Company / Competitor

Hitachi

Mentioned in 7 AI use cases across 4 industries

Use Cases Mentioning Hitachi

energyTime-Series

Nostradamus AI Energy Forecasting Software Solution

This is like a very smart weather forecast, but for electricity and energy: it predicts how much energy will be needed or produced in the future so utilities and grid operators can plan ahead and avoid costly surprises.

transportationTime-Series

AI Solutions for Connected Transportation Assets

Think of this as a digital mechanic that constantly listens to your vehicles, trains, or equipment, predicts when something is about to break, and tells you exactly when to bring it in for service so you avoid breakdowns and warranty fights.

energytime-series

AI Applications in the Energy Sector (from multiresearchjournal.com article)

Think of this as giving power plants and grids a smart brain that constantly watches operations, predicts future demand and equipment issues, and suggests optimal ways to run everything more safely and cheaply.

energyClassical-Supervised

Machine Learning for Faster, More Reliable Power Flow in Electric Grids

This is like giving the power grid a smart navigation system that can instantly reroute electricity around traffic jams and accidents so the lights stay on and the roads (power lines) don’t get overloaded or damaged.

energyTime-Series

Smart Grid Management and Optimization

A smart grid is like upgrading from an old landline to a modern smartphone for your electricity network. Instead of just pushing power one way from big plants to homes, the grid becomes two‑way, with sensors and software that can see what’s happening in real time, shift loads, use home batteries and solar panels, and prevent or shorten outages.

miningWorkflow Automation

Mining Digitalization in 2025: Current Landscape, Trends and Outlook

This is a big-picture review of how modern software, sensors, automation, and AI are changing mines—from how ore is found and extracted to how equipment is run and energy is used. Think of it as a roadmap showing how a traditional mine can become a data-driven, semi-autonomous factory under the ground and in open pits.

constructionTime-Series

Optimizing maintenance of heavy equipment: A data-driven approach

Think of this as a “health tracker and advisor” for bulldozers, excavators, and cranes. It watches how machines are used, learns patterns from past breakdowns, and then tells you the best time to maintain each piece of equipment so you fix problems before they become expensive failures.