Abstract
One of the primary concerns of humanity today is developing strategies for saving energy and promoting environmental sustainability. This paper suggests the development of an intelligent Internet of Things based system with the use of meta-heuristics that will be able to find optimal energy saving configurations. This system takes into account the activity of the users, size of area, state of lights, and blinds. A comparative study of four optimization techniques (GA, PSO, DBDE, and BSO) with the use of the Friedman test is shown.
Please note that the LNCS Editorial assumes that all authors have used the western naming convention, with given names preceding surnames. This determines the structure of the names in the running heads and the author index.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Friess, P.: Internet of Things-global Technological and Societal Trendsfrom Smart Environments and Spaces to Green ICT. River Publishers (2011)
Doctor, F., Hagras, H., Callaghan, V.: An intelligent fuzzy agent approach for Realising ambient intelligence in intelligent inhabited environments. IEEE Trans. Syst., Man Cybern., Part A: Syst. Humans 55–65 (2005)
Sulaiman, F., Ahmad, A., Kamarulzaman, M.S.: âce Automated Fuzzy LogicLight Balanced Control Algorithm Implemented in Passive Optical FiberDay lighting System. In: At AIML6 (2006)
Wang, Z., Wang, Y.: âce Design of intelligent residential light-ing control system based on zigbee wireless sensor network and fuzzy con-trollerâ. In: 2010International Conference on Machine Vision and Human-Machine Interface (MVHI), pp. 561–564 (2010)
Miki, M., et al.: Intelligent lighting control using correlation coefficient between luminance and illuminance. Proc. IASTED Intell. Syst. Control. 497(078), 31–36 (2005)
Pandharipande, A., Caicedo, D.: Adaptive illumination rendering in LED lighting systems. IEEE Trans. Syst., Man, Cybern.: Syst. 1052–1062 (2013)
Pan, M.-S., et al.: A WSN-based intelligent light control system considering user activities and proles. IEEE Sens. J. 8(10), 1710–1721 (2008)
Caicedo, D., Pandharipande, A.: Distributed illumination control with local sensing and actuation in networked lighting systems. IEEE Sens. J. 13(3), 1092–1104 (2013)
Romero-Rodriguez, W.J.G. et al.: Comparative study of BSO and GA for the optimizing energy in ambient intelligence. In: Mexican International Conference on Artificial Intelligence, pp. 177-188. Springer, Berlin (2011)
Eberhart, R., Kennedy, J.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948. Citeseer (1995)
Eberhart, R.C., Shi, Y., Kennedy, J.: Swarm Intelligence. Elsevier (2001)
Pham, D.T. et al.: The bees algorithm a novel tool for complex optimisation problems. In: Intelligent Production Machines and Systems, pp. 454–459. Elsevier (2006)
Sampson, J.R.: Adaptation in natural and artificial systems (John H. Holland). In: Society for Industrial and Applied Mathematics (1976)
Storn, R., Price, K.: Differential evolution a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11(4), 341–359 (1997)
Mexicana, N.: NOM-025-STPS-2008. In: Condiciones de iluminacion en los centros de trabajo (2008)
Acknowledgements
This work is supported by the Instituto Tecnológico de León. The authors want to acknowledge the generous support by the Consejo Nacional de Ciencia y Tecnología (CONACyT) for this research project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Romero-Rodriguez, W.J.G., Baltazar, R., Zamudio, V., Casillas, M., Alaniz, A. (2020). Comparative Study of Bio-Inspired Algorithms Applied to Illumination Optimization in an Ambient Intelligent Environment. In: Jezic, G., Chen-Burger, YH., Kusek, M., Šperka, R., Howlett, R., Jain, L. (eds) Agents and Multi-agent Systems: Technologies and Applications 2019. Smart Innovation, Systems and Technologies, vol 148. Springer, Singapore. https://doi.org/10.1007/978-981-13-8679-4_18
Download citation
DOI: https://doi.org/10.1007/978-981-13-8679-4_18
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-8678-7
Online ISBN: 978-981-13-8679-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)