The impact of IoT on LCA's primary energy indicator

Regarding data collection for Life Cycle Assessment (LCA), the traditional method remains manual, which can be complemented by exploring data in existing databases; however, this approach compromises its reliability and accuracy. It is argued that the use of new technologies, such as Building Information Modeling (BIM), the Internet of Things (IoT), and Digital Twins (DT), provides greater accuracy in LCA. This article aims to quantify the impact on the LCA primary energy indicator, distinguishing between non-renewable and renewable sources, with the support of integrating IoT into BIM and DT. Comparative analyses of energy consumption were carried out in a Case Study. The case unit was a research and teaching laboratory specializing in construction materials. IoT monitoring was done by instantiating the data in a corresponding Digital Twin, aiming for real-time visualization in a BIM model. We observed that the LCA Indicators of primary energy consumption, based on estimated data, are extremely high, approximately 528% higher in the material characterization and concrete and mortar testing environment. We highlight a potential scale of accuracy that IoT-mediated LCA data collection can achieve. We demonstrate the application of three IoT and DT theoretical frameworks in an integrated way for architecture, engineering, and construction. We exemplify how IoT will promote Construction 4.0, generating an intelligent and invisible global platform that links physical and digital entities to enable a new class of applications and services. This investigation is aligned with two critical national strategies: BIM BR and IoT.