An integrated access control and lighting configuration system for smart buildings

Maciel, Hyuri S.; Cardoso, Isadora Bianco; Ramos, Heitor S.; Rodrigues, Joel J. P. C.; Aquino, André L. L.

doi:10.24138/jcomss.v13i2.378

Cited by 2 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mortadha et al [312] controls the lights based on face detection implemented on the camera. Maciel et al [313] implements PCA in Eigenface face recognition as authentication in smart lighting. The concept of ''space of face'' and PCA are usable in Eigenface face recognition.…”

Section: ) Computer Visionmentioning

confidence: 99%

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

et al. 2022

View full text Add to dashboard Cite

Smart lighting has become a universal smart product solution, with global revenues of up to US$5.9 billion by 2021. Six main factors drive the technology: light-emitting diode (LED) lighting, sensors, control, analytics, and intelligence. The Internet of things (IoT) concept with the end device, platform, and application layer plays an essential role in optimizing the advantages of LED lighting in the emergence of smart lighting. The ultimate aim of smart lighting research is to introduce low energy efficiency and high user comfort, where the latter is still in the infancy stage. This paper presents a systematic literature review (SLR) from a bird's eye view covering full-length research topics on smart lighting, including issues, implementation targets, technological solutions, and prospects. In addition to that, this paper also provides a detailed and extensive overview of emerging machine learning techniques as a key solution to overcome complex problems in smart lighting. A comprehensive review of improving user comfort is also presented, such as the methodology and taxonomy of activity recognition as a promising solution and user comfort metrics, including light utilization ratio, unmet comfort ratio, light to comfort ratio, power reduction rate, flickering perception, Kruithof's comfort curve, correlated color temperature, and relative mean square error. Finally, we discuss in-depth open issues and future challenges in increasing user comfort in smart lighting using activity recognition.

show abstract

Section: ) Computer Visionmentioning

confidence: 99%

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In the work "An integrated access control and lighting configuration system for smart buildings", [7] the authors H. S. Maciel, I. Cardoso, H. S. Ramos, J. J. P. C. Rodrigues, A. L. L. Aquino presented an integrated access control and lighting configuration system for smart buildings. The system uses two-factor authentication, one based on face recognition and other on RFID tag and identifies the user on the room and performs an automatic lighting configuration.…”

mentioning

confidence: 99%

Enabling Architectures and Technologies for Smart Cities

Šolić

Patrono

Perković

et al. 2017

JCOMSS

View full text Add to dashboard Cite

The vision of smart cities has became a reality. Technological advances in low power devices and reliable communication and overall system architectures made it happening. However, there are plenty of improvements that still can be employed to further increase the efficiency of relevent systems or to provide new approaches that improve exisiting solutions.This special issue on Enabling Architectures and Technologies for Smart Cities of the JOURNAL OF COMMUNICATIONS SOFTWARE AND SYSTEMS aims to report on the recent advancements and developments in various aspects related to emerging hardware and software technologies enabling the IoT, such as RFID, WSN, system software architecture, integrated solutions, embedded systems, and so on.This issue recommended totally 10 papers for publication based on the standard reviewing process, where at least two constructive reviews and with guest editors comment have been received. Papers are split in two main groups focused mainly on system architectures that improve reliability in smart cities ([1-5]), and hardware solutions ([6-10]) that are presented as either upgrades to exisiting solutions or new more efficient proposals. All of these were validated by analytics, simulations and/or testbed approaches.In the work "An IoT-aware Architecture to improve Safety in Sports Environments" [1], the authors L.

show abstract

An integrated access control and lighting configuration system for smart buildings

Cited by 2 publications

References 13 publications

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

Enabling Architectures and Technologies for Smart Cities

Contact Info

Product

Resources

About