Building information modeling for facility managers

A Decision Support System (DSS) can help facility managers to improve building performance, occupants’ comfort, and energy efficiency during the Operation and Maintenance (O&M) phase. These DSSs are normally data-intensive and have specific data requirements. Building Information Modeling (BIM) has the potential to advance and transform facilities O&M by providing facility managers with a digitalized virtual environment that allows them to retrieve, analyze, and process such data. However, the implementation of BIM in O&M phases is still limited. The majority of issues in the BIM-O&M context lie in the interoperability between different software that requires different data structures and formats. In a BIM environment, there are issues associated with extracting, storing, managing, integrating, and disseminating data so that interoperability is assured. Considering the aforementioned aspects, the aim of this thesis is to enable interoperability between BIM models and the DSSs for building performance aspects such as building condition, maintenance, and occupants’ comfort. This integration automatizes the data transfer process which can assist Facility Management (FM) team in properly establishing the necessary measurements to moderate the negative consequences on buildings and thereby improve their performance and occupants’ comfort. The approach can also provide FM teams with an effective platform for data visualization in a user-friendly manner that can assist in integrating digital insights into FM decision-making processes and converting them into positive strategic actions. The proposed approach is validated in existing software as a case study. It is possible to demonstrate the applicability of this approach by ensuring that its interactions and outcomes are feasible using case studies. Case studies also identify how much the task efficiencies are in comparison with the manual method, helping facility managers to optimize operation strategies of buildings in order to enhance their performance. Verification tests are also performed on the information exported from a software program. The results demonstrate an efficiency increase in high-quality FM data collection for different kinds of DSS, reducing the time and effort that the FM team spends on searching for information and entering data. A Dynamo script is designed to allow administrators to include as much information as they wish in BIM models. Moreover, a novel approach is proposed to create a new category in BIM to assist public and business administrations with managing assets efficiently. In addition, building performance aspects can also be analyzed using the proposed method of integrating occupants' feedback into BIM models. By implementing the proposed approach, FM teams are able to correctly establish measurements which can be applied to mitigate the negative effects on buildings, thus improving their performance and enhancing their occupants’ comfort. Besides, the proposed approach enables BIM to be a more useful tool for visualization by using the most appropriate charts and formatting.Un Sistema de Soporte de decisiones (SSD) puede ayudar a los gestores de edificios a mejorar su rendimiento, su eficiencia energética y el confort de sus ocupantes. Para el buen funcionamiento de los SSD se requieren muchos datos. El Building Information Modeling (BIM) permite mejorar la gestión de las operaciones y el mantenimiento de los edificios al proporcionar un entorno virtual digitalizado que permite recuperar, analizar y procesar los datos requeridos por los SSD. Sin embargo, la implementación de BIM en las fases de Operación y Mantenimimento (O&M) aún es escasa. La mayoría de los problemas en el contexto de BIM-O&M radican en la interoperabilidad entre diferentes programas que requieren diferentes estructuras y formatos de datos. En un entorno BIM, existen problemas asociados a la extracción, el almacenamiento, la gestión, la integración y la difusión de datos para garantizar la interoperabilidad. Teniendo en cuenta los aspectos antes mencionados, el objetivo de esta tesis es facilitar la interoperabilidad entre los modelos BIM y los SSD relacionados con el rendimiento de los edificios, su estado de conservación y el confort de los ocupantes. Esta integración automatiza el proceso de transferencia de datos que puede ayudar a los gestores de edificios a establecer correctamente las medidas necesarias para mejorar su rendimiento y el confort de sus ocupantes. Esta integración también va a proporcionar a los gestores de edificios una plataforma eficaz para la visualización de datos de una manera fácil de usar que puede ayudar a integrar resultados de los SSD y convertirlos en acciones estratégicas. Para demostrar la aplicabilidad y la eficiencia de este integración, ésta se valida a través de casos de estudio. También se realizan pruebas de verificación sobre la información exportada en los diferentes sistemas. Los resultados demuestran un aumento de la eficiencia en la recopilación de datos de alta calidad para diferentes tipos de DSS, lo que reduce el tiempo y el esfuerzo que los gestores de edificios dedican a buscar información e introducir datos en la diferentes aplicaciones. Un script de Dynamo está diseñado para permitir que los gestores incluyan tanta información como deseen en los modelos BIM. Además, se propone un enfoque novedoso para crear una nueva categoría en BIM para ayudar a las administraciones públicas y empresariales a gestionar los activos de manera eficiente. Además, los aspectos del rendimiento del edificio también se pueden analizar utilizando el método propuesto de integrar los comentarios de los ocupantes en los modelos BIM. Al implementar el enfoque propuesto, los gestores de edificios pueden establecer correctamente las medidas que se pueden aplicar para mitigar los efectos negativos en los edificios, mejorando así su rendimiento y el confort de sus ocupantes. Además, la integración propuesta permite que BIM sea una herramienta más útil para la visualización mediante el uso de los gráficos y las opciones de formato más apropiados, guiando a la toma de decisiones para gestionar los edificiosPostprint (published version

