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公开(公告)号：US20250100414A1
公开(公告)日：2025-03-27
申请号：US18730420
申请日：2022-01-31
Applicant: NEC Corporation
Inventor： Iori TOKUDA , Tooru IWAMOTO , Takuroh KASHIMA , Norihito OI , Tomoaki MAKINO
Abstract: An electric vehicle management apparatus (10) includes a charging plan acquisition unit (110), an operation plan acquisition unit (120), and an output unit (150). The charging plan acquisition unit (110) acquires vehicle identification information of at least one electric vehicle incorporated with a battery, and charging plan information indicating a charging schedule period of the electric vehicle associated with the vehicle identification information, in association with each other. The operation plan acquisition unit (120) acquires the vehicle identification information of a target vehicle being the electric vehicle for which operation timing is determined, and the operation timing of the target vehicle, in association with each other. The output unit (150) outputs first vehicle information indicating the target vehicle, when the charging plan information of the target vehicle is absent, or when it is indicated that charging is not completed before the operation timing in the charging plan information.
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公开(公告)号：US20240085196A1
公开(公告)日：2024-03-14
申请号：US18274909
申请日：2021-02-01
Applicant: NEC Corporation
Inventor： Asako FUJII , Takuroh KASHIMA
CPC classification number: G01C21/3446 , G01C21/343 , G01C21/3453 , G06N3/092
Abstract: A function input means 71 accepts input of a cost function that calculates a cost incurred by an itinerary, the cost function being expressed as a linear sum of terms weighted for each feature that a traveler is expected to intend in the itinerary. A learning means 72 learns the cost function by inverse reinforcement learning using training data that includes scheduled information indicating travel planning of the traveler, attribute information indicating an attribute of the traveler, and actual information indicating an actual travel result of the traveler. A data extraction means 73 extracts the training data whose specified attribute matches the attribute information. Then, the learning means 72 learns the cost function according to the attributes by inverse reinforcement learning using the extracted training data.
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公开(公告)号：US20250069177A1
公开(公告)日：2025-02-27
申请号：US18722767
申请日：2021-12-28
Applicant: NEC Corporation
Inventor： Norihito OI , Tooru IWAMOTO , Takuroh KASHIMA , Tomoaki MAKINO
Abstract: A transportation plan acquisition unit (11) acquires a transportation plan including a transportation destination, an order of transportation, and a weight of a cargo. A terminal departure time state of charge (SOC) acquisition unit (12) acquires an SOC of a vehicle at a time of departure from a terminal. An SOC change prediction unit (13) determines, based on the transportation plan, a load during transportation changing in response to loading and unloading of the cargo during transportation, and predicts, based on the determined load, a change of an SOC of the vehicle during transportation when transportation following the transportation plan is performed. A determination unit (14) determines whether a point where an SOC drops below a reference value exists in a change of an SOC of the vehicle during transportation. A determination result output unit (15) outputs a result of the determination.
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Patent Agency Ranking
公开(公告)号：US20220392057A1
公开(公告)日：2022-12-08
申请号：US17770109
申请日：2020-10-05
Applicant: NEC Corporation
Inventor： Yuka OSHIMA , Takuroh KASHIMA , Yusuke KOITABASHI , Atsushi MATSUDA
Abstract: A first imaging unit 71 generates a first image a first image by taking an object to be inspected. A guide display unit 72 determines the object to be inspected from the first image by using a model for determining an object to be inspected from an image, and displays an illustration representing the object to be inspected as a guide. A second imaging unit 73 generates a second image by superimposing on the guide, and taking the object to be inspected with a recognizable marker regardless of color of an appearance of an object to be inspected, attached in a vicinity of a defect. A defect position determination unit 74 determines a position of the defect included in the object to be inspected based on a positional relationship between the illustration and the marker included in the second image. An information collecting unit 75 collects defect information associated with a type of the object to be inspected and the position of the defect.
