In the digital transformation era in the Architecture, Engineering, and Construction (AEC) industry, Cognitive Digital Twins (CDT) are introduced as part of the next level of process automation and control towards Construction 4.0. CDT incorporates cognitive abilities to detect complex and unpredictable actions and reason about dynamic process optimization strategies to support decision-making in building lifecycle management (BLM). Nevertheless, there is a lack of understanding of the real impact of CDT integration, Machine Learning (ML), Cyber-Physical Systems (CPS), Big Data, Artificial Intelligence (AI), and Internet of Things (IoT), all connected to self-learning hybrid models with proactive cognitive capabilities for different phases of the building asset lifecycle. This study investigates the applicability, interoperability, and integrability of an adapted model of CDT for BLM to identify and close this gap. Surveys of industry experts were performed focusing on life cycle-centric applicability, interoperability, and the CDT model’s integration in practice besides decision support capabilities and AEC industry insights. The evaluation of the adapted model of CDT model support approaching the development of CDT for process optimization and decision-making purposes, as well as integrability enablers confirms progression towards Construction 4.0.
Wood is one of the most fully renewable building materials, so wood instead of non-renewable materials produced from organic energy sources significantly reduces the environmental impact. Construction products can be replenished at the end of their working life and their elements and components deconstructed in a closed-loop manner to act as a material for potential construction. Materials passports (MPs) are instruments for incorporating circular economy principles (CEP) into structures. Material passports (MPs) consider all the building’s life cycle (BLC) steps to ensure that it can be reused and transformed several times. The number of reuse times and the operating life of the commodity greatly influence the environmental effects incorporated. For a new generation of buildings, the developing of an elegant kinetic wooden façade has become a necessity. It represents a multidisciplinary region with different climatic, fiscal, constructional materials, equipment, and programs, and ecology-influencing design processes and decisions. Based on an overview of the material’s environmental profile (MEP) and material passport (MP) definition in the design phase, this article attempts to establish and formulate an analytical analysis of the wood selection process used to produce a kinetic façade. The paper will analyze the importance of environmentally sustainable construction and a harmonious architectural environment to reduce harmful human intervention on the environment. It will examine the use of wooden panels on buildings’ façades as one solution to building impact on the environment. It will show the features of the formation of the wooden exterior of the building. It will also examine modern architecture that enters into a dialogue with the environment, giving unique flexibility to adapt a building. The study finds that new buildings can be easily created today. The concept of building materials passport and the environmental selection of the kinetic wooden façade can be incorporated into the building design process. This will improve the economic and environmental impact of the building on human life.
Lake Sapanca is the drinking water source of the Sakarya province of Turkey. Intensive urbanization in the region is the main obstacle to implementing appropriate physical planning and measures to adapt to rapid change. The monitoring of the water quality parameters in the planning and management of the lakes is significant. The Artificial Neural Network (ANN), a mathematical representation of the human brain’s functioning, was employed to estimate the Lake’s Dissolved Oxygen (DO) concentration. pH, Magnesium (Mg), Temperature (Temp), Chemical Oxygen Demand (COD), Orthophosphate (o-PO4), Nitrite Nitrogen (NO2-N), and Nitrate Nitrogen (NO3-N) were used as independent parameters. The successful ANN model gives better results compared to the traditional multiple linear regression (MLR) analysis. The developed model can be used for forecast purposes to complete the missing data in the future and support the decision process for pollution reduction through sustainable environmental management. The eutrophication threat for Lake Sapanca has been revealed. The main objective is to create the scientific infrastructure that will draw attention to the rapid urbanization problem with ANN and eutrophication models’ outputs. It has been understood that the protection of the water budget of Lake Sapanca is the primary solution method in terms of ecological sustainability to eliminate the existing pollution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.