Enhancing building performance : a Bayesian network model to support facility management

Premi Extraordinari de Doctorat, promoció 2018-2019. Àmbit d’Enginyeria Civil i AmbientalThe performance of existing buildings is receiving increased concern due to the need to renovate the aging building stock and provide better quality of life for end users. The conservation state of buildings and the indoor environment conditions have been related to occupants’ well-being, health, and productivity. At the same time, there is a need for more sustainable buildings with reduced energy consumption. Most challenges encountered during the analysis of the performance of existing buildings are associated with the complex relationships among the causal factors involved. The performance of a building is influenced by several factors (e.g., environmental agents, occupant behavior, operation, maintenance), which also generate uncertainties when predicting it. Most previous studies that investigate methods to assess a building’s performance do not consider the uncertainty and are often based on linear models. Although different stakeholders’ requirements regarding building performance coexist, few studies centered on the implications of these requirements. Previous studies tend to be highly specific on indicators related to a particular performance aspect, overlooking potential trade-offs that may occur between them. Therefore, a holistic and integrated approach to manage the performance of existing buildings has not been explored. Facility managers need an efficient approach to deal with uncertainty, to manage risks, and systematically identify, analyze, evaluate and mitigate factors that may impact the building performance. Taking into account the aforementioned aspects, the aim of this thesis is to devise a Bayesian network (BN) model to holistically manage the operational performance of buildings and support facility management. The proposed model consists of an integrated probabilistic approach to assess the performance of existing buildings, considering three categories: safety and elements working properly, health and comfort, and energy efficiency. The model also provides an understanding of the causality chain between multiple factors and indicators regarding building performance. The understanding of the relationships between building condition, end user comfort and building energy efficiency, supports facility managers to unwind a causal explanation for the performance results in a reasoning process. The proposed model is tested and validated using sensitivity analysis and data from existing buildings. A set of model applications are discussed, including the assessment of a building’s performance holistically, the identification of causal factors, the prediction of building performance through renovation and retrofit scenarios, and the prioritization of maintenance actions. Case studies also allow to illustrate the applicability of the model for ensuring that its interactions and outcomes are feasible. Scenario analyses provide a basis for a deeper understanding of the potential responses of the model, helping facility managers to optimize operation strategies of buildings in order to enhance its performance. The results of this thesis also include data collection methods for the inputs of the proposed BN model. A building inspection system is proposed to evaluate the technical performance of buildings, a text-mining approach is developed to analyze maintenance requests of end users, and a questionnaire is formulated to collect end-user satisfaction regarding building comfort. To conclude, this work proposes the use of Building Information Modeling (BIM) to