Nippon Yusen Kabushiki Kaisha

Hitachi Solutions, Ltd.

Takashi Mishima

Masayuki Kozuka

Hiroshi Nakatani

Tomoo Oishi

Kanefumi Uematsu

Masahiro Shibaoka

Akinori Asahara

Masahiro Oba

Naoki Shimode

Tomohide Suzuki

A client device accepts event information for which a people flow prediction is to be performed from a user and the client device inputs the accepted event information to a people flow prediction device. The people flow prediction device outputs a result of people flow prediction responsive to the input event information to the client device and the client device displays the result of people flow prediction to the user. The people flow prediction device performs a people flow prediction by temporally and spatially allocating an event attendance which has been input from the client device to pathways, each connecting a transport facility at which a people flow originates and an event site. Consequently, it is possible to predict a flow of people who attend an event or the like, the people flow differing from that in an ordinary situation, without need to input real-time data.

People flow prediction device

A reference range identifying device acquires and records, at a predetermined time interval, a measuring result of a load and exhaust temperature of an engine. The device identifies, based on combinations of the load and exhaust temperature recorded at multiple points of time, for each load zone, for example a 95% confidence interval of a distribution of exhaust temperatures as a reference range. Subsequently, the device calculates an approximate curve for lower limits and upper limits of reference ranges identified for the load zones. The device identifies a range sandwiched by the calculated two approximate curves as a reference range that changes in accordance with a load. The device, upon detecting that a current load and exhaust temperature of the engine is not included in the reference range, notifies the detected fact to a user.

Device, program, recording medium, and method for determining device normality and abnormality involving loads

A first unit acquires attribute record data and a second unit acquires deterioration degree data from a terminal device mounted on a ship. The attribute record data indicates an attribute relating to a past sailing of the ship. The deterioration degree data indicates a deterioration degree, which is checked during performance of maintenance work, of each device mounted on the ship. A third unit generates relational data indicating a relation between various attributes relating to the state of the sailing of the ship and the deterioration degree of the device based on the attribute record data and deterioration degree data. A fourth unit acquires estimated attribute data indicating an estimated value of the attributes relating to sailing of the ship. A fifth unit generates timing data indicating a timing of maintenance work to be performed on each device based on the attribute record data, estimated attribute data, and relational data.

Device, program and recording medium for assisting maintenance of marine equipment

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Tokyo, Japan

Takashi Mishima