City geospatial dashboard: IoT and big data analytics for geospatial solutions provider in disaster management

KK Lwin, Y Sekimoto, W Takeuchi… - … on information and …, 2019 - ieeexplore.ieee.org
2019 international conference on information and communication …, 2019ieeexplore.ieee.org
Geospatial information generated from satellites, drones, and big data (mobile CDR (call
details record), GPS trajectory data, wireless sensor network, and IoT (Internet of Things))
are important to all processes in disaster management such as disaster mitigation,
preparedness, response, and mitigation. The emergence of a global navigation system and
wireless communication technology changed the way we live and how we collect geospatial
data in the field. For example, a large amount of geospatial data streams from the data …
Geospatial information generated from satellites, drones, and big data (mobile CDR (call details record), GPS trajectory data, wireless sensor network, and IoT (Internet of Things)) are important to all processes in disaster management such as disaster mitigation, preparedness, response, and mitigation. The emergence of a global navigation system and wireless communication technology changed the way we live and how we collect geospatial data in the field. For example, a large amount of geospatial data streams from the data repository as a base map in the field, and many IoT devices can collect and transmit geospatial data to IoT cloud server or centralised geodatabases. Moreover, collection, sharing and visualisation of all collected geospatial data is a crucial task for effective disaster planning and mitigation. Proper information needs to reach appropriate disaster management teams in minimal time to reduce loss of life and property. In this paper, we discuss establishment of a City Geospatial Dashboard, which can collect, share and visualise geospatial data collected from satellites, IoT devices, and other big data. We also explain geovisualisation of big data analytical results such as near-real-time rainfall profiler, hourly grid population, link population and flow direction estimated from mobile CDR, and hourly link speed computed from bus/taxi GPS trajectory data in order to improve spatial thinking and planning processes in disaster management by providing a set of spatial analysis tools known as geovisualisation.
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