store and access building information, which are typically disperse and not standardized in existing buildings.Actualmente, el desempeño de los edificios existentes es de gran interés debido a la necesidad de renovar el stock de edificios antiguos, proporcionando así una mejor calidad de vida a los usuarios finales. El estado de conservación de los edificios y las condiciones ambientales interiores se relacionan con el bienestar, la salud y la productividad de los ocupantes. Al mismo tiempo, existe la necesidad de edificios más sostenibles con un menor consumo energético. El desempeño de un edificio se ve afectado por varios factores (p.ej., agentes ambientales, comportamiento de los ocupantes, operación, mantenimiento, etc.). La mayoría de estos aspectos y causas muestran complejas relaciones, y consecuentemente existe una gran incertidumbre para predecirlo. Sin embargo, las investigaciones anteriores no contemplan estas relaciones causales y, a menudo, se basan en modelos lineales. Aunque el desempeño de los edificios se debe abordar teniendo en cuenta los requisitos de las diferentes partes interesadas, pocos estudios se centran en este enfoque. Los estudios anteriores tienden a analizar aspectos particulares del desempeño, ignorando las posibles relaciones que pueden ocurrir entre ellos. Los gestores de edificios deben abordar eficientemente la incertidumbre, gestionar los riesgos e identificar, analizar, evaluar y mitigar sistemáticamente los factores que pueden afectar el desempeño del edificio. Teniendo en cuenta los aspectos comentados anteriormente, el objetivo de esta tesis es desarrollar un modelo de red bayesiana (BN) para gestionar holísticamente el desempeño operativo de los edificios y apoyar su gestión. El modelo propuesto consiste en un enfoque probabilístico para evaluar el desempeño de los edificios existentes, considerando tres categorías: seguridad y funcionalidad, salud y confort, y eficiencia energética. El modelo también proporciona una interpretación de la cadena de causalidad entre los múltiples factores e indicadores relacionados con el desempeño del edificio. El análisis de las relaciones entre los diferentes aspectos del desempeño de los edificios (estado de conservación del edificio, el confort del usuario final y la eficiencia energética del edificio) va a permitir explicar y entender sus factores causales y va a posibilitar mejorar la gestión de estos edificios. La verificación del modelo propuesto se lleva a cabo mediante análisis de sensibilidad y datos de edificios existentes. Las aplicaciones del modelo incluyen: la evaluación del desempeño de edificios de forma integrada; la identificación de factores causales; la predicción del desempeño de los edificios a través de escenarios de renovación y modernización; y la priorización de las acciones de mantenimiento. La implementación del modelo en diversos casos de estudio permite ilustrar su aplicabilidad y validar su uso. Los resultados de esta tesis también incluyen métodos de recogida de datos para las variables del modelo propuesto. De hecho, se propone un sistema de inspección de edificios para evaluar el desempeño técnico de los edificios, se desarrolla un sistema de text mining para analizar las solicitudes de mantenimiento de los usuarios finales y se formula un cuestionario para recoger la satisfacción de los usuarios finales en relación a los espacios de los edificios en los que interactúan. Para concluir, este trabajo propone el uso del Building Information Modeling (BIM) para almacenar y acceder a la información necesaria para el modelo.Postprint (published version

Enhancing building performance : a Bayesian network model to support facility management

