A new approach to determine the reverse logistics-related issues of smart buildings focusing on sustainable architecture

Abstract

Introduction: As the disposal of materials and commodities in the management of construction projects has evolved into a critical issue, certain building materials are likely to be thrown away as rubbish at the end of a structure’s useful life. However, tearing down houses and dumping huge amounts of garbage in landfills are not the best feasible solutions to the problem. The depletion and loss of building materials on the project site are exacerbated by the significant amount of waste generated during construction. The tearing down and rebuilding of previously existing buildings are two other methods contributing to rubbish production. Trash management that is as effective as possible has become a need in light of the depletion of natural resources and raw materials, as well as the rise in the pollution brought on by waste from construction projects. One technique that might be taken to address these challenges is the implementation of concepts related to reverse logistics (RL). By considering energy management in construction utilizing sustainability and environmental criteria, this study aims to identify the inverse logistics issues of construction management and smart building. Methods: An integrated method of multi-criteria decision-making called MARCOS and ordinal priority approach (OPA) for ranking solutions and weighing criteria is presented in this study. Results: The findings indicate that out of the 23 challenges that must be overcome to implement reverse logistics effectively and achieve sustainability in the construction industry, the one with the most weight and impact on sustainability is “Workforce errors and mistakes during execution.” Discussion: out of the ten potential solutions, “determining reverse logistics as a part of a sustainability program” and “strategic collaboration with reverse logistics partners” offer the most viable options for resolving the issue and overcoming the obstacles.

PIR Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches

“…They reviewed many studies on how to count people in different places, noting the types of spaces, their sizes, and how these studies measured results. They used this information to create a system for classifying the number of occupants in their own study, as follows: [0], [1][2], [3][4], [5][6], [7][8][9], [10][11][12], [13][14][15], [16][17][18], [19][20][21][22],. .…”

Passive Infrared Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches

“…They reviewed many studies on how to count people in different places, noting the types of spaces, their sizes, and how these studies measured results. They used this information to create a system for classifying the number of occupants in their own study, as follows: [0], [1][2], [3][4], [5][6], [7][8][9], [10][11][12], [13][14][15], [16][17][18], [19][20][21][22],. .…”

“…AI integration also makes predictive maintenance easier, allowing for the early detection and resolution of possible problems to ensure the longevity and effectiveness of building systems [ 14 , 15 , 16 , 17 ]. Essentially, smart buildings offer a sustainable, efficient, and user-centric environment that combines the capabilities of the IoT and AI [ 18 , 19 ]. In smart buildings, occupancy information is critical for shaping energy consumption, optimizing HVAC and lighting systems for energy efficiency, improving occupant comfort through personalized environments, strengthening security by detecting unexpected occupancy in real time, and making design adjustments based on space utilization patterns.…”

The Main Barriers Limiting the Development of Smart Buildings

“…Regarding the "lack of qualified professionals", some authors point out as limitations the lack of knowledge about the specificities and requirements of SBs [45,46,49]; the lack of workers with adequate technical qualifications [8,27,30,33,53,61], mainly for small commercial, educational, and residential buildings; and the lack of professional training in the field of SBs [49,64], as well as labor as a factor that hinders the execution of new smart constructions [65].…”