Search

PurposeThe aim of this study is o examine the advantages and disadvantages of different existing scoring systems in the cybersecurity domain and their applicability to the AEC industry and to systematically apply a scoring system to determine scores for some of the most significant construction participants.Design/methodology/approachThis study proposes a methodology that uses the Common Vulnerability Scoring System (CVSS) to calculate scores and the likelihood of occurrence based on communication frequencies to ultimately determine risk categories for different paths in a construction network. As a proof of concept, the proposed methodology is implemented in a construction network from a real project found in the literature.FindingsResults show that the proposed methodology could provide valuable information to assist project participants to assess the overall cybersecurity vulnerability of construction and assist during the vulnerability-management processes. For example, a project owner can use this information to get a better understanding of what to do to limit its vulnerability, which will lead to the overall improvement of the security of the construction network.Research limitations/implicationsIt has to be noted that the scoring systems, the scores and categories adopted in the study need not necessarily be an exact representation of all the construction participants or networks. Therefore, caution should be exercised to avoid generalizing the results of this study.Practical implicationsThe proposed methodology can provide valuable information and assist project participants to assess the overall cyber-vulnerability of construction projects and support the vulnerability-management processes. For example, a project owner can use this approach to get a better understanding of what to do to limit its cyber-vulnerability exposure, which will ultimately lead to the overall improvement of the construction network's security. This study will also help raise more awareness about the cybersecurity implications of the digitalization and automation of the AEC industry among practitioners and construction researchers.Social implicationsGiven the amount of digitized services and tools used in the AEC industry, cybersecurity is increasingly becoming critical for society in general. In some cases, (e.g. critical infrastructure) incidents could have significant economic and societal or public safety implications. Therefore, proper consideration and action from the AEC research community and industry are needed.Originality/valueTo the authors' knowledge, this is the first attempt to measure and assess the cybersecurity of individual participants and the construction network as a whole by using the Common Vulnerability Scoring System.

The architecture, engineering, and construction (AEC) industry is increasingly becoming digital and more prone to cyber-attacks. Although there are several studies and standards in the cybersecurity domain, experts suggest that domain-specific studies need to be conducted to address the unique challenges faced within each of the different industries. Therefore, several cybersecurity studies have been undertaken for various industries, such as healthcare, manufacturing, telecommunication, and energy. However, this type of study is largely missing in the AEC industry due to different reasons, including lack of awareness. To address that, this study aims to (a) compare and analyze the number of cybersecurity-related documents in the AEC industry with several other industries, and (b) extract and analyze the cybersecurity-related documents data to identify potential future research trends and topics for the AEC community. The Web of Science (WOS) database, consisting of significant and influential journal publications, was used for document retrieval. VOSviewer was used to identify key research topics and trends in the cybersecurity domain and define future cybersecurity research in the AEC industry. WOS document retrieval results that compared the total number of publications corroborated the little to no attention received to cybersecurity investigation in the AEC industry. In addition, the VOSviewer analysis revealed three significant areas of research in the cybersecurity community that provide a reasonably justified roadmap for conducting cybersecurity research in the AEC industry. This study could greatly benefit the AEC research community and potential reaping benefits to the industry by creating more awareness among different stakeholders.

The umbrella concept for the current efforts to digitize construction is known as Construction 4.0. One of its key concepts is cyber-physical systems. The construction industry is not only creating increasingly valuable digital assets (in addition to physical ones) but also the buildings and built infrastructures are increasingly monitored and controlled using digital technology. Both make construction a vulnerable target of cyber-attacks. While the damage to digital assets, such as designs and cost calculations, may result in economic damage, attacks on digitally-controlled physical assets may damage the well-being of occupants and, in worst-case scenarios, even damage (or death) to the users. The problem is amplified by the emerging cyber-physical nature of the systems, where the human checks may be left out. We propose that construction learns from the work done in the context of critical infrastructures (CI). First, a lot of CI is construction-related, and the process of designing and building it must be secured accordingly. Second, while most assets may not be critical in the CI sense, they are critical to the operations of a business and the lives of citizens. In the end, we recommend some steps so that well-established processes of critical infrastructure protection trickle down to make Construction 4.0 and the built environment more cyber-secure. With that in mind, we describe the possible inclusion of Construction 4.0 considerations into existing critical infrastructure protection (CIP) frameworks with minimum frictions. We also propose some suggestions regarding possible future courses of action to improve the increasingly vulnerable cyber-security environment of the built environment across all life cycle phases - design, construction, operation, maintenance, and end of life.