The performance of existing buildings is receiving increased concern due to the need to renovate the aging building stock and provide better quality of life for end users. The conservation state of buildings and the indoor environment conditions have been related to occupants’ well-being, health, and productivity. At the same time, there is a need for more sustainable buildings with reduced energy consumption. Most challenges encountered during the analysis of the performance of existing buildings are associated with the complex relationships among the causal factors involved. The performance of a building is influenced by several factors (e.g., environmental agents, occupant behavior, operation, maintenance), which also generate uncertainties when predicting it. Most previous studies that investigate methods to assess a building’s performance do not consider the uncertainty and are often based on linear models. Although different stakeholders’ requirements regarding building performance coexist, few studies centered on the implications of these requirements. Previous studies tend to be highly specific on indicators related to a particular performance aspect, overlooking potential trade-offs that may occur between them. Therefore, a holistic and integrated approach to manage the performance of existing buildings has not been explored. Facility managers need an efficient approach to deal with uncertainty, to manage risks, and systematically identify, analyze, evaluate and mitigate factors that may impact the building performance. Taking into account the aforementioned aspects, the aim of this thesis is to devise a Bayesian network (BN) model to holistically manage the operational performance of buildings and support facility management. The proposed model consists of an integrated probabilistic approach to assess the performance of existing buildings, considering three categories: safety and elements working properly, health and comfort, and energy efficiency. The model also provides an understanding of the causality chain between multiple factors and indicators regarding building performance. The understanding of the relationships between building condition, end user comfort and building energy efficiency, supports facility managers to unwind a causal explanation for the performance results in a reasoning process. The proposed model is tested and validated using sensitivity analysis and data from existing buildings. A set of model applications are discussed, including the assessment of a building’s performance holistically, the identification of causal factors, the prediction of building performance through renovation and retrofit scenarios, and the prioritization of maintenance actions. Case studies also allow to illustrate the applicability of the model for ensuring that its interactions and outcomes are feasible. Scenario analyses provide a basis for a deeper understanding of the potential responses of the model, helping facility managers to optimize operation strategies of buildings in order to enhance its performance. The results of this thesis also include data collection methods for the inputs of the proposed BN model. A building inspection system is proposed to evaluate the technical performance of buildings, a text-mining approach is developed to analyze maintenance requests of end users, and a questionnaire is formulated to collect end-user satisfaction regarding building comfort. To conclude, this work proposes the use of Building Information Modeling (BIM) to store and access building information, which are typically disperse and not standardized in existing buildings.Actualmente, el desempeño de los edificios existentes es de gran interés debido a la necesidad de renovar el stock de edificios antiguos, proporcionando así una mejor calidad de vida a los usuarios finales. El estado de conservación de los edificios y las condiciones ambientales interiores se relacionan con el bienestar, la salud y la productividad de los ocupantes. Al mismo tiempo, existe la necesidad de edificios más sostenibles con un menor consumo energético. El desempeño de un edificio se ve afectado por varios factores (p.ej., agentes ambientales, comportamiento de los ocupantes, operación, mantenimiento, etc.). La mayoría de estos aspectos y causas muestran complejas relaciones, y consecuentemente existe una gran incertidumbre para predecirlo. Sin embargo, las investigaciones anteriores no contemplan estas relaciones causales y, a menudo, se basan en modelos lineales. Aunque el desempeño de los edificios se debe abordar teniendo en cuenta los requisitos de las diferentes partes interesadas, pocos estudios se centran en este enfoque. Los estudios anteriores tienden a analizar aspectos particulares del desempeño, ignorando las posibles relaciones que pueden ocurrir entre ellos. Los gestores de edificios deben abordar eficientemente la incertidumbre, gestionar los riesgos e identificar, analizar, evaluar y mitigar sistemáticamente los factores que pueden afectar el desempeño del edificio. Teniendo en cuenta los aspectos comentados anteriormente, el objetivo de esta tesis es desarrollar un modelo de red bayesiana (BN) para gestionar holísticamente el desempeño operativo de los edificios y apoyar su gestión. El modelo propuesto consiste en un enfoque probabilístico para evaluar el desempeño de los edificios existentes, considerando tres categorías: seguridad y funcionalidad, salud y confort, y eficiencia energética. El modelo también proporciona una interpretación de la cadena de causalidad entre los múltiples factores e indicadores relacionados con el desempeño del edificio. El análisis de las relaciones entre los diferentes aspectos del desempeño de los edificios (estado de conservación del edificio, el confort del usuario final y la eficiencia energética del edificio) va a permitir explicar y entender sus factores causales y va a posibilitar mejorar la gestión de estos edificios. La verificación del modelo propuesto se lleva a cabo mediante análisis de sensibilidad y datos de edificios existentes. Las aplicaciones del modelo incluyen: la evaluación del desempeño de edificios de forma integrada; la identificación de factores causales; la predicción del desempeño de los edificios a través de escenarios de renovación y modernización; y la priorización de las acciones de mantenimiento. La implementación del modelo en diversos casos de estudio permite ilustrar su aplicabilidad y validar su uso. Los resultados de esta tesis también incluyen métodos de recogida de datos para las variables del modelo propuesto. De hecho, se propone un sistema de inspección de edificios para evaluar el desempeño técnico de los edificios, se desarrolla un sistema de text mining para analizar las solicitudes de mantenimiento de los usuarios finales y se formula un cuestionario para recoger la satisfacción de los usuarios finales en relación a los espacios de los edificios en los que interactúan. Para concluir, este trabajo propone el uso del Building Information Modeling (BIM) para almacenar y acceder a la información necesaria para el modelo

