Smart buildings and digital twin to monitoring the efficiency and wellness of working environments: a case study on IoT integration and data-driven management

Quality and efficiency of the work environment are essential to the well-being, health and productivity of employees. Despite the increasing focus on these aspects, many workplaces currently do not fully meet the needs and expectations of employees, with negative consequences for their well-being and productivity. The research aims to develop a system based on the Smart Building and Digital Twin paradigm, focusing on the implementation of various IoT components, the creation of automation flows for energy-efficient lighting, HVAC and indoor air quality control systems, and decision support through real-time data visualization enabled by user interfaces and dashboards integrating the geometric and information model (BIM). The system also aims to provide a tool for both monitoring and simulation/planning/decision support through the processing and development of machine learning (ML) algorithms. In relation to emergency management, real-time data can be acquired, allowing information to be shared with users and building managers through the creation of dashboards and visual analysis. After defining the functional requirements and identifying all3 the monitorable quantities that can be translated into requirements, the system architecture is described, the implementation of the case study is illustrated and the preliminary results of the first data collection campaign and initial estimates of future forecasts are shown.