Download or read book Scalable Data driven Modeling and Analytics for Smart Buildings written by Srinivasan Iyengar and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Buildings account for over 40% of the energy and 75% of the electricity usage. Thus, by reducing our energy footprint in buildings, we can improve our overall energysustainability. Further, the proliferation of networked sensors and IoT devices in recent years have enabled monitoring of buildings to provide data at various granularity. For example, smart plugs monitor appliance level usage inside the house, while solar meters monitor residential rooftop solar installations. Furthermore, smart meters record energy usage at a grid-scale. In this thesis, I argue that data-driven modeling applied to the IoT data from a smart building, at varying granularity, in association with third party data can help to understand and reduce human energy consumption. I present four data-driven modeling approaches - that use sophisticated techniques from Machine Learning, Optimization, and Time Series Analysis - applied at different granularities. First, I study IoT devices inside the house and discuss an approach called NIMD that automatically models individual electrical loads found in a household. The analytical model resulting from this approach can be used in several applications. For example, these models can improve the performance of NILM algorithms to disaggregate loads in a given household. Further, faulty or energy-inefficient appliances can be identified by observing deviations in model parameters over its lifetime. Second, I examine data from solar meters and present a machine learning framework called SolarCast to forecast energy generation from residential rooftop installations. The predictions enable exploiting the benefits of locally-generated solar energy. Third, I employ a sensorless approach utilizing a graphical model representation to report city-scale photovoltaic panel health and identify anomalies in solar energy production. Immediate identification of faults maximizes the solar investment by aiding in optimal operational performance. Finally, I focus on grid-level smart meter data and use correlations between energy usage and external weather to derive probabilistic estimates of energy, which is leveraged to identify the least efficient buildings from a large population along with the underlying cause of energy inefficiency. The identified homes can be targeted for custom energy efficiency programs.

Download or read book Enabling Scalable Smart Building Analytics written by Arka Bhattacharya and published by . This book was released on 2016 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern buildings are being integrated with myriad (often >1000s) networked sensors to improve convenience, occupant comfort accessibility and energy-efficient operations. These technological improvements hold the promise of significant advances in centralized operation and management, fault diagnosis, and integration to an emerging smart grid. As of 2012, 14% of the buildings in the U.S. deployed Building Management Systems (BMS) to provide some kind of programmatic interface to the the sensors, actuators, and historical data management. Innovations in "Internet of Things" (IoT) devices have further led to connected lights, power meters, occupancy sensors and appliances that are capable of interfacing with the underlying BMS systems used in building automation. New buildings are installed with a BMS by design, and older buildings are being continuously retrofitted with networked systems for improved efficiency. However, whether provided by novel sensor networks or legacy instrumentation, extracting meaningful information from sensor data and taking actions based on that data depends fundamentally on the metadata available to interpret it. There are more than 5 million commercial buildings in the US, with the sensors in each building set up with customized and obscure metadata. One cannot achieve scalable deployments of software analytics and applications across buildings if deploying them requires vendors and domain experts spending spending 100s of hours fixing each building. Today even well-established applications do not get deployed at scale because of this very reason. Thus, the major challenge is scalability , i.e a paradigm where an application can be written once and deployed on 100s or 1000s of buildings. This thesis evaluates the challenges with existing metadata of sensors in smart-buildings and proposes ways to normalize it to uniform standard that would allow scalable (write-once and deploy everywhere) application development. We develop three empirical criteria for successful metadata schemas -- (a) completeness, or the ability to capture all sensors, (b) ability to capture all relationships between sensors required by state-of-the-art applications, and (c) flexibility in incorporating novel sensors and applications, and usability. We empirically demonstrate that no existing smart-building sensor metadata schema satisfy these properties and develop a schema based on an underlying graphical data model, Brick, that does. We validate Brick across 6 large and diverse commercial buildings (comprising more than 17,000 sensors) in two different continents and set up by different BMS vendors. We also develop a human-in-the-loop synthesis technique which uses syntactic and data-driven steps to parse legacy metadata into a common schema. This technique allows building-experts, who might not be conversant with sophisticated regular expression programs, to parse more than 70% of the legacy metadata in a building to a common schema by providing example parses of only about 1% of the sensors. We also show how to use active perturbations of subsystems in a building to construct functional relationships between subsystems that may have been missing or incorrectly captured in legacy metadata with an accuracy of ~80%. Finally, we demonstrate the power of our normalized smart-building metadata schema paradigm by using the standardized sensor and relationship representations to implement both simple (e.g. finding errant zones, identifying inefficient air handling subsystems to save energy) and sophisticated applications (e.g finding rough occupancy estimates) that scale across real-world smart-buildings.

