US 11,854,250 B2
Portable terminal and oshibori management system
Yasuyuki Sakai, Tokyo (JP); and Taku Watanabe, Tokyo (JP)
Assigned to FSX, INC., Tokyo (JP)
Appl. No. 17/755,088
Filed by FSX, INC., Tokyo (JP)
PCT Filed Aug. 17, 2021, PCT No. PCT/JP2021/029993
§ 371(c)(1), (2) Date Apr. 21, 2022,
PCT Pub. No. WO2022/059404, PCT Pub. Date Mar. 24, 2022.
Claims priority of application No. 2020-155461 (JP), filed on Sep. 16, 2020.
Prior Publication US 2022/0375212 A1, Nov. 24, 2022
Int. Cl. G06V 10/82 (2022.01); G06T 7/13 (2017.01); G06T 7/70 (2017.01); G06V 10/72 (2022.01); G06V 10/764 (2022.01); G06V 10/44 (2022.01); G06Q 10/0875 (2023.01); G06V 10/24 (2022.01); H04N 23/63 (2023.01); H04N 23/60 (2023.01)
CPC G06V 10/82 (2022.01) [G06Q 10/0875 (2013.01); G06T 7/13 (2017.01); G06T 7/70 (2017.01); G06V 10/24 (2022.01); G06V 10/44 (2022.01); G06V 10/72 (2022.01); G06V 10/764 (2022.01); H04N 23/63 (2023.01); H04N 23/64 (2023.01); G06T 2207/10024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30242 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A portable terminal comprising: an information receiving unit that receives pre-collection store information from a core system, the pre-collection store information including a store to which oshiboris are delivered, a type of the oshiboris used by the store, a number of the oshiboris delivered to the store, a number of the oshiboris collected from the store, and a number of the oshiboris in stock at the store;
a photographing unit that photographs used oshiboris stored in a collection box;
a learning model storing unit that stores a learning model learned by a neural network with an image for learning as an input value and a number of the used oshiboris as an output value, the image for learning photographed the used oshiboris stored in the collection box;
an image acquiring unit that acquires an image for estimation photographed by the photographing unit; an estimating unit that estimates a number of used oshiboris from the image for estimation acquired by the image acquiring unit, with the learning model stored in the learning model storing unit, by the neural network; a display unit that displays an estimation result estimated by the estimating unit; and an information transmitting unit that transmits post-collection store information added the estimation result to the pre-collection store information received by the information receiving unit to the core system.