Automatic Estimate of Depreciated Reproduction Cost for Optimizing the Real Estate Management Through BIM
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 11622 LNCS, Page: 123-131
2019
- 2Citations
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Conference Paper Description
Building Information Modeling (BIM) can be defined synthetically as a digital model of a real estate that collects data from the different disciplines that contribute to its realization. In civil engineering, it represents an innovative approach to the construction and management of a building. Cost assessment is a fundamental activity both in the construction phase but especially in the economic management of real estate assets. The use of the BIM makes possible to carry out a rapid and precise estimate of the costs of production, reconstruction or maintenance during the entire life cycle of the building. This work aims to implement the depreciation of real estate assets within a BIM model in order to develop an easy tool to support the economic decisions of those involved in real estate asset management. In particular, the possibility of observing in real time the dynamics of depreciation of the building, placing it in relation, on the one hand, with the dynamics of the land rent and, on the other, with the costs of restoration, can become essential in the choices about times and ways of maintenance, building renovation or eventual razing. The first simulations well confirm the reasons for the research, which is placed in the same direction identified by relevant legislation aimed at the definition of the Real Estate Due Diligence and the digital dossier of the building.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85068590736&origin=inward; http://dx.doi.org/10.1007/978-3-030-24305-0_10; http://link.springer.com/10.1007/978-3-030-24305-0_10; http://link.springer.com/content/pdf/10.1007/978-3-030-24305-0_10; https://doi.org/10.1007%2F978-3-030-24305-0_10; https://dx.doi.org/10.1007/978-3-030-24305-0_10; https://link.springer.com/chapter/10.1007/978-3-030-24305-0_10
Springer Science and Business Media LLC
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