Abstract
With recent advances in the Internet of Things (IoT), a wide variety of sensing data are disseminated, shared and utilized in smart cities to improve their efficiency and quality of life of citizens. The key is to turn sensing data into actionable information called “smart data”, used for planning, monitoring, navigation and intelligent decision making. In order to manipulate smart data, advanced data analytics is indispensable for detecting valuable events from sensing data and discovering and predicting latent associations among different kind of events. Their optimization in collaboration between a variety of observation data and application-specific data collected from users is also a crucial. In NICT Real World Information Analytics Project, an ICT platform called xData (cross-data) platform is constructed for developing smart applications with harnessing the above technologies toward realization of smart and sustainable cities. For example, association discovery from a variety of meteorological and traffic data is performed to create and distribute a map that predicts various transport disturbance risks due to heavy rain, heavy snow and other abnormal weather conditions and to navigate safe, risk-free routes.
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Zettsu, K. (2019). Transforming Sensing Data into Smart Data for Smart Sustainable Cities. In: Madria, S., Fournier-Viger, P., Chaudhary, S., Reddy, P. (eds) Big Data Analytics. BDA 2019. Lecture Notes in Computer Science(), vol 11932. Springer, Cham. https://doi.org/10.1007/978-3-030-37188-3_1
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DOI: https://doi.org/10.1007/978-3-030-37188-3_1
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