Construction is progressively making strides towards embracing new technologies such as robotics, big data analytics, blockchain, machine learning, virtual reality, and augmented reality. The adoption of those technologies to promote automation coupled with the digitalization of the industry are the pillars of Construction 4.0 which is the construction industry’s equivalent of Industry 4.0. Experts believe that successful implementation of the same will have the ability to positively impact the whole life cycle of a construction project from project conception to the end of life phase. Particularly, researchers and practitioners suggest that robotics forms an integral part of the Construction 4.0 framework. This is mainly attributed to the numerous advantages they offer such as a) Productivity improvement: can perform tasks significantly faster without getting tired (e.g. laying bricks); b) Safety improvement: can work in harsh and unsafe environments where humans are unwilling or unable to work (e.g. gas pipe inspection); c) Cost-effectiveness: can be more economical than human counterparts (e.g. performance evaluation of existing old buildings); d) Quality improvement: can be more precise and accurate than humans (e.g. structural monitoring). Since the 1970s, several different types of robotic systems have been studied, explored, suggested, and developed for various construction-related applications. Though there exist quite a few numbers of such prototypes, robots are still not widely represented in the construction industry. This is possibly due to the highly unstructured and harsh environments of construction sites. Thus, there is still a strong need to investigate the potential of these systems. The overarching goal of this chapter is to briefly discuss the history of robotics, underlying concepts, and corresponding construction-domain specific applications. Specifically, the objectives are to a) develop a taxonomy for construction robots based on the work environment, b) discuss some of the key fundamental capabilities for construction robotic systems, and c) discuss in detail a built environment case study application for autonomous multi-sensor fused mobile robots.

Building engineers need access to real-time data to make retrofit decisions or improve the energy performance of the building occupants. Such data is typically gathered with the help of fixed wired and/or wireless sensors. Such a process consumes a significant amount of time, effort, and financial resources, particularly in existing buildings which do not have a Building Automation Systems (BAS) installed. This paper introduces a framework that uses autonomous mobile indoor robots for gathering actionable building information in real-time, and discusses how this information can be further utilized for various analyses and critical decision-making. The navigation and drift correction algorithms developed for autonomous robot operation are described in detail. Experimental results demonstrate the feasibility and applicability of the proposed method in large areas using only a sparse set of sensors mounted on mobile indoor robots. This research also developed a generic framework for making informed retrofit decisions with the help of robot collected data. A case study is performed to demonstrate the informed retrofit decision making process with the help of temperature data collected by a robot and subsequently used in an EnergyPlus simulation. Simulated annual energy savings of 3% were obtained by slightly modifying the R-values (20% to 45% improvement) of one of the external wall assemblies. These savings are expected to be larger if whole building retrofit and upgrade of material is performed. Thus, the proposed framework offers promise in improving the energy efficiency by extending the approach to other combinations of building materials (e.g. doors and windows).

Home automation involves automatic control of household features, activity and appliances. Automation system helps one’s home to promote security, comfort and convenience. This paper explains the importance of accessing modern smart home over the internet and highlights about the modern pantry system. The work explains the evolution of pantry system by using micro controllers which helps you to keep track of the quantity of commodities which is going out of stock in pantry by notifying the user through messaging service. It increases the lifestyle by solving the problem of keeping track of commodities which is going out of stock in pantry.

