公开(公告)号：US20240219180A1

公开(公告)日：2024-07-04

申请号：US17923826

申请日：2022-01-04

Applicant: Korea University Research and Business Foundation

Inventor： Lynn CHOI ,  Han Jun BAE

IPC: G01C21/12 ,  G01C21/00 ,  G01C21/20

CPC classification number: G01C21/12 ,  G01C21/206 ,  G01C21/383

Abstract: Disclosed is a low power and low memory based indoor positioning method performed by a computing device including at least one processor. The method may include: determining an operation mode to be executed based on at least one of a motion of a target and movement of the target; loading a map segment related to a current location of the target from a memory when executing a specific mode related to performing indoor positioning; and acquiring positioning data by using sensing data collected in real time for the indoor positioning, and the map segment.

公开(公告)号：US20240247936A1

公开(公告)日：2024-07-25

申请号：US18018153

申请日：2022-01-04

Applicant: Korea University Research and Business Foundation

Inventor： Lynn CHOI ,  Han Jun BAE

IPC: G01C21/20 ,  G01C21/00 ,  G01S5/02

CPC classification number: G01C21/206 ,  G01C21/383 ,  G01C21/3863 ,  G01S5/02 ,  G01S2205/02

Abstract: Disclosed is a low memory based indoor positioning method performed by a computing device including at least one processor. The method may include: extracting coordinate information in which a sensing value is not recorded as empty space information from map data in which each of a plurality of sensing values measured in a plurality of coordinates is recorded; generating a sensing value array including the plurality of sensing values; and storing the empty space information and the sensing value array in a memory.

公开(公告)号：US20190049231A1

公开(公告)日：2019-02-14

申请号：US15972316

申请日：2018-05-07

Applicant: KOREA UNIVERSITY RESEARCH AND BUSINESS FOUNDATION

Inventor： Lynn CHOI ,  Ho Jun JANG

IPC: G01B7/008 ,  G06N3/08 ,  G01B7/14

Abstract: A device for generating a location estimation model is disclosed. The location estimation model generator device according to an embodiment of the invention includes: a map generator part configured to generate a magnetic field map, which includes magnetic field values corresponding respectively to the coordinates of an indoor space; a data generator part configured to generate learning data by using the magnetic field map; and a learning part configured to generate a location estimation model by artificial neural network (ANN) learning using the learning data.