A method and system for controlling elevator dispatch is provided. User data, including user behavior, is collected from a number of users over a specified time period. Elevator use data for a number of elevators in a building is also collected over the specified time period. Applying the user data and elevator use data, an elevator dispatch model is constructed that predicts future elevator use according to predicted user needs. An elevator control system dispatches the elevators according to the dispatch model. The elevator dispatch model is refined according to feedback data collected from users over a subsequent time period.

A method schedules elevator cars in a group elevator system in a building by first generating a set of probability distributions for arrivals of future passengers at any floor of the building, wherein the set of probability distributions are characterized by probabilistic variables that specify arrival information of the future passengers, wherein the arrival information includes a probability of service requests by the future passengers and a probability of possible times of the service requests. A schedule for the elevator cars is based on the set of probabilistic distribution. Then, the schedule is provided to a controller of the group elevator system to move the elevator cars according to the schedule.

According to an aspect, there is provided a method for forecasting elevator passenger traffic of an elevator group. The method comprises training a statistical traffic model describing a traffic profile for a specific cycle with historical timestamped origin-destination passenger counts, obtaining timestamped origin-destination passenger counts for a current cycle, generating an elevator passenger traffic forecast based on the trained statistical traffic model and the timestamped origin-destination passenger counts for the current cycle, and outputting the elevator passenger traffic forecast for use by an elevator group control.

A method of monitoring a conveyance apparatus within a conveyance system including: obtaining a first health level of a conveyance system at a first time; receiving customer feedback regarding operation of the conveyance system proximate the first time from a customer; and adjusting a threshold health level of the conveyance system to be less than or equal to the first health level of the conveyance system in response to the customer feedback.

A control system for controlling motion of elevators of a bank of elevators uses a neural network trained for an extended destination prediction of a person based on a partial trajectory of the person to produce a multinomial of the extended destination prediction. The multinomial has at least two dimensions including a first dimension of destinations of the person and a second dimension of time intervals of the person arriving at the destinations of the first dimension. The control system optimizes a schedule of the bank of elevators based on the multinomial, and further controls the bank of elevators according to the schedule.

A method for determining an allocation decision for at least one elevator includes using an existing calls in an elevator system as a first input in a machine learning module, processing the first input with the machine learning module to provide a first output comprising a first allocation decision, using the first output as a second input in an iterative module, processing the second input with the iterative module to provide a second ouput comprising a second allocation decision, and providing the second allocation decision to an elevator control module and to an allocation decision storage for further machine learning module training.

A method and an apparatus for computing allocation decisions in an elevator system is provided. Historical passenger batch journey data relating to the elevator system is obtained, wherein each passenger batch journey includes an origin and a destination floor of the journey, the number of passengers of the journey and the time of the journey. Historical passenger traffic statistics are constructed based on the passenger batch journey data, and expected calls are modelled based on the passenger traffic statistics. The modelled expected call is taken into account in computing subsequent allocation decisions in the elevator system.

A method for the call allocation in an elevator group uses a call allocation unit of an elevator group control. In the call allocation unit, passenger flow data of the elevator group is used to adapt call allocation parameters to improve the performance of the elevator group. The public traffic data is retrieved from at least one public transportation system, and is used to supplement expected passenger flow data for the adaption of call allocation parameters.

A method for elevator call allocations in an elevator group of an elevator system includes applying statistical traffic forecasts modelling future passenger arrivals in the elevator system; receiving an indication of at least one elevator call; generating, for a fixed parameter, a set of scenarios based on the statistical traffic forecasts; determining a quality attribute for each candidate allocation policy of a set of candidate allocation policies by simulating, for each candidate allocation policy, the set of scenarios according to the candidate allocation policy in a current elevator call allocation situation in the elevator system; selecting a candidate allocation policy based on the quality attributes associated with the candidate allocation policies; and allocating the at least one elevator call to at least one elevator in the elevator group according to the selected candidate allocation policy.

A method of adjusting a load setting of an elevator car that includes receiving one or more load measurements associated with the elevator car and determining a maximum load of the elevator car from the one or more load measurements. The method further includes generating a modified load setting for the elevator car based on the maximum load and replacing the load setting of the elevator car with the modified load setting.