Optimization of Elevator Services Using Machine Learning
Keywords:
Elevator, Machine Learning, Optimization, Up-peak, Down-peak, zoning division techniqueAbstract
Elevators are used in a large amount of buildings all over the world for fast and comfortable transportation.
Today it is becoming increasingly important for people and products to be time efficient, and with technological development
new solutions are created to answer this rising demand. To do this in an elevator context, elevator control strategies are
implemented as optimal as possible. Machine learning is a relatively new concept, but it is already used in attempts to
improve the performance of elevator control strategies. Machine learning algorithms can learn from both the current and
past environments. Also the Zoning division technique is proposed to improve the speed of operation. Conclusion drawn is
that the current environment is most valuable in the user travel pattern down-peak, while information about previous days
especially can improve the performance in the user travel pattern up-peak