Download or read book Data Driven Mining Learning and Analytics for Secured Smart Cities written by Chinmay Chakraborty and published by Springer Nature. This book was released on 2021-04-28 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.

Download or read book Smart Buildings Digitalization Two Volume Set written by O.V. Gnana Swathika and published by CRC Press. This book was released on 2022-05-27 with total page 747 pages. Available in PDF, EPUB and Kindle. Book excerpt: A smart building is the state-of-art in building with features that facilitates informed decision making based on the available data through smart metering and IoT sensors. This set provides useful information for developing smart buildings including significant improvement of energy efficiency, implementation of operational improvements and targeting sustainable environment to create an effective customer experience. It includes case studies from industrial results which provide cost effective solutions and integrates the digital SCADE solution. Describes complete implication of smart buildings via industrial, commercial and community platforms Systematically defines energy-efficient buildings, employing power consumption optimization techniques with inclusion of renewable energy sources Covers data centre and cyber security with excellent data storage features for smart buildings Includes systematic and detailed strategies for building air conditioning and lighting Details smart building security propulsion. This set is aimed at graduate students, researchers and professionals in building systems, architectural, and electrical engineering.

Download or read book Smart Buildings Digitalization written by O.V. Gnana Swathika and published by CRC Press. This book was released on 2022-02-23 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various artificial intelligence and machine learning applications concerning smart buildings. It includes how renewable energy sources are integrated into smart buildings using suitable power electronic devices. The deployment of advanced technologies with monitoring, protection, and energy management features is included, along with a case study on automation. Overall, the focus is on architecture and related applications, such as power distribution, microgrids, photovoltaic systems, and renewable energy aspects. The chapters define smart building concepts and their related benefits. FEATURES Discusses various aspects of the role of the Internet of things (IoT) and machine learning in smart buildings Explains pertinent system architecture and focuses on power generation and distribution Covers power-enabling technologies for smart cities Includes photovoltaic system-integrated smart buildings This book is aimed at graduate students, researchers, and professionals in building systems engineering, architectural engineering, and electrical engineering.

Download or read book Scalable Big Data Architecture written by Bahaaldine Azarmi and published by Apress. This book was released on 2015-12-31 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.

Download or read book Data driven Analytics for Sustainable Buildings and Cities written by Xingxing Zhang and published by Springer Nature. This book was released on 2021-09-11 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.

Download or read book Real time Data Driven Model Predictive Control for Efficient Energy Consumption in Smart Buildings written by Fatma Mtibaa and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Information Networking and Applications written by Leonard Barolli and published by Springer Nature. This book was released on 2023-03-14 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations are emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low cost and high volume applications. Several of such applications have been difficult to realize because of many interconnections problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next generation wireless systems should be integrated in order to develop high performance computing solutions to problems arising from the complexities of these networks. This volume covers the theory, design and applications of computer networks, distributed computing and information systems. The aim of the volume “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.

Download or read book Data driven Multivalence in the Built Environment written by Nimish Biloria and published by Springer. This book was released on 2019-07-01 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sets the stage for understanding how the exponential escalation of digital ubiquity in the contemporary environment is being absorbed, modulated, processed and actively used for enhancing the performance of our built environment. S.M.A.R.T., in this context, is thus used as an acronym for Systems & Materials in Architectural Research and Technology, with a specific focus on interrogating the intricate relationship between information systems and associative material, cultural and socioeconomic formations within the built environment. This interrogation is deeply rooted in exploring inter-disciplinary research and design strategies involving nonlinear processes for developing meta-design systems, evidence based design solutions and methodological frameworks, some of which, are presented in this issue. Urban health and wellbeing, urban mobility and infrastructure, smart manufacturing, Interaction Design, Urban Design & Planning as well as Data Science, as prominent symbiotic domains constituting the Built Environment are represented in this first book in the S.M.A.R.T. series. The spectrum of chapters included in this volume helps in understanding the multivalence of data from a socio-technical perspective and provides insight into the methodological nuances involved in capturing, analysing and improving urban life via data driven technologies.

