Cognitive Buildings

Cognitive building is a pioneering topic envisioning the future of our built environment. The concept of "cognitive" provides a paradigm shift that steps from the static concept of the building as a container of human activities towards the modernist vision of "machine à habiter" of Le Corbusier, where the technological content adds the capability of learning from users' behavior and environmental variables to adapt itself to achieve major goals such as user comfort, energy-saving, flexible functionality, high durability, and good maintainability. The concept is based on digital frameworks and IoT networks towards the concept of a smart city

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements

Exploring Indoor Health: An In-depth Field Study on the Indoor Air Quality Dynamics

Indoor air pollution, a significant driver of respiratory and cardiovascular diseases, claims 3.2 million lives yearly, according to the World Health Organization, highlighting the pressing need to address this global crisis. In contrast to unconstrained outdoor environments, room structures, floor plans, ventilation systems, and occupant activities all impact the accumulation and spread of pollutants. Yet, comprehensive in-the-wild empirical studies exploring these unique indoor air pollution patterns and scope are lacking. To address this, we conducted a three-month-long field study involving over 28 indoor spaces to delve into the complexities of indoor air pollution. Our study was conducted using our custom-built DALTON air quality sensor and monitoring system, an innovative IoT air quality monitoring solution that considers cost, sensor type, accuracy, network connectivity, power, and usability. Our study also revealed that conventional measures, such as the Indoor Air Quality Index (IAQI), don't fully capture complex indoor air quality dynamics. Hence, we proposed the Healthy Home Index (HHI), a new metric considering the context and household activities, offering a more comprehensive understanding of indoor air quality. Our findings suggest that HHI provides a more accurate air quality assessment, underscoring the potential for wide-scale deployment of our indoor air quality monitoring platform.Comment: 15 pages, 19 figure

Innovative Tools and Methods Using BIM for an Efficient Renovation in Buildings

This open access book describes a BIM-based toolkit that has been developed according to the latest research activities on building information modelling and semantic interoperability to optimize the building process. It highlights the impacts of using such new tools to fast renovation activities starting from the decision-making and design stages to the construction site management with the possibility to monitor occupants' and owners’ feedback during the realization process. In this process, a framework has been developed and implemented to allow stakeholders involved in a renovation project to efficiently compile, maintain, and add data about (i) building elements, (ii) building services systems, (iii) tenants, operators, and owners of the building, and (iv) current and predicted performance of the building from the various data sources available. The framework applies and specializes the existing practices in the Semantic Web, Linked Data, and ontology domain to the management of renovation projects. It has been designed to be open so that any system which implements the required functions and uses the specified conventions will be able to achieve semantic interoperability with other framework-compliant systems in the renovation domain. Finally, this book represents the validation process of the toolkit that has been held in three demo sites: a social housing building in Italy and two private residential buildings in Poland and Finland. The outcome shows that the toolkit facilitates the renovation process with relevant reductions of time, costs, and energy consumption and that the inhabitants can take advantage of the increase in building performances, quality, and comfort

A Practical Review to Support the Implementation of Smart Solutions within Neighbourhood Building Stock

The construction industry has witnessed an increase in the use of digital tools and smart solutions, particularly in the realm of building energy automation. While realising the potential benefits of smart cities, a broader scope of smart initiatives is required to support the transition from smart buildings towards smart neighbourhoods, which are considered critical urban development units. To support the interplay of smart solutions between buildings and neighbourhoods, this study aimed to collect and review all the smart solutions presented in existing scientific articles, the technical literature, and realised European projects. These solutions were classified into two main sections, buildings and neighbourhoods, which were investigated through five domains: building-energy-related uses, renewable energy sources, water, waste, and open space management. The quantitative outcomes demonstrated the potential benefits of implementing smart solutions in areas ranging from buildings to neighbourhoods. Moreover, this research concluded that the true enhancement of energy conservation goes beyond the building’s energy components and can be genuinely achieved by integrating intelligent neighbourhood elements owing to their strong interdependencies. Future research should assess the effectiveness of these solutions in resource conservation