Abstract
A growing interest has been shown recently, concerning buildings as well as different constructions that use transformative and mobile attributes for adapting their shape, size and position in response to different environmental factors, such as humidity, temperature, wind and sunlight. Responsive architecture as it is called, can exploit climatic conditions and changes for making the most of them for the economy of energy, heating, lighting and much more. In this paper, a data warehouse has been developed for supporting and managing spatiotemporal objects such as shape-shifting constructions. Spatiotemporal data collected from these transformations are good candidates for analysis by data warehouses for decision making and business intelligence. The approach proposed in this research work is based on the integration of space and time dimensions for the management of these kinds of data. A case study is presented where a shape-shifting buildings data warehouse is developed and implemented. A number of spatiotemporal queries have been executed and their run times were compared and evaluated. The results prove the suitability of the proposed approach.
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Acknowledgments
The reported study was funded by RFBR according to the research project 19-01-246-a, 19-07-00329-a, 18-01-00402-a, 18-08-00549-a. The authors would like to thank Christos Siopis, undergraduate student from the Department of Computer Science and Engineering of the University of Thessaly, who helped with the implementation of this research work during his diploma thesis.
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Garani, G., Savvas, I.K., Chernov, A.V., Butakova, M.A. (2020). An Intelligent Data Warehouse Approach for Handling Shape-Shifting Constructions. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_27
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