Download or read book 5D Building Information Modeling written by Pardis Pishdad-Bozorgi and published by . This book was released on 2021-08-03 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: 5D+ Building Information Modeling: A Data-Driven Approach to Construction Supply Chain Integration, the third book in the Practical Revolutions series, is a valuable guide for AEC professionals who want to learn more about 5D+ BIM and how implementing this technology can optimize work efficiency. Starting with a brief introduction to BIM and the history of its emerging applications, this book highlights the unleveraged power of 5D+ in addressing the inefficiencies associated with current fragmented construction supply chains. This 5D+ guide focuses on the benefits of applying the power of data-driven BIM in achieving supply chain integration today and in the foreseeable future. Architects, engineers, contractors, and owners will find an implementation roadmap that includes state-of-the-art technologies, standards, workflows, and contractual framework established to achieve an integrated construction supply chain. About the series: Practical Revolutions: Disruptive Technologies and their Applications to Building Design and Construction drives the conversation of the practical deployment of emerging technologies in the building industries. It is a central information source for building professionals seeking to advance their individual capabilities and their firm's practices. Each volume in the series will cover an emerging technology paradigm. Volumes in the series will cover: Digital Sketching; Design Automation; 5D Building Information Modeling; Construction Automation and Robotics; Building Data Modeling; and Smart Buildings and Environments.

Download or read book Smart Sustainable Cities of the Future written by Simon Elias Bibri and published by Springer. This book was released on 2018-02-24 with total page 685 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to help explore the field of smart sustainable cities in its complexity, heterogeneity, and breadth, the many faces of a topical subject of major importance for the future that encompasses so much of modern urban life in an increasingly computerized and urbanized world. Indeed, sustainable urban development is currently at the center of debate in light of several ICT visions becoming achievable and deployable computing paradigms, and shaping the way cities will evolve in the future and thus tackle complex challenges. This book integrates computer science, data science, complexity science, sustainability science, system thinking, and urban planning and design. As such, it contains innovative computer–based and data–analytic research on smart sustainable cities as complex and dynamic systems. It provides applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the underlying physical and informational landscapes. It offers contributions pertaining to the ongoing development of computer–based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to urban systems that will advance different aspects of sustainability. This book seeks to explicitly bring together the smart city and sustainable city endeavors, and to focus on big data analytics and context-aware computing specifically. In doing so, it amalgamates the design concepts and planning principles of sustainable urban forms with the novel applications of ICT of ubiquitous computing to primarily advance sustainability. Its strength lies in combining big data and context–aware technologies and their novel applications for the sheer purpose of harnessing and leveraging the disruptive and synergetic effects of ICT on forms of city planning that are required for future forms of sustainable development. This is because the effects of such technologies reinforce one another as to their efforts for transforming urban life in a sustainable way by integrating data–centric and context–aware solutions for enhancing urban systems and facilitating coordination among urban domains. This timely and comprehensive book is aimed at a wide audience across science, academia industry, and policymaking. It provides the necessary material to inform relevant research communities of the state–of–the–art research and the latest development in the area of smart sustainable urban development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of smart sustainable cities based on big data analytics and context–aware computing.

Download or read book Technological Paradigms and Digital Eras written by Giacomo Chiesa and published by Springer. This book was released on 2019-07-24 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book connects the ICT and the architectural worlds, analyzing modeling, materialization and data-driven visions for design issues at different scales. Furthermore, using sample modeling and materialization tools, it explores the links between performance-driven design approaches and the application of new digital technologies. Intended for architects and urbanists, it provides a theoretical framework to address the implications of the digital revolution in building design and operation. Furthermore, combining insights from IT and ICT with architectural and urban design know-how, it offers engineering professionals a technology-driven interpretation of the building design field.

