An elevator system is provided. Aspects includes an elevator car, a sensor affixed to the elevator car, wherein the sensor is operated by a controller, the controller is configured to receive occupancy data associated with the elevator car. The occupancy data is analyzed to determine an occupancy of the elevator car. A first hall call is received and based at least in part on the occupancy and the first hall call, adjusting operation of the elevator car in the elevator system.

A group control device according to the present disclosure includes a registration unit, a calculation unit, and a selection unit. The registration unit makes call registration for a boarding floor, a destination floor, and an allocated car when a user makes a hall destination call by a hall destination calling device. The calculation unit calculates an in-car stay time of the user for the hall destination call. The selection unit selects a past hall destination call as an alternative candidate for call registration for a new hall destination call, in a case where the past hall destination call which has already been registered by the registration unit, whose allocated car is different from a car allocated to the new hall destination call, and whose in-car stay time is shorter than the in-car stay time calculated by the calculation unit.

One or more elevators can be more efficiently controlled by considering the then-current spatial capacity of the elevator. Camera images or other sensor data indicative of the occupied space in the elevator are received and processed by a control device to determine whether or not the elevator should stop at a requested floor. If the elevator is determined to lack space for additional passengers, then the elevator can bypass the requested stop and proceed without delay. If space remains, however, the elevator can stop to accommodate additional passengers. Measured spatial capacity can also be used to coordinate the actions of multiple elevators operating within a building.

A collaborative scheduling method for high-rise elevators based on Internet of Things is provided. The method includes: obtaining the number of people carried at the current moment of each elevator in the elevator group, the target distance corresponding to the current moment of each elevator, and the number of people waiting at the current moment of each floor; predicting the number of people waiting for the going up and the number of people waiting for the going down at the current moment of each floor based on the monitoring video data of the elevator door every day in the preset historical days, and constructing the corresponding feature vectors of each elevator at the current moment and the corresponding feature vectors of the skyscraper at the current moment, and then obtaining the corresponding state vectors at the current moment, controlling each elevator based on state vector and ES-Reinforcement learning network.

A dynamic car assignment method implemented by an elevator system is provided. The elevator system includes a plurality of elevators. The dynamic car assignment method includes an assignment, by the elevator system, of a first elevator car of the plurality of elevators to pick up a passenger in response to an elevator call. The elevator system then detects that the first elevator car is fully occupied prior to the first elevator car arriving to pick up the passenger. Further, the elevator system dynamically assigns a second elevator car of the plurality of elevator cars to pick up the passenger in response to the elevator call and in response to detecting that the first elevator car is fully occupied.

An elevator operation managing device capable of reducing a switching of passengers at a time of getting on and getting out of a car. The elevator operation managing device includes an in-car position acquisition unit and a car allocation acquisition unit. The in-car position acquisition unit obtains an in-car position of a user based on layout information and a congestion degree obtained in a congestion degree acquisition unit. The car allocation acquisition unit performs a car allocation to allocate the user to the car based on a received boarding floor and destination floor and the in-car position obtained in the in-car position acquisition unit.

A conveyance system including a system interface having a camera to generate an image including an input fingerprint and an input finger presentation; a dispatch system including a fingerprint recognition unit and a profile unit, the fingerprint recognition unit comparing the input fingerprint to a reference fingerprint; the dispatch system accessing a user profile when the input fingerprint matches the reference fingerprint; the dispatch system comparing the input finger presentation to a reference finger presentation in the user profile; and the dispatch system retrieving a destination from the user profile when the input finger presentation matches the reference finger presentation.

A method for controlling an elevator system comprises obtaining images of the inside of an elevator car, detecting passengers in the images, creating graphic passenger models of the detected passengers from the images and determining the number of passengers who may additionally board the elevator car using the passenger models. The passenger models may reflect the actual size of the passengers.

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.

Systems and methods for operating an elevator system are provided. Aspects includes receiving, by a processor, a call request for an elevator car in an elevator system. Receiving sensor data from a plurality of sensors associated with the elevator car, wherein the plurality of sensors are configured to collect sensor data from one or more predefined areas associated with the elevator car. Determining an occupancy level in the elevator car based on a feature vector, generated by a machine learning model, comprising a plurality of features extracted from the sensor data and operating, by the processor, the elevator car based at least in part on the occupancy level.