At GRID, our philosophy is “Infrastructure, Life, Innovation,” which expresses our desire to contribute AI technologies to infrastructure projects that are connected to people’s life.
GRID INC. analyzes a variety of dataset from “Infrastructure”, “Manufacturing””Energy””Plant””Finance”. Supporting multiple algorithm within “ReNom”, we implement data analysis and research and development of AI.
Deep learning is used to extract traffic congestion patterns from large amounts of data gathered on freeways, in order to predict traffic congestion. The congestion predictions can be used to regulate speed and control vehicles to flow to the roadway, alleviating or preventing congestion in advance, as well as reducing economic loss from traffic delays.
Constant railcar condition monitoring can be performed by collecting real time data and using deep learning to execute high-level analysis, which increases inspection efficiency and assures greater safety.
AI can provide optimal overall solutions for a certain supply chain such as material procurement, transportion, storage, production, and delivery service. This can support decision-making by using algorithms to identify the best options in a constant changing situation and environment, such as alternatives to minimize costs and options to maximize production.
Rough meshed spatio-temporal data, distributed from Japan Meteorological Agency, can be recalculated in hundred-meter grids at 30-minute intervals, acquiring more detailed weather information. The resulting weather data can be used as explanatory variables to solve problems caused by weather data in a variety of industries.