A Japanese government-funded project to develop the world's first predictive maintenance system for industrial plants will employ artificial intelligence and advanced technology to store data in a secure and user-centric way.
The IOTA Foundation, a German-based nonprofit organization behind the technology, said it has been chosen as a partner in the project funded by Japan's New Energy and Industrial Technology Development Organization, a national research and development agency operating under the Ministry of Economy, Trade and Industry.
The project, which seeks to strengthen the durability of critical infrastructure, will optimize facility management systems deployed in power, industrial, petrochemicals and oil refining plants throughout Japan by digitizing maintenance data and using artificial intelligence to predict when checkups are needed, according to the foundation.
Data for plants across Japan are currently stored manually, causing issues with integrity and sharing capability, it said.
The project aims to shift data to a decentralized database using IOTA's distributed ledger service called the Tangle, while AI systems are expected to replace engineers amid Japan's shrinking labor force.
Each node in a distributed ledger database, which is geographically spread across multiple sites on a peer-to-peer network, replicates and saves an identical copy of the ledger and updates itself independently.
The decentralized nature of the system makes it more resistant to cyberattacks while making it easier for partners across the supply chain to share data in an efficient way.
It marks the first time the IOTA Foundation has partnered with organizations within Japan, although it has worked with overseas subsidiaries of Japanese companies in the past, said the foundation's co-founder Dominik Schiener.
The IOTA Foundation, established in Germany in 2017 to support development of the IOTA platform and related technologies, is currently involved in a range of collaborative projects, including digitizing Europe's mine supply chain and improving data management in East Africa.