US 12,454,439 B2
People flow prediction method and people flow prediction system
Yu Kitano, Tokyo (JP); Akinori Asahara, Tokyo (JP); Naoki Shimode, Tokyo (JP); and Nobuo Sato, Tokyo (JP)
Assigned to Hitachi, Ltd., Tokyo (JP)
Appl. No. 17/255,835
Filed by Hitachi, Ltd., Tokyo (JP)
PCT Filed May 10, 2019, PCT No. PCT/JP2019/018682
§ 371(c)(1), (2) Date Dec. 23, 2020,
PCT Pub. No. WO2020/003761, PCT Pub. Date Jan. 2, 2020.
Claims priority of application No. 2018-121057 (JP), filed on Jun. 26, 2018.
Prior Publication US 2021/0276824 A1, Sep. 9, 2021
Int. Cl. B66B 1/34 (2006.01); B66B 1/24 (2006.01); B66B 3/00 (2006.01); B66B 5/00 (2006.01)
CPC B66B 1/3476 (2013.01) [B66B 1/24 (2013.01); B66B 1/3446 (2013.01); B66B 3/002 (2013.01); B66B 5/0012 (2013.01)] 11 Claims
OG exemplary drawing
 
1. A people flow prediction method executed by a computer system having a processor and a storage device connected to the processor, the method comprising:
calculating, by the processor, a number of people who got in an elevator in a past on a basis of information of a sensor installed in the elevator and creating on-site getting in and out data including the number of people calculated;
creating, by the processor, virtual getting in and out data including at least a number of people who get in the elevator by making a person who arrives at each of a plurality of landings of the elevator in order to use the elevator virtually appear and simulating operation of the elevator on a basis of a number of people who appear;
creating, by the processor, a first conversion model for converting the virtual getting in and out data before a certain time point into the number of people who appear after the certain time point on a basis of the number of people who appear and the virtual getting in and out data;
creating, by the processor, a second conversion model for converting the virtual getting in and out data after a certain time point into the number of people who appear before the certain time point on a basis of the number of people who appear and the virtual getting in and out data;
learning, by the processor, a prediction model for predicting the number of people who appear after a certain time point from the number of people who appear before the certain time point on a basis of the number of people who appear converted by the second conversion model;
predicting, by the processor, the number of people who appear after a certain time point from the on-site getting in and out data before the certain time point by using the first conversion model and the prediction model; and
controlling operation of the elevator based on a prediction of the number of people who appear after a certain time point from the on-site getting in and out data before the certain time point.