Abstract
Ubiquitous computing technologies are becoming increasingly a part of our daily lives. For example, in the ubiquitous home environments, plenty of context information can be obtained from various home sensors, and this information can be exploited for smart home activities. This paper presents a new elevator scheduling system for smart apartment buildings that exploits the ubiquitous sensor technologies. In the proposed elevator scheduling system, floor sensors are located at each floor of the apartment building and detect the candidate elevator passengers’ behavior before they come to the elevator door and push the elevator call button. The detected information is then delivered to the elevator scheduling system through the building network and the elevator scheduling system utilizes this information in the efficient control of the elevator. Through extensive simulations with various passengers’ traffic conditions, we show that the proposed system performs better than the conventional elevator scheduling system in terms of the passengers’ average waiting time, the maximum waiting time, and the energy consumption of the elevator significantly.
This work has been supported by KESRI (R-2005-7-059), which is funded by MOCIE (Ministry of commerce, industry and energy).
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
Preview
Unable to display preview. Download preview PDF.
References
Kidd, C.D., Orr, R.J., Abowd, G.D., Atkeson, C.G., Essa, I.A., MacIntyre, B., Mynatt, E., Starner, T.E., Newstetter, W.: The Aware Home: A Living Laboratory for Ubiquitous Computing Research. In: Proceedings of the Second International Workshop on Cooperative Buildings (1999)
Essa, I.: Ubiquitous Sensing for Smart and Aware Environments: Technologies towards the building of an Aware Home, the DARPA/NSF/NIST Workshop on Smart Environments (1999)
Orr, R.J., Abowd, G.D.: The Smart Floor: A Mechanism for Natural User Identification and Tracking. In: The 2000 Conference on Human Factors in Computing Systems (CHI 2000), The Hague, Netherlands (2000)
Addlesee, M., Jones, A., Livesey, F., Samaria, F.: The ORL Active Floor. IEEE Personal Communications (1997)
Lee, S., Bahn, H.: An Energy-aware Elevator Group Control System. In: 3rd IEEE International Conference on Industrial Informatics (2005)
Brand, M.E., Nikovski, D.N.: Optimal Parking in Group Elevator Control. IEEE International Conference on Robotics and Automation 1, 1002–1008 (2004)
Kim, J.H., Moon, B.R.: Adaptive Elevator Group Control with Camera. IEEE Transactions on Industrial Electronics 48(2), 377–382 (2001)
Kim, C., Seong, K.A., Lee-Kwang, H., Kim, J.O.: Design and Implementation of a Fuzzy Elevator Group Control System. IEEE Transactions on System, Man, and Cybernetics 28(3), 277–287 (1998)
Brand, M.E., Nikovski, D.N.: Risk-Averse Group Elevator scheduling, Elevcon World Congress on Vertical Transportation Technology (2004)
Kulkarni, A.B.: Energy consumption analysis for geared elevator modernization: upgrade from DC Ward Leonard system to AC vector controlled drive. In: The IEEE Industry Applications Conference, Rome, Italy, vol. 4, pp. 2066–2070 (2000)
Eguchi, T., Hirasawa, K., Hu, J., Markon, S.: Elevator Group Supervisory Control Systems Using Genetic Network Programming. Congress on Evolutionary Computation 2, 1661–1667 (2004)
Igarashi, K., Take, S., Ishikawa, T.: Supervisory control for elevator group with fuzzy expert system. In: Proc. IEEE Int. Conference Industrial Technology, pp. 133–137 (1994)
Dewen, Z., Li, J., Yuwen, Z., Guanghui, S., Kai, H.: Modern elevator group supervisory control systems and neural networks technique. In: IEEE Int. Conf. Intelligent Processing Systems, pp. 528–532 (1997)
Pepyne, D., Cassandras, C.: Optimal dispatching control for elevator systems during uppeak traffic. IEEE Transactions on Control Systems Technology, 629–643 (1997)
Fujino, A., Tobita, T., Segawa, K., Yoneda, K., Togawa, A.: An elevator group control system with floor attribute control method and system optimization using genetic algorithms. In: 21st Int. Conf. Industrial Electronics, Control, and Instrumentation (1995)
Pepyne, D., Cassandras, C.: Design and Implementation of an Adaptive Dispatching Controller for Elevator Systems During Uppeak Traffic. IEEE Transactions on Control Systems Technology, 635–650 (1998)
Chung, D.-W., Ryu, H.-M., Lee, Y.-M., Kang, L.-W., Sul, S.-K., Kang, S.-J., Song, J.-H., Yoon, J.-S., Lee, K.-H., Suh, J.-H.: Drive systems for high-speed gearless elevators. IEEE Industry Applications Magazine (2001)
Amano, M., Yamazaki, M., Ikejima, H.: The latest elevator group supervisory control system. Mitsubishi Elect. ADVANCE 67, 88–95 (1996)
Maeda, T., Komaya, K.: Revised design calculations of elevator systems. In: IEEE International Conference on Systems, Man, and Cybernetics, vol. 2, pp. 1041–1046 (2000)
Fujino, A., Tobita, T., Yoneda, K.: An On-line Tuning Method for Multi-Objective Control of Elevator Group. Proceedings of IEEE Industrial Electronics, Control, Instrumentation, and Automation 2, 795–800 (1992)
Fujino, A., Tobita, T., Segawa, K., Yoneda, K., Togawa, A.: An elevator group control system with floor-attribute system optimization using genetic algorithms. IEEE Transactions on Industrial Electronics 44(4), 546–552 (1997)
Kaneko, M., Ishikawa, T., Sogawa, Y.: Supervisory control for elevator group by using fuzzy expert system. In: 23rd Int. Conf Industrial Electronics, Control, and Instrumentation (1997)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kwon, O., Bahn, H., Koh, K. (2007). A Context-Aware Elevator Scheduling System for Smart Apartment Buildings. In: Szczuka, M.S., et al. Advances in Hybrid Information Technology. ICHIT 2006. Lecture Notes in Computer Science(), vol 4413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77368-9_36
Download citation
DOI: https://doi.org/10.1007/978-3-540-77368-9_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77367-2
Online ISBN: 978-3-540-77368-9
eBook Packages: Computer ScienceComputer Science (R0)