Model Predictive Control of HVAC Systems: Design and Implementation on a Real Case Study

The final aim of this work is to design, implement and test a controller on a real testbed kindly provided by KTH. The control paradigm presented in this thesis is a MPC that aims at saving energy as well as keeping the temperature and the CO2 concentration in a comfort range that guarantees the wellness of room occupants. To improve the knowledge of the plant, we also study the problem of modeling both the dynamics of of the system to be controlled and of the dedicated actuation syste

Improved multi-user interaction in a smart environment through a preference-based conflict resolution virtual assistant

In this work we will examine and develop a system that can assist people in Activities of Daily Life (ADL). This study focuses on resolving conflicts for the requests from different users’ profiles, for instance - elderly, adult and young. The objective of the system is to present a dialogue manager which is able to detect multi-user semantic conflict and to resolve the conflict for improved dialogue informing about its decisions using a system interface Avatar. The system is also able to prioritize requests that occurred among the services of multiple home appliances, as well as to deal with conflicting entities involving a single device. We investigated whether the multi-user context awareness by a Virtual Assistant adds value to the Smart Home concept in recognizing multi-user conflicts dynamically. This work has proposed a preference based method for resolving conflict and evaluated the developed system in a smart home environmen

Impact of Occupant Behaviour (OB) on building energy use and thermal comfort: From stochastic modelling and occupant profiling to interdisciplinary user engagement

L'abstract è presente nell'allegato / the abstract is in the attachmen

Improved multi-user interaction in a smart environment through a preference-based conflict resolution virtual assistant

In this work we will examine and develop a system that can assist people in Activities of Daily Life (ADL). This study focuses on resolving conflicts for the requests from different users’ profiles, for instance - elderly, adult and young. The objective of the system is to present a dialogue manager which is able to detect multi-user semantic conflict and to resolve the conflict for improved dialogue informing about its decisions using a system interface Avatar. The system is also able to prioritize requests that occurred among the services of multiple home appliances, as well as to deal with conflicting entities involving a single device. We investigated whether the multi-user context awareness by a Virtual Assistant adds value to the Smart Home concept in recognizing multi-user conflicts dynamically. This work has proposed a preference based method for resolving conflict and evaluated the developed system in a smart home environmen

BIM-based decision support for building condition assessment

Building condition assessment requires the integration of various types of data such as building characteristics, the properties of elements/systems and maintenance records. Previous research has focused on identifying these data and developing a building condition risk assessment model based on Bayesian networks (BN). However, due to interoperability issues, the process of transferring the data is performed manually, which requires considerable time and effort. To address this issue, this paper presents a data model to integrate the building condition risk assessment model into BIM. The proposed data model is implemented in existing software as a case study and tested and evaluated on three scenarios. Addressing interoperability will leverage the BIM tool as a data re- pository to automate the data transfer process and improve its consistency and reliability. It will also enable BIM to be a more effective tool for building condition and causality analysis visualization.This work was supported by Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) from Generalitat de Catalunya under Grant 2019 FI_B00064Postprint (published version

