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LightCloud: Future of Dynamic Lighting in the Shared Space

Conference paper
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Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1290)

Abstract

Lighting conditions in an indoor environment have been shown to affect our cognition and behaviors in a variety of ways. On average, we spend 90% of our time in indoor environments. These usually involve multiple people with diverse environmental needs sharing a space with the same lighting conditions. Additionally, besides providing us with better illumination for practical and aesthetic effects, the way we use and interact with light has not changed. To address this, we present LightCloud, a lighting system that enables each user to create and control their own dynamic light source in a shared enclosed space for enhancing social interactions and work experience. The advances in smart lighting and novel distributed system architecture will further enable novel multi-user dynamic lighting. This paper aims to provide a look into the applications of dynamic lighting between multiple users in a shared environment.

Keywords

Social interactive lighting Multi-user lighting Ubiquitous computing Smart lighting Ambient intelligence Context-aware pervasive systems 

References

  1. 1.
    Alkozei, A., Smith, R., Dailey, N.S., Bajaj, S., Killgore, W.D.S.: Acute exposure to blue wavelength light during memory consolidation improves verbal memory performance. PLoS ONE 12(9), e0184884 (2017)CrossRefGoogle Scholar
  2. 2.
    Boyce, P.R., Veitch, J.A., Newsham, G.R., Jones, C.C., Heerwagen, J., Myer, M., Hunter, C.M.: Lighting quality and office work: two field simulation experiments. Light. Res. Technol. 38(3), 191–223 (2006)CrossRefGoogle Scholar
  3. 3.
    Cajochen, C.: Alerting effects of light. Sleep Med. Rev. 11(6), 453–464 (2007)CrossRefGoogle Scholar
  4. 4.
    Chellappa, S.L., Gordijn, M.C.M., Cajochen, C.: Can light make us bright? Effects of light on cognition and sleep, Chap. 7. In: Van Dongen, H.P.A., Kerkhof, G.A. (eds.) Human Sleep and Cognition Part II. Progress in Brain Research, vol. 190, pp. 119–133. Elsevier (2011)Google Scholar
  5. 5.
    Choi, H., Van Merrienboer, J.J.G., Paas, F.: Effects of the physical environment on cognitive load and learning: towards a new model of cognitive load. Educ. Psychol. Rev. 26, 225–244 (2014)CrossRefGoogle Scholar
  6. 6.
    US EIA. Annual energy outlook 2019 (2019)Google Scholar
  7. 7.
    Figueiro, M.G., Wood, B., Plitnick, B., Rea, M.S.: The impact of light from computer monitors on melatonin levels in college students. Neuro Endocrinol. Lett. 32(2), 158–163 (2011)Google Scholar
  8. 8.
    Gentile, C., Li, S., Kar, P., Karatzoglou, A., Zappella, G., Etrue, E.: On context-dependent clustering of bandits. In: Proceedings of the 34th International Conference on Machine Learning, vol. 70, pp. 1253–1262. JMLR.org (2017)Google Scholar
  9. 9.
    Gooley, J.J., Chamberlain, K., Smith, K.A., Khalsa, S.B.S., Rajaratnam, S.M.W., Van Reen, E., Zeitzer, J.M., Czeisler, C.A., Lockley, S.W.: Exposure to room light before bedtime suppresses melatonin onset and shortens melatonin duration in humans. J. Clin. Endocrinol. Metab. 96(3), 463–72 (2011)CrossRefGoogle Scholar
  10. 10.
    Hao, F., Li, S., Min, G., Kim, H.-C., Yau, S.S., Yang, L.T.: An efficient approach to generating location-sensitive recommendations in ad-hoc social network environments. IEEE Trans. Serv. Comput. 8(3), 520–533 (2015)CrossRefGoogle Scholar
  11. 11.
    Klepeis, N., Nelson, W.C., Ott, W., Robinson, J.P.: The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants (2001)Google Scholar
  12. 12.
    Knez, I., Hygge, S.: Irrelevant speech and indoor lighting: effects on cognitive performance and self-reported affect. Appl. Cogn. Psychol.: Official J. Soc. Appl. Res. Mem. Cogn. 16(6), 709–718 (2002)CrossRefGoogle Scholar
  13. 13.
    Knez, I., Kers, C.: Effects of indoor lighting, gender, and age on mood and cognitive performance. Environ. Behav. 32(6), 817–831 (2000)CrossRefGoogle Scholar
  14. 14.
    Korda, N., Szörényi, B., Li, S.: Distributed clustering of linear bandits in peer to peer networks. In: Journal of Machine Learning Research Workshop and Conference Proceedings, vol. 48, pp. 1301–1309. International Machine Learning Society (2016)Google Scholar
  15. 15.
    Li, S., Chen, W., Leung, K.-S.: Improved algorithm on online clustering of bandits. arXiv preprint arXiv:1902.09162 (2019)
  16. 16.
    Li, S., Karatzoglou, A., Gentile, C.: Collaborative filtering bandits. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 539–548 (2016)Google Scholar
  17. 17.
    Lok, R., Smolders, K.C.H.J., Beersma, D.G.M., de Kort, Y.A.W.: Light, alertness, and alerting effects of white light: a literature overview. J. Biol. Rhythms 33(6), 589–601 (2018)CrossRefGoogle Scholar
  18. 18.
    Mayton, B.D., Zhao, N., Aldrich, M., Gillian, N.E., Paradiso, J.A.: WristQue: a personal sensor wristband. In: 2013 IEEE International Conference on Body Sensor Networks, pp. 1–6 (2013)Google Scholar
  19. 19.
    Mills, P.R., Tomkins, S.C., Schlangen, L.J.M.: The effect of high correlated colour temperature office lighting on employee wellbeing and work performance. J. Circadian Rhythms 5(1), 2 (2007)CrossRefGoogle Scholar
  20. 20.
    Özçelik, M.A.: The design and comparison of central and distributed light sensored smart LED lighting systems. Int. J. Photoenergy 2018, 4589085 (2018)CrossRefGoogle Scholar
  21. 21.
    Seitinger, S., Taub, D.M., Taylor, A.S.: Light bodies: exploring interactions with responsive lights. In: Proceedings of the Fourth International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2010, pp. 113–120. Association for Computing Machinery, New York (2010)Google Scholar
  22. 22.
    Sørensen, T., Andersen, O.D., Merritt, T.: “Tangible Lights”: in-air gestural control of home lighting. In: Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2015, pp. 727–732. Association for Computing Machinery, New York (2015)Google Scholar
  23. 23.
    Zhao, N., Aldrich, M., Reinhart, C.F., Paradiso, J.A.: A multidimensional continuous contextual lighting control system using Google glass. In: Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments, pp. 235–244 (2015)Google Scholar
  24. 24.
    Zhao, N., Azaria, A., Paradiso, J.A.: Mediated atmospheres: a multimodal mediated work environment. Proc. ACM Interact. Mob. Wearable Ubiquit. Technol. 1(2), 31:1–31:23 (2017)Google Scholar
  25. 25.
    Zhao, N., Paradiso, J.A.: HALO: wearable lighting. In: Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2015 Adjunct, pp. 601–606. Association for Computing Machinery, New York (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Media LabMassachusetts Institute of TechnologyCambridgeUSA

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