Abstract
With the ever increasing observations and measurements of geo-sensor networks, satellite imageries, geo-spatial data of location based services (LBS) and location-based social networks has become a serious challenge for data management and analysis systems. In urban micro-climate, we need to deal with various types of data such as: environmental data measurements, Wi-Fi data and so on. The format and the nature of data coming from different sensors such as temperature, humidity, thermal cameras, wind sensors, and others within an urban area varies. Therefore, there is a need for a unified platform to store these data efficiently using new technologies for which, we have come up with implementation of OLAP cubes. Furthermore, additional analytics for assessing urban thermal comfort can also be derived based on behavioural patterns of people. Therefore, outdoor Wi-Fi usage statistics is used as a proxy for the amount of time people spend outdoors, to correlate outdoor thermal conditions to perceived thermal comfort. Some interesting obervations are made in our study.
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Manandhar, P., Marpu, P.R., Aung, Z. (2018). Urban Climate Data Sensing, Warehousing, and Analysis: A Case Study in the City of Abu Dhabi, United Arab Emirates. In: Woon, W., Aung, Z., Catalina Feliú, A., Madnick, S. (eds) Data Analytics for Renewable Energy Integration. Technologies, Systems and Society. DARE 2018. Lecture Notes in Computer Science(), vol 11325. Springer, Cham. https://doi.org/10.1007/978-3-030-04303-2_12
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