Download or read book Artificial Intelligence in Performance Driven Design written by Narjes Abbasabadi and published by John Wiley & Sons. This book was released on 2024-05-29 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE IN PERFORMANCE-DRIVEN DESIGN A definitive, interdisciplinary reference to using artificial intelligence technology and data-driven methodologies for sustainable design Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools explores the application of artificial intelligence (AI), specifically machine learning (ML), for performance modeling within the built environment. This work develops the theoretical foundations and methodological frameworks for utilizing AI/ML, with an emphasis on multi-scale modeling encompassing energy flows, environmental quality, and human systems. The book examines relevant practices, case studies, and computational tools that harness AI’s capabilities in modeling frameworks, enhancing the efficiency, accuracy, and integration of physics-based simulation, optimization, and automation processes. Furthermore, it highlights the integration of intelligent systems and digital twins throughout the lifecycle of the built environment, to enhance our understanding and management of these complex environments. This book also: Incorporates emerging technologies into practical ideas to improve performance analysis and sustainable design Presents data-driven methodologies and technologies that integrate into modeling and design platforms Shares valuable insights and tools for developing decarbonization pathways in urban buildings Includes contributions from expert researchers and educators across a range of related fields Artificial Intelligence in Performance-Driven Design is ideal for architects, engineers, planners, and researchers involved in sustainable design and the built environment. It’s also of interest to students of architecture, building science and technology, urban design and planning, environmental engineering, and computer science and engineering.

Download or read book Predictive Maintenance in Smart Factories written by Tania Cerquitelli and published by Springer Nature. This book was released on 2021-08-26 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.

Download or read book Smart Trajectories written by Azedine Boulmakoul and published by CRC Press. This book was released on 2022-12-30 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the developments, discoveries, and practical and advanced experiences related to responsive distributed computing and how it can support the deployment of trajectory-based applications in smart systems. Smart Trajectories: Metamodeling, Reactive Architecture for Analytics and Smart Applications deals with the representation and manipulation of smart trajectories in various applications and scenarios. Presented in three parts, the book first discusses the foundation and principles for spatial information systems, complex event processing, and building a reactive architecture. Next, the book discusses modeling and architecture in relation to smart trajectory metamodeling, mining and big trajectory data, and clustering trajectories. The final section discusses advanced applications and trends in the field, including congestion trajectory analytics and real-time Big Data analytics in cloud ecosystems. Metamodeling, distributed architectures, reactive programming, Big Data analytics, NoSQL databases, connected objects, and edge-fog-cloud computing form the basis of the concepts and applications discussed. The book also presents a number of case studies to demonstrate smart trajectories related to spatiotemporal events such as traffic congestion and pedestrian accidents. This book is intended for graduate students in computer engineering, spatial databases, complex event processing, distributed systems, and geographical information systems (GIS). The book will also be useful for practicing traffic engineers, city managers, and environmental engineers interested in monitoring and security analysis.

Download or read book Smart Cities written by Houbing Song and published by John Wiley & Sons. This book was released on 2017-06-09 with total page 911 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides the foundations and principles needed for addressing the various challenges of developing smart cities Smart cities are emerging as a priority for research and development across the world. They open up significant opportunities in several areas, such as economic growth, health, wellness, energy efficiency, and transportation, to promote the sustainable development of cities. This book provides the basics of smart cities, and it examines the possible future trends of this technology. Smart Cities: Foundations, Principles, and Applications provides a systems science perspective in presenting the foundations and principles that span multiple disciplines for the development of smart cities. Divided into three parts—foundations, principles, and applications—Smart Cities addresses the various challenges and opportunities of creating smart cities and all that they have to offer. It also covers smart city theory modeling and simulation, and examines case studies of existing smart cities from all around the world. In addition, the book: Addresses how to develop a smart city and how to present the state of the art and practice of them all over the world Focuses on the foundations and principles needed for advancing the science, engineering, and technology of smart cities—including system design, system verification, real-time control and adaptation, Internet of Things, and test beds Covers applications of smart cities as they relate to smart transportation/connected vehicle (CV) and Intelligent Transportation Systems (ITS) for improved mobility, safety, and environmental protection Smart Cities: Foundations, Principles, and Applications is a welcome reference for the many researchers and professionals working on the development of smart cities and smart city-related industries.