BIM-enabled Cognitive Computing for Smart Built Environment

Potential, Requirements, and Implementation

Ibrahim Yitmen

• Publisher: CRC Press
• Year: 2021
• Print ISBN: 9780367861834
• eBook ISBN: 9781000350975
• Edition: 1
• Topic: Computer Science
• Subtopic: Architecture Design
• Index: Computer Science

The book provides knowledge in the Building Information Model (BIM)-enabled cognitive computing methods for smart built environment involving cognitive network capabilities for smart buildings, integrating Augmented Reality/Mixed Reality in cognitive building concepts, cognitive Internet of Things (CIoT) for smart cities, Artificial Intelligence applications for cognitive cities, and cognitive smart cities using big data and machine learning. It focuses on the potential, requirements and implementation of CIoT paradigm to buildings, Artificial Intelligence techniques, reasoning, and Augmented Reality/Mixed Reality in cognitive building concepts, the concept of cognitive smart cities in its complexity, heterogeneity, and scope, and the challenge of utilizing the big data generated by smart cities from a machine learning perspective. The book comprises BIM-based and data-analytic research on cognitive IoT for smart buildings and cognitive cities using big data and machine learning as complex and dynamic systems. It presents applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the motivating physical and informational settings. It reviews ongoing development of BIM-based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to cognitive systems that will advance different aspects of future cognitive cities. The book also analyses the required material to inform pertinent research communities of the state-of-the-art research and the latest development in the area of cognitive smart cities development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of CIoT based on big data analytics and context–aware computing.

CHAPTER 1
Overview of Cyber-Physical Systems and Enabling Technologies in Cognitive Computing for Smart Built Environment

Ibrahim Yitmen¹* and Sepehr Alizadehsalehi²

¹ Department of Construction Engineering and Lighting Science, School of Engineering, Jönköping University, Gjuterigatan 5, 551 11, Jönköping, Sweden

² Project Management Program, Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA

* Corresponding author: [email protected]

1.1 Introduction

Cyber-Physical Systems (CPSs) comprising interconnected and integrated smart systems can transform the architecture, engineering, and construction (AEC) industry and contribute to the development of Construction 4.0. The built environment, being a significant constituent of the projected Construction 4.0, utilizes innovative CPS connecting smart buildings through IoT/enabled smart city network in real-time (Pardis et al., 2020). Many researchers and industry professionals envision that CPS will augment the AEC industry through connected and autonomous systems to efficiently improve communication, operation, safety, and performance. CPS applications are predicted to significantly improve the approach in construction projects that are planned, managed, built, and connected to other autonomous systems. A smart built environment provides a fully integrated and networked connectivity between virtual assets and physical assets.

A clear understanding of the requirements, processes, and characteristics of CPS is essential to make for proper and precise CPS implementation in the AEC industry. Currently, there is limited literature about CPS technologies/processes in the AEC industry. For this purpose, in this chapter, a comprehensive review regarding CPS and its different levels of architecture, CPS in the AEC industry, enabling technologies in cognitive computing (CC), and smart cities and digital technologies are presented. Overall, this study provides a thorough exploration of using CPS to solve a variety of construction project management issues effectively and efficiently. More prominently, this study provides a roadmap for future efforts to implement CPS technologies in the AEC industry to contribute to the development of Construction 4.0 besides creating a smart built environment.

1.2 Cyber-Physical Systems (CPSs)

The key technological concept of Industry 4.0 is CPSs (Borangiu et al., 2019). In the last couple of years, the importance of CPSs to optimizing industrial processes has led to a significant increase in sensitized production environments. Data collected in this context allows new intelligent solutions to support decision processes or to enable predictive actions. A CPS is a system with continuous automatic linking among the world of material and smart digital components that can sense, manage, and control the physical world (Klinc and Turk, 2019). CPSs are integrated systems that build a bi-directional link among the physical environment and cyber parts to manage methods, information, and supplies autonomously. CPSs are integrated multiple systems that create a bi-directional link among the physical environment and cyber components to manage techniques, methods, information, and supplies autonomously. They are working with different sensors, processors, and actuators, which can be monitored through computers provided with feedback loops with physical facilities.