A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE

L’Ambient Intelligence (AmI) è caratterizzata dall’uso di sistemi pervasivi per monitorare l’ambiente e modificarlo secondo le esigenze degli utenti e rispettando vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti come la scalabilità e la trasparenza per l’utente. Una tecnologia che consente di raggiungere questi obiettivi è rappresentata dalle reti di sensori wireless (WSN), caratterizzate da bassi costi e bassa intrusività. Tuttavia, sebbene in grado di effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacità di elaborazione necessarie a supportare un sistema intelligente; d’altra parte senza questa attività di pre-elaborazione la mole di dati sensoriali può facilmente sopraffare un sistema centralizzato con un’eccessiva quantità di dettagli superflui. Questo lavoro presenta un’architettura cognitiva in grado di percepire e controllare l’ambiente di cui fa parte, basata su un nuovo approccio per l’estrazione di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione. Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacità computazionali vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire ad un sistema centralizzato intelligente di effettuare ragionamenti di alto livello. L’architettura proposta è stata utilizzata per sviluppare un testbed dotato degli strumenti hardware e software necessari allo sviluppo e alla gestione di applicazioni di AmI basate su WSN, il cui obiettivo principale sia il risparmio energetico. Per fare in modo che le applicazioni di AmI siano in grado di comunicare con il mondo esterno in maniera affidabile, per richiedere servizi ad agenti esterni, l’architettura è stata arricchita con un protocollo di gestione distribuita della reputazione. È stata inoltre sviluppata un’applicazione di esempio che sfrutta le caratteristiche del testbed, con l’obiettivo di controllare la temperatura in un ambiente lavorativo. Quest’applicazione rileva la presenza dell’utente attraverso un modulo per la fusione di dati multi-sensoriali basato su reti bayesiane, e sfrutta questa informazione in un controllore fuzzy multi-obiettivo che controlla gli attuatori sulla base delle preferenze dell’utente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive equipments for monitoring and modifying the environment according to users’ needs, and to globally defined constraints. Furthermore, such systems cannot ignore requirements about ubiquity, scalability, and transparency to the user. An enabling technology capable of accomplishing these goals is represented by Wireless Sensor Networks (WSNs), characterized by low-costs and unintrusiveness. However, although provided of in-network processing capabilities, WSNs do not exhibit processing features able to support comprehensive intelligent systems; on the other hand, without this pre-processing activities the wealth of sensory data may easily overwhelm a centralized AmI system, clogging it with superfluous details. This work proposes a cognitive architecture able to perceive, decide upon, and control the environment of which the system is part, based on a new approach to knowledge extraction from raw data, that addresses this issue at different abstraction levels. WSNs are used as the pervasive sensory tool, and their computational capabilities are exploited to remotely perform preliminary data processing. A central intelligent unit subsequently extracts higher-level concepts in order to carry on symbolic reasoning. The aim of the reasoning is to plan a sequence of actions that will lead the environment to a state as close as possible to the users’ desires, taking into account both implicit and explicit feedbacks from the users, while considering global system-driven goals, such as energy saving. The proposed conceptual architecture was exploited to develop a testbed providing the hardware and software tools for the development and management of AmI applications based on WSNs, whose main goal is energy saving for global sustainability. In order to make the AmI system able to communicate with the external world in a reliable way, when some services are required to external agents, the architecture was enriched with a distributed reputation management protocol. A sample application exploiting the testbed features was implemented for addressing temperature control in a work environment. Knowledge about the user’s presence is obtained through a multi-sensor data fusion module based on Bayesian networks, and this information is exploited by a multi-objective fuzzy controller that operates on actuators taking into account users’ preference and energy consumption constraints