Integration of Real-time Facial Recognition and Visualization in BIM

Yang, Chia-En; Shen, Yang-Ting; Liao, Shih-Hao

doi:10.1109/ecice50847.2020.9301999

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Generally, in these spaces, privacy for the user is not assumed, and people have grown accustomed to closed circuit cameras (CCTV) in these types of spaces for decades [33]. However, as facial recognition software improves [39], occupants are weary of cameras tracking their movements [40], not only within a space, but between spaces. In smaller public spaces, such as small office buildings and stand-alone shops, security cameras have often been utilized outside the building or in entryways but not frequently deployed within the main spaces.…”

Section: Image Detectionmentioning

confidence: 99%

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

Jacoby

Tan

Katanbaf

et al. 2021

JSAN

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Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities.

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Section: Image Detectionmentioning

confidence: 99%

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

Jacoby

Tan

Katanbaf

et al. 2021

JSAN

View full text Add to dashboard Cite

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“…For a building space involving a wide range of levels, the integration of software and hardware and the deployment of various systems, such as environmental data, the number of users, and the analysis of crowds, etc., would have a certain degree of crucial impact on building O&M. In response to such impact, this study believes that the usage status of these buildings must be actively displayed through machine learning and the application of AI technology, and such relationship of changes requires to be reflected in the O&M process. In order to solve the problem of BIM in the O&M of building facilities, this study proposes the "BIM management platform for decision-making", which is hereby referred to as "SyncBIM" [4].…”

Section: Introductionmentioning

confidence: 99%

SyncBIM: The Decision-Making BIM-Based Cloud Platform with Real-time Facial Recognition and Data Visualization

Yang¹,

Shen²,

Liao³

2021

Adv. sci. technol. eng. syst. j.

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In this research we developed an BIM-based system to monitor and visualize the real-time building users information. Concentrating on building in-use stages, advantages in tracking facial recognition should be revealed through the availability of real-time information. In this way could explore the possibility of how BIM and IoT could improve data-oriented facility management. The integration system called SyncBIM. The five system elements of the construction platform are also proposed to allow more efficient management and data transmission of the building O&M system. This study integrates the three pieces of technology respectively known as BIM platform, Internet of Things, and computer vision to explore the architecture and technology required by the building O&M system, and establishes a "Decision-Making BIM-Based Cloud Platform" to allow the opportunities of information integration and collaborative operations for the application of BIM and the introduction of computer vision technology.

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Integration of Real-time Facial Recognition and Visualization in BIM

Cited by 2 publications

References 9 publications

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

SyncBIM: The Decision-Making BIM-Based Cloud Platform with Real-time Facial Recognition and Data Visualization

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