CPSs run complex analytics through connectivity strength. Complex inference within a CPS occurs by a centralized analytic hub in which knowledge is acquired from raw data. Based on the knowledge inferred from the data and the help of the Internet of Things (IoT) control, commands are sent to the physical asset. CPS has extensive applications in medical operation, military systems, manufacturing systems, monitoring systems, traffic control and safety, and power generation. Jazdi (2014) stated that in contrast to the conventional embedded systems, created as separate devices, the emphasis of CPS of Industry 4.0 is on networking numerous devices. The IoT is a technology/system of interconnected computing and digital-based devices and machines with unique identifiers and data transferability over a network without requiring human-to-human or human-to-computer interaction. Recently, various industries have witnessed an increase in generated data in the form of structured and unstructured data from IoT-based digital devices, sensor tools, and software applications.

1.2.1 CPS 5C Level Architecture

Santos et al. (2017) describe CPSs as an augmentation of embedded systems linking the digital and physical worlds through integrating complex data processing from numerous interacted physical elements, such as people, machinery, equipment, sensors. Lee et al. (2015) stated that the main functional components of a CPS are advanced connectivity and intelligent data management, analytics, and computational capability. Based on this conceptual guideline, a 5C (Connection, Conversion, Computation, Cognition, and Configuration) architecture for application objectives was proposed (Muhuri et al., 2019). Figure 1.1 illustrates the detailed CPS 5C architecture.

Fig. 1.1: 5C architecture for implementation of CPS (adapted from Lee et al., 2015)

The proposed levels describe the architecture of a CPS from the preliminary data acquired over analytics to the ultimate value creation on five distinct levels (Lee et al., 2015):

1. The level of smart connections: Gathering precise and reliable data from different components and sections is the primary phase in developing a CPS application, which might be measured directly by sensors or acquired from manufacturing systems. It comprises ‘plug & play’ devices, independent communications, and sensor networks. Data acquiring and transmission within selected devices utilizing uniform procedures have to be as forthright as possible for this level to operate under expectations.
2. The level of data-to-information conversion: There exist services, tools, and procedures built on data stored at Level 1, that are being retrieved and utilized for predictions, correlations, statistics, and management to support decision making.
3. The cyber level: It performs as a central data hub within this pile. The primary model for this level is the Digital Twin (DT), digital representation of an object that exists or will exist in the physical world. When the data stored at the level of smart connections and analyzed at the data to information conversion level is located in the framework of the advanced data mining model, interconnections, simulations, and analytics turn out to be actual and practical.
4. The cognition level: Learning can proceed beyond and utilize artificial intelligence (AI) technologies to make progressive decisions, diagnostics, and machine learning (ML). It is presumed that a majority of information, which cannot be handled using conventional approaches, will require analyzing with machine learning as the scope and variety of data would be very big for the analysis to be processed manually by people writing algorithms.
5. The configuration level: It is the feedback from cyberspace to physical space, which functions as managerial control to make machines self-adaptive and self-configuring. This can lead to autonomous, smart, self-learned, and automatic configuration of cyber systems that can intelligently respond to environmental changes and user requirements.

Accordingly, the ever-growing use of sensors, reality capture technologies and networked machines has resulted in the continuous generation of high volume data, called Big Data. In such an environment, CPS, with all levels combined, will have a significant impact on the improvements to reach the goal of intelligent, resilient, and self-adaptable machines.

