and Melbourne, Australia.    

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Source: IBM

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