Abstract
The rising volume of heterogeneous data accessible at various phases of the construction process has had a significant impact on the construction industry. The availability of data is especially advantageous in the context of deep renovation, where it may significantly accelerate the decision-making process for building stock retrofit. This chapter covers Big Data and analytics in the context of deep renovation and shows how Machine Learning and Artificial Intelligence have affected the various phases of the deep renovation life cycle. It presents a review of the literature on Big Data and deep renovation and discusses a series of use cases, applications, advantages, and benefits as well as challenges and barriers. Finally, Big Data and deep renovation prospects are discussed, including future potential developments and guidelines.
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Koukaras, P., Krinidis, S., Ioannidis, D., Tjortjis, C., & Tzovaras, D. (2023). Big Data and Analytics in the Deep Renovation Life Cycle. In Palgrave Studies in Digital Business and Enabling Technologies (Vol. Part F1217, pp. 69–81). Palgrave Macmillan. https://doi.org/10.1007/978-3-031-32309-6_5
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