Digitalization and automation are making the architecture, engineering, and construction (AEC) industry more vulnerable to cyberattacks. Existing literature suggests that industry-specific studies need to be conducted. The work presented in this study shows a preliminary cybersecurity threat model relevant to the AEC industry. To that end, threat models for each of the life cycle phases are proposed. The feasibility of the proposed approach is illustrated with an example from the commissioning phase of a building, which includes an autonomous robotic system to collect data as a possible countermeasure. The suggested countermeasure shows promise to address some of the cybersecurity challenges faced in the building certification and commissioning process. The results show that the likelihood of detecting rogue sensors increases with additional constraints in the monitoring robot, such as minimum and maximum distance. The illustrative models suggest that the proposed framework will help to address the safety and cyber security of stakeholders and systems during crucial phases of construction projects.

Buildings contribute a major component of the world's total energy consumption. During the design phase, building energy simulation models can be used to predict building performance and design energy-efficient buildings that consume an optimal amount of energy, if operated and maintained within the confines of energy model assumptions. Similarly, Dynamic Data-Driven Simulation and Analysis (DDDSA) methods can be used during the operation and maintenance phase of buildings. Such methods allow models to be seeded periodically with real-time data that influences the simulation system for better analysis and prediction of system performance. In order to optimize energy consumption in buildings and subsequently improve their energy efficiency, buildings need to be monitored and various forms of copious data need to be collected to support DDDSA. The primary objective of this paper is to classify different data types that affect the energy consumption in buildings, and provide a comprehensive review of the exi...

This paper presents the process of design, development and testing of a power quality conditioner and a load management system to be integrated as a part of a small grid (Nano 3kW) system suitable for residential power needs. This set-up is being developed at the college laboratory so as to facilitate execution of various studies in the domain of integration of renewables in small distribution systems. The grid is powered by solar and wind energy sources which are synchronized. The power quality conditioner is designed to take care of power quality issues that arise due to the integration of renewable energy sources and operation of power electronic loads. A load management system capable of identifying, monitoring and controlling the loads connected to the system is also put in place using Near Field Communication(NFC) and IPv6 over Low Power Wireless Personal Area Network(6LoWPAN) technologies. The working of the power quality conditioner as well as the load management system are implemented and tested in hardware as individual stages before they become part of the grid and agreement is observed between the simulation and experimental results.

We develop an approximate analytical solution for the shape of a nonaxisymmetric sessile drop using regular perturbation methods and ignoring gravity. We assume that the pinned, contorted triple-line shape is known and is a small perturbation of the circular footprint of a spherical cap. We obtain an analytical solution using regular perturbation methods that we validate by comparing to the numerical solution of the Young-Laplace equation obtained using publicly available Surface Evolver software. In this process, we also show that the pressure inside the perturbed drop is unchanged and relate this to the curvature of the drop using the Young-Laplace equation. The rms error between the perturbation and Evolver solutions is calculated for a range of contact angles and amplitudes of triple-line perturbations. We show that the perturbation solution matches the numerical results well for a wide range of contact angles. In addition, we calculate the extent to which the drop surface is affected by triple-line contortions. We discuss the applicability of this solution to the possibility of real time hybrid experimental/computational characterization of the 3D sessile drop shapes, including obtaining local contact angle information.

This article describes the use of an improved top oil temperature rise model of a distribution transformer. The IEEE Standard C57.91-1995 model for transformer thermal calculations is discussed briefly, and a loss of life calculation based on the “10-degree rule” is formulated. This loss of life formulation is used with the improved model for top oil temperature rise to assess the impact of ambient temperature change on distribution transformer life. A probabilistic model for ambient temperature rise is used, and an increased ambient temperature of 3.5°C in 100 years is studied. Seven artifact transformers and four loading test beds are considered. The service life calculated for a base case and an increased ambient temperature case shows that there is a reduction of the order of 3–6 years for the cases studied.

