Wireless electric appliance control for smart buildings using indoor location tracking and BIM-based virtual environments

Rashid, Khandakar M.; Louis, Joseph; Fiawoyife, Kenneth Kwaku

doi:10.1016/j.autcon.2019.01.005

Cited by 57 publications

(37 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 4 summarizes the overview of the studies in Level 3 with different research domains. Nakama et al 2015, Riaz et al 2015, Tomasi et al 2015, Pasini et al 2016, Suprabhas and Dib 2017, Kang et al 2018, Sava et al 2018, Zhong et al 2018, Atazadeh et al 2019, Ignatov and Gade 2019, Rashid et al 2019, Zhao et al 2019 Indoor Thermal Comfort Chang et al 2018, Ioannou et al 2018, Pasini 2018 Space Management Fang et al 2016, Teizer et al 2017, Ferreira et al 2018, Gong et al 2018, Ha et al 2018, Asadi et al 2019, Mahmood et al 2020 Hazards…”

Section: Level 3: Integration Of Bim and Iot Techniquesmentioning

confidence: 99%

“…BIM-IoT integration has also been considered as a key feature for smart buildings. For example, Sava et al (2018) analyzed the way that digital technologies could be implemented to achieve smart buildings with the help of IoT, and Rashid et al (2019) proposed an intuitive framework that integrated IoT and BIM to control the electric fixtures for a smart building, in which the indoor position and orientation of the users could be detected using ultra-wideband (UWB) -based indoor positioning system as well as inertial measurement units (IMUs).…”

Section: Indoor Environment Monitoringmentioning

confidence: 99%

See 1 more Smart Citation

From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry

Deng¹,

Menassa²,

Kamat³

2021

ITcon

186

100

View full text Add to dashboard Cite

The widespread adoption of Building Information Modeling (BIM) and the recent emergence of Internet of Things (IoT) applications offer several new insights and decision-making capabilities throughout the life cycle of the built environment. In recent years, the ability of real-time connectivity to online sensors deployed in an environment has led to the emergence of the concept of the Digital Twin of the built environment. Digital Twins aim to achieve synchronization of the real world with a virtual platform for seamless management and control of the construction process, facility management, environment monitoring, and other life cycle processes in the built environment. However, research in Digital Twins for the built environment is still in its nascent stages and there is a need to understand the advances in the underlying enabling technologies and establish a convergent context for ongoing and future research. This paper conducted a systematic review to identify the development of the emerging technologies facilitating the evolution of BIM to Digital Twins in built environment applications. A total of 100 related papers including 23 review papers were selected and reviewed. In order to systematically classify the reviewed studies, the authors developed a five-level ladder categorization system based on the building life cycle to reflect the current state-of-the-art in Digital Twin applications. In each level of this taxonomy, applications were further categorized based on their research domains (e.g., construction process, building energy performance, indoor environment monitoring). In addition, the current state-of-art in technologies enabling Digital Twins was also summarized from the reviewed literature. It was found that most of the prior studies conducted thus far have not fully exploited or realized the envisioned concept of the Digital Twin, and thus classify under the earlier ladder categories. Based on the analysis of the reviewed work and the trends in ongoing research, the authors propose a concept of an advanced Digital Twin for building management as a baseline for further studies.

show abstract

Section: Level 3: Integration Of Bim and Iot Techniquesmentioning

confidence: 99%

Section: Indoor Environment Monitoringmentioning

confidence: 99%

From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry

Deng¹,

Menassa²,

Kamat³

2021

ITcon

186

100

View full text Add to dashboard Cite

show abstract

“…Smart BIM is used to create virtual space containing smart objects that can perform certain functions and react to user interactions based on the set of attributes of the objects. Rashid et al [80] also provides users with a smart indoor environment (Z 3 ) but does not consider the interaction between users and smart objects.…”

Section: Operation and Maintenance Phase Based On Bim (Y 3 )mentioning

confidence: 99%

Adopting Building Information Modeling (BIM) for the Development of Smart Buildings: A Review of Enabling Applications and Challenges

Yang

Han

Zeng

et al. 2021

Advances in Civil Engineering

View full text Add to dashboard Cite

The construction industry is undergoing a digital revolution due to the emergence of new technologies. A significant trend is that construction projects have been transformed and upgraded to the digital and smart mode in the whole life cycle. As a critical technology for the construction industry’s innovative development, building information modeling (BIM) is widely adopted in building design, construction, and operation. BIM has gained much interest in the research field of smart buildings in recent years. However, the dimensions of BIM and smart building applications have not been explored thoroughly so far. With an in-depth review of related journal articles published from 1996 to July 2020 on the BIM applications for smart buildings, this paper provides a comprehensive understanding and critical thinking about the nexus of BIM and smart buildings. This paper proposes a framework with three dimensions for the nexus of BIM application in smart buildings, including BIM attributes, project phases, and smart attributes. According to the three dimensions, this paper elaborates on (1) the advantages of BIM for achieving various smartness; (2) applications of BIM in multiple phases of smart buildings; and (3) smart building functions that be achieved with BIM. Based on the analysis of the literature in three dimensions, this paper presents the cross-analysis of the nexus of BIM and smart buildings. Lastly, this paper proposes the critical insights and implications about the research gaps and research trends: (1) enhancing the interoperability of BIM software; (2) further exploring the role of BIM in the operation and refurbishment phase of smart buildings; (3) paying attention to BIM technology in the field of transportation infrastructure; (4) clarifying the economic benefits of BIM projects; and (5) integrating BIM and other technologies.

show abstract

“…Traditional risk management strategies can be complemented with BIM technology to manage hazards such as automatic rule checking, knowledge based systems and reactive proactive IP based safety systems [34]: BIM could not only be utilized to support project development processes as a systematic risk management tool, but it could also provide the core data generator and platform to allow other BIM based tools to perform further risk analysis (although due to existing technical limitations and the lack of "human factor" testing, BIM based risk management has not been commonly used in real environments). A BIM model can be integrated with other IoT technologies to improve user interaction and interfaces [35]: examples include an ultrawide band (UWB) based indoor positioning system and an inertial measurement unit (IMU) that retrieves user contextual information with respect to the built environment for the control of electric appliances in a smart home. The BIM can also be applied with other manufacturing and production techniques and reverse engineering [36], which include 3D laser scanning, virtual reality, 3D printing and prefabrication for a better understanding of the design and construction process and for tools with enhanced organization and management quality that reduce defects and reworks.…”

Section: Infrastructure Data and The Building Information Modelmentioning

confidence: 99%

Deep Reinforcement Learning Algorithms in Intelligent Infrastructure

Serrano

2019

Infrastructures

View full text Add to dashboard Cite

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.

show abstract

Wireless electric appliance control for smart buildings using indoor location tracking and BIM-based virtual environments

Cited by 57 publications

References 9 publications

From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry

From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry

Adopting Building Information Modeling (BIM) for the Development of Smart Buildings: A Review of Enabling Applications and Challenges

Deep Reinforcement Learning Algorithms in Intelligent Infrastructure

Contact Info

Product

Resources

About