1.2.2 CPSs in AEC Industry

Various AEC researchers and industry professionals project that construction projects will be augmented by connected and autonomous systems to improve communication, operation, safety, and performance very shortly (Nunes et al., 2015; Correa, 2018). Based on the current practices in the AEC industry, CPS could be seen as one of the best technologies to solve the recurrent problems faced in the industry. Its applications predicted to significantly ameliorate the approach construction projects are planned, managed, built, and connected to other autonomous systems (Linares et al., 2019). A CPS is a bi-directional interaction among the physical components and cyber components of a system. In this process, sensors gather the physical components data. These data are then automatically transferred to cyber-components, and finally, the analyzed data are transmitted into required information through cyber processes. The necessary measures are decided and built on the earlier analysis and assessment and are transmitted back to physical components through actuators.

The built assets and construction sites are considered as the components of physical CPS, and Building Information Modeling (BIM) can be comprehended as a key CPS facilitator, demonstrating cyber counterparts and connecting them by their physical and other cyber components, comprising cloud servers and knowledge management centers (Linares et al., 2019). However, this real-time interaction is exceptionally challenging because of interoperability among the CPSs and BIM platforms (Correa and Maciel, 2018).

Some of the current applications of bi-directional CPSs in the construction industry are intelligent building systems (Zheng, 2018), smart traffic management systems (Teizer et al., 2010), and construction site safety operations (Teizer et al., 2010). Most of these applications in the construction industry are unidirectional and much the same as IoT implementations, such as the automation of recurring and basic activities, enhanced productivity, modularization, safety, and the integration of future technology tendencies that improve project outcomes. Nevertheless, the more critical issues to consider for driving CPS in the industry involve a higher level of CPSs integration, standards definition, and the advancement of the supportive technologies for CPSs. CPSs are encouraged by numerous technologies that, based on their implementation level, can be separated into two major categories:

1. The various technologies, which are known, accepted, and implemented in construction projects like BIM, reality capturing technologies, portable devices, GPS, and UAVs, are currently utilized in different construction progressions and have the potential to encourage future higher levels of CPSs implementation.
2. Trendy technologies that currently are not fully used. However, they can take CPSs applications to the next level, such as IoT, extended reality (XR) technologies (virtual reality (VR)/augmented reality (AR)/mixed reality (MR)), robotics, machine learning (ML), artificial intelligence (AI), etc.

As mentioned, there are various trendy technologies/systems for cyber applications in the AEC industry, such as IoT, fifth-generation (5G) wireless technology, XR, AI, DT, blockchain, robotization, cognitive computing (CC), and cloud computing (Chiarello et al., 2018; Erboz, 2017; Santos et al., 2017; Vaidya et al., 2018):

Internet of Things (IoT): IoT technologies are facilitating continuous interoperability and improved connectivity between the physical and cyber world with potential benefits in different applications, including smart homes, smart buildings, smart cities, and others (Faheem et al., 2018). The concept is to connect everything complex enough to be connected through the switch to the Internet and can be transmitted from the Internet. Therefore, the vital point is being equipped with smart sensors, which are sensing what is occurring around them in real-time. AEC industry has begun to use the IoT as products and services, including Information an...

Table of contents

• Cover
• Title Page
• Copyright Page
• Preface
• Acknowledgements
• About the Editor
• List of Contributors
• List of Figures
• List of Tables
• Introduction
• Contents
• 1. Overview of Cyber-Physical Systems and Enabling Technologies in Cognitive Computing for Smart Built Environment
• 2. Towards a Digital Twin-based Smart Built Environment
• 3. BIM-IoT-integrated Architectures as the Backbone of Cognitive Buildings: Current State and Future Directions
• 4. The Evolution of Building Information Model: Cognitive Technologies Integration for Digital Twin Procreation
• 5. The Integration of Building Information Modeling (BIM) and Immersive Technologies (ImTech) for Digital Twin Implementation in the AECO/FM Industry
• 6. Smart Maintenance Services for Buildings with Digital Twins and Augmented Reality
• 7. Blockchain: Technologies for Facilitating Cyber-Physical Security in Smart Built Environment
• 8. eLUX: The Case Study of Cognitive Building in the Smart Campus at the University of Brescia
• Index