Optimizing and improving energy performance of buildings while maintaining occupants’ comfort are primary goals for building managers. In order to analyze a building’s energy performance and make informed retrofit, maintenance, or operational decisions, decision-makers need access to credible real-time data illustrating how building systems are being used by its occupants at a floor and room level granularity. Traditionally, such data has been collected in buildings using wired or wireless systems by installing a dense array of sensors in every building location that needs monitoring. This is an effort and cost-prohibitive approach, especially in existing older buildings where instrumentation and integration with existing building systems is challenging. This paper introduces a novel concept of using autonomous mobile indoor robots for monitoring various occupant comfort and energy parameters inside an existing building, and discusses how the collected data can be utilized in various analyses. The research evaluates the hypothesis that a single multi-sensor fused robotic data mule that collects building energy systems performance and occupancy comfort data at sparse locations inside a building can provide decision-makers with a rich data set that is comparable in fidelity to data obtained from pre-installed and fixed sensor systems. In order to demonstrate the effectiveness of the proposed approach, an experiment was conducted using a tele-operated robot outfitted with thermal comfort data collection sensors and a localization camera in a multi-occupancy space within a large university building. The data collected by the mobile robot was statistically compared with data obtained from the building’s pre-installed Building Automation System. Experimental results demonstrated the proposed method’s promise and applicability in collecting dense actionable data in large spaces using only a sparse set of sensors mounted on mobile indoor robots.

In this paper, we study equilibrium three-dimensional shapes of drops on hysteretic surfaces. We develop a function coupled with the publicly available surface energy minimization code Surface Evolver to handle contact angle hysteresis. The function incorporates a model for the mobility of the triple line into Surface Evolver. The only inputs to the model are the advancing and receding contact angles of the surface. We demonstrate this model's versatility by studying three problems in which parts of the triple line advance while other parts either recede or remain stationary. The first problem focuses on the three-dimensional shape of a static pendant drop on a vertical surface. We predict the finite drop volume when impending sliding motion is observed. In the second problem, we examine the equilibrium shapes of coalescing sessile drops on hysteretic surfaces. Finally, we study coalescing puddles in which gravity plays a leading role in determining the equilibrium puddle shape along with hysteresis. � 2012 Springer-Verlag.

Multiobjective optimization has been applied to the problem of optimal energy management in power distribution systems. Future distribution systems with increased deployment of distributed energy storage devices and distributed energy resources are being designed under the aegis of a number of sectors of the power engineering community. This includes the National Science Foundation supported Future Renewable Electric Energy Distribution Management (FREEDM) center. A technical roadmap for the FREEDM center distribution system is proposed that is based on multiobjective optimization. Diverse objectives in the optimal control of the distribution energy management system are handled through a Pareto optimal approach. The normal boundary intersection method is used to develop a Pareto optimal front and solving the multiobjective optimization subroutine has been approached through separable programming techniques. Uncertainty in load demand and distributed resource power output are incorporated in the test cases studied to formulate a robust algorithm for distribution energy management. The paper also makes brief reference to the Smart Grid and its objectives - and how the proposed distribution energy management fits into this initiative.

Recently, the National Science Foundation (NSF) has inaugurated an Engineering Research Center dedicated to Future Renewable Electric Energy Distribution Management (FREEDM). The premise of the center is to enable the utilization of renewable resources in power distribution systems through the utilization of solid state controllers and direct digital control. The center is at an initial stage and the focus of some effort is on the development of a test bed that will allow the evaluation of alternative system configurations, controls, solid state controllers, and operations strategies. This paper describes some of those considerations and the requirements for a test bed for a future power distribution system with renewable resources.

This is a description of a panel presentation on the subject of enabling renewable energy resources in power distribution systems. The main elements of the presentation relate to: control methods; fault current management; safety considerations; improvement of system reliability; energy management; and infrastructure issues. A discussion of multiobjective management is given, and a hierarchical control infrastructure is proposed for distribution systems with renewable resources.