Intelligent human-centric lighting for mental wellbeing improvement

Dominika Cupkova, Erik Kajati, Jozef Mocnej, Peter Papcun, Jiri Koziorek and Iveta Zolotova

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 9, 1550147719875878

Abstract: In recent years, the main area of interest in the issue of influencing mental states of people is the impact of lighting on human beings, their wellbeing but also workplace productivity. This work discusses in detail the problem of positively influencing people using intelligent technologies, especially the role of the colors. We describe techniques and technologies needed to implement the case study of an intelligent lighting system. The system proposed can detect humans from an IP camera, find faces, and detect emotion. The main aim is to adjust the lights accordingly to the emotional result to improve the mood of people while taking into consideration the principles of color psychology and daytime. We have evaluated our case study solution in a real-world environment and collected the feedback from participants in the form of a questionnaire. Evaluation of participants’ wellbeing was based on their subjective statements. There were several ideas on further functionality extension which needs to be explored. Among them is including wearable devices to the proposed system, validate the emotional results according to them, but also determine the impact of an increasing number of users interacting with the system at the same time.

Keywords: Human-centric lighting; intelligent lighting; Internet of Things; wellbeing (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147719875878 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:9:p:1550147719875878

DOI: 10.1177/1550147719875878

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().