Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications

Jia, Mengda; Komeily, Ali; Wang, Yueren; Srinivasan, Ravi S.

doi:10.1016/j.autcon.2019.01.023

Cited by 389 publications

(230 citation statements)

References 46 publications

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“…Although several ideas related to the intelligent built environment have been introduced in the industry, some scholars argue that smart building innovation has not been successfully implemented to-date (Jia et al 2019). Batov (2015) suggests that in many cases, the intelligence of the building is confused with building automation.…”

Section: Green and Smart Buildings' Features And The Preferences Of Omentioning

confidence: 99%

“…One of the key technologies in the development of smart building is the Internet of Things (IoT). IoT may have several applications (Jia et al 2019;Stojkoska and Trivodaliev 2017): location of users and resources tracking, energy management, facility management, indoor comfort management (heating, ventilation and air conditioning (HVAC) systems), security and safety. Another feature is related to artificial intelligence, automation, analytics and big data computing.…”

Section: Green and Smart Buildings' Features And The Preferences Of Omentioning

confidence: 99%

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Smart and Green Buildings Features in the Decision-Making Hierarchy of Office Space Tenants: An Analytic Hierarchy Process Study

Głuszak

Gawlik

Zięba

2019

Administrative Sciences

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In the paper, we investigate the role of smart building or green building innovations on the Polish real estate market using the Analytic Hierarchy Process (AHP) method on the group of experts (consultants, managers, brokers) that are active on the office market in Krakow (study area). The findings point towards the highest relevance of the localisation factor, but also at the relatively low importance of the features of a sustainable building: building automation and information technology systems, as well as energy efficiency or certification. The findings suggest that despite the growing interest in sustainability and technological advancement amongst office market participants in Krakow, the relative importance of smart and green building features in their decision-making processes is relatively low. The study has some interesting practical implications. The knowledge regarding the relative importance of decision criteria can be valuable for developers and investors because the anticipation of tenants’ expectations is directly linked with return on investment and innovation premiums.

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Section: Green and Smart Buildings' Features And The Preferences Of Omentioning

confidence: 99%

Section: Green and Smart Buildings' Features And The Preferences Of Omentioning

confidence: 99%

Smart and Green Buildings Features in the Decision-Making Hierarchy of Office Space Tenants: An Analytic Hierarchy Process Study

Głuszak

Gawlik

Zięba

2019

Administrative Sciences

View full text Add to dashboard Cite

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“…In addition, the integration of BIM also blurs the level of responsibility between different team members and data and design ownership. Empirical insights into the implementation and collaborative nature of BIM construction projects are divided into (1) Information Technology capacity, (2) technology management, (3) attitude and behaviour, (4) role taking, (5) trust, (6) communication, (7) leadership and (8) learning and experience [32], where the taxonomy of BIM affects three dimensions: technology, people and process.…”

Section: Infrastructure Data and The Building Information Modelmentioning

confidence: 99%

“…In the IoT, things are objects of the physical world (physical things) that can be sensed or objects of the information world (virtual things) that can be digitalized: both are capable of being identified, integrated into information and transmitted via the sensor wired or wireless communication networks [6]. The IoT has made a significant contribution to building construction, operation and management by enabling data services, providing efficient functionalities and moving toward sustainable development goals [7]; however, the full adoption of the IoT in infrastructure still presents challenges such as the interoperability of protocols, data consistency and the amount of data to be collected, processed and stored. In addition, the integration of a BIM 3D virtual reality model with the real time uninterrupted collection of data from the IoT to control and manage infrastructure [8] provides innovative applications that improve construction and operational efficiencies.…”

Section: Introductionmentioning

confidence: 99%

Deep Reinforcement Learning Algorithms in Intelligent Infrastructure

Serrano

2019

Infrastructures

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Intelligent infrastructure, including smart cities and intelligent buildings, must learn and adapt to the variable needs and requirements of users, owners and operators in order to be future proof and to provide a return on investment based on Operational Expenditure (OPEX) and Capital Expenditure (CAPEX). To address this challenge, this article presents a biological algorithm based on neural networks and deep reinforcement learning that enables infrastructure to be intelligent by making predictions about its different variables. In addition, the proposed method makes decisions based on real time data. Intelligent infrastructure must be able to proactively monitor, protect and repair itself: this includes independent components and assets working the same way any autonomous biological organisms would. Neurons of artificial neural networks are associated with a prediction or decision layer based on a deep reinforcement learning algorithm that takes into consideration all of its previous learning. The proposed method was validated against an intelligent infrastructure dataset with outstanding results: the intelligent infrastructure was able to learn, predict and adapt to its variables, and components could make relevant decisions autonomously, emulating a living biological organism in which data flow exhaustively.

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“…Once the buildings are in operation, they experience unexpected impacting factors, including complex usage of the electrical equipment or space and staff traffic flow. Therefore, some scholars attempt to use IoT (Internet of Things) technology to collect basic environmental information of the locations of individual projects for monitoring the architectural space environment of different projects in a more precise way, even control the environmental equipment via IoT [7]. In this context, recent developments in BEMS are focusing on smart technologies to address the gap between energy consumption and occupants' comfort [8,9].…”

Section: Introductionmentioning

confidence: 99%

A Visual and Persuasive Energy Conservation System Based on BIM and IoT Technology

Liu

2019

Sensors

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Comfort level in the human body is an index that is always difficult to evaluate in a general and objective manner. Therefore, building owners and managers have been known to adjust environmental physical parameters such as temperature, humidity, and air quality based on people’s subjective sensations to yield satisfactory feelings of comfort. Furthermore, electricity consumption could be reduced by minimizing unnecessary use of heating and cooling equipment based on precise knowledge of comfort levels in interior spaces. To achieve the aforementioned objectives, this study undertook the following four tasks: first, providing visualization and smart suggestion functions to assist building managers and users in analyzing and developing plans based on the demands of space usage and electrical equipment; second, using Internet of Things technology to minimize the difference between real situations and those simulated in building information modeling (BIM); third, accurately evaluating interior environment comfort levels and improving equipment operating efficiency based on quantized comfort levels; and fourth, establishing a persuasive workflow for building energy saving systems. Through developing this system, COZyBIM will help to enhance the satisfactions of comfort level in interior space and operate energy consuming equipment efficiently, to reach the target of energy saving.

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Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications

Cited by 389 publications

References 46 publications

Smart and Green Buildings Features in the Decision-Making Hierarchy of Office Space Tenants: An Analytic Hierarchy Process Study

Smart and Green Buildings Features in the Decision-Making Hierarchy of Office Space Tenants: An Analytic Hierarchy Process Study

Deep Reinforcement Learning Algorithms in Intelligent Infrastructure

A Visual and Persuasive Energy Conservation System Based on BIM and IoT Technology

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