The National Environment Agency (NEA) and IBM (NYSE: IBM) announced a three-year research collaboration and signed a Joint Development Agreement (JDA) under which IBM researchers will work with NEA to develop advanced modelling and predictive capabilities to address key environmental concerns in Singapore such as air quality, extreme weather events, dengue outbreaks and food poisoning incidents.
The collaboration will enable researchers from NEA and IBM's mathematical experts to harness the wide capabilities of advanced analytics including the ability to capture data in real time and turn this unstructured information into intelligence, or even predictive insight that facilitates smarter decisions. By enabling accurate forecasting, proactive measures can be taken to prevent unwanted events instead of simply reacting to events as they occur. For example, the forecasting capability will help NEA to better inform the public in advance of changes in air quality.
Leveraging real-time environmental data from NEA's environmental sensor networks, the predictive environmental capabilities to be developed under the collaboration will help NEA officers to take timely and effective action to mitigate environmental pollution and public health risks. The information gathered from the models developed under the collaboration will help other public agencies in their operations and also help the public make informed choices in their daily activities.
Specifically, NEA and IBM will work together to develop four sets of predictive models in key environmental domains in Singapore:
Through the collaboration, NEA and IBM also seek to engage with other public agencies and research ecosystem – to add to the vibrancy of the research community that is engaged in creating innovative leading-edge solutions ready to be tested and deployed, testing them locally, and deploying them worldwide.
Leveraging real-time environmental data from NEA's environmental sensor networks, the predictive environmental capabilities to be developed under the collaboration will help NEA officers to take timely and effective action to mitigate environmental pollution and public health risks. The information gathered from the models developed under the collaboration will help other public agencies in their operations and also help the public make informed choices in their daily activities.
Specifically, NEA and IBM will work together to develop four sets of predictive models in key environmental domains in Singapore:
- Air quality – Where models will be developed to forecast air quality six to 24 hours in advance on an operational basis, using real-time data streams from weather and environmental sensor networks; and to backtrack air pollution incidents to identify possible sources of the pollution. By tracing and tracking the pollution source rapidly, NEA officers can more quickly respond to the incident through targeted inspections at the likely sources of the pollution.
- Weather forecast – Where models will be developed to forecast heavy rainfall events and/or wind gust speed at a given location. This allows early warning and alerts that would help the public plan their activities.
- Dengue prediction – Where models will be developed to help predict outbreaks and to conduct scenario analysis to evaluate the efficacy of intervention policies. By predicting areas of high dengue risks and evaluating proposed prevention policies and measures, it would help enhance the effectiveness of the dengue control programme.
- Food poisoning – Where models will be developed for early event detection of food poisoning incidents by harnessing social media analytics to complement the existing inspection regime, allowing for more targeted and timely inspections based on public feedback on social media platforms.
Through the collaboration, NEA and IBM also seek to engage with other public agencies and research ecosystem – to add to the vibrancy of the research community that is engaged in creating innovative leading-edge solutions ready to be tested and deployed, testing them locally, and deploying them worldwide.
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