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公开(公告)号：US20250157262A1
公开(公告)日：2025-05-15
申请号：US18727119
申请日：2022-01-17
Applicant: NEC Corporation
Inventor： Norihito OI , Tooru IWAMOTO , Takuroh KASHIMA , Tomoaki MAKINO
Abstract: The present invention provides a warning apparatus (10) including a prediction information acquisition unit (11) that acquires prediction information indicating a change in a predicted value of state of charge (SOC) of a vehicle while traveling based on a transport plan is performed, an actual measurement value acquisition unit (12) that acquires an actual measurement value of SOC of the vehicle while traveling based on the transport plan is performed, a determination unit (13) that determines whether a relationship between the predicted value and the actual measurement value satisfies a predetermined warning condition, and an output unit (14) that outputs first warning information in a case where the warning condition is satisfied.
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公开(公告)号：US20250156795A1
公开(公告)日：2025-05-15
申请号：US18727140
申请日：2022-01-18
Applicant: NEC Corporation
Inventor： Norihito OI , Tooru IWAMOTO , Takuroh KASHIMA , Tomoaki MAKINO
IPC: G06Q10/083 , G06Q10/0631 , G07C5/02
Abstract: The present invention provides a processing apparatus (10) including a prediction information acquisition unit (11) that acquires remaining-fuel-amount prediction information indicating a change in a predicted value of a remaining amount of fuel in a vehicle while traveling based on a transport plan is performed and being produced based on a prediction model, an actual measurement information acquisition unit (12) that acquires remaining-fuel-amount actual measurement information indicating a change in an actual measurement value of a remaining amount of fuel in the vehicle while traveling based on the transport plan is performed, and a determination unit (13) that determines, based on the remaining-fuel-amount prediction information and the remaining-fuel-amount actual measurement information, whether correction of the prediction model is necessary.
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7.发明公开公开(公告)号：US20240289941A1
公开(公告)日：2024-08-29
申请号：US17768612
申请日：2020-10-05
Applicant: NEC Corporation
Inventor： Yuka OSHIMA , Takuroh KASHIMA , Yusuke KOITABASHI , Atsushi MATSUDA
CPC classification number: G06T7/0008 , G06T7/62 , G06T2207/30156 , G06T2207/30204
Abstract: A conversion equation calculation unit 81 calculates, based on a defect image with marker in which a marker of a predetermined size that can be recognized regardless of color of appearance of an object to be inspected and a defect of the object to be inspected are taken, a conversion equation from size of the defect image with marker to actual size. A defect type determination unit 82 determines, by using a model for detecting the defect of the object to be inspected from an image and determining a defect type, the defect type included in the defect image with marker. A defect measuring unit 83 measures defect size included in the defect image with marker by using the conversion equation. A defect content output unit 84 outputs the determined defect type and the measured defect size.
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公开(公告)号：US20220274608A1
公开(公告)日：2022-09-01
申请号：US17627969
申请日：2020-05-22
Applicant: NEC Corporation
Inventor： Asako FUJII , Yusuke KOITABASHI , Takuroh KASHIMA , Yuki CHIBA , Kenji SOBATA
Abstract: A comfort determination model learning unit 81 learns a comfort determination model, by using comfortable activity data where a comfort indicator, which is an indicator measuring whether an individual is comfortable or not when an activity classified as a comfortable activity is performed, is associated with a teacher label indicating comfort, and uncomfortable activity data where the comfort indicator when an activity classified as an uncomfortable activity is performed, is associated with a teacher label indicating discomfort, as first training data, taking an objective variable for a comfort value indicating a degree of comfort, and taking an explanatory variable for each of the comfort indicators. An individual data generation unit 82 generates individual data including explanatory variables, which are used in the comfort determination model, generated based on the comfort indicators of the subject during riding on a vehicle, and driving situations of the vehicle when the comfort indicators are obtained. A driving data generation unit 83 generates comfortable driving data and uncomfortable driving data according to a comfort value calculated by applying the individual data to the comfort determination model.
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