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India and Japan forge data partnership to power AI-ready smart cities

India and Japan forge data partnership to power AI-ready smart cities

BENGALURU: A Japanese construction technology firm and an Indian Institute of Science-backed data platform have joined forces in a bid to unlock one of urban planning’s most persistent blind spots: the vast troves of construction data that go dark the moment a building project closes.ONESTRUCTION Inc., a Tottori-based specialist in open-standard built environment data, and DataKaveri Systems, the commercial arm of IISc Bengaluru’s Centre of Data for Public Good (CDPG) signed an MoU to integrate construction data into AI-ready urban data exchanges across Indian and Japanese cities.The signing took place on the sidelines of the inaugural Japan-India AI Strategic Dialogue — a bilateral initiative to advance cooperation in AI and data infrastructure.Under the agreement, the two organisations will work to connect ONESTRUCTION’s openBIM platform — built around IFC, the internationally recognised open data standard for construction information — with DataKaveri’s Intelligent Universal Data Exchange (IUDX), a platform already live across 55 smart cities in India covering urban mobility, utilities, environment and public services.The ambition is to make construction data such as floor plans, utility layouts, and asset histories, flow securely into city-scale AI applications and digital twins, rather than being lost or locked within individual project silos once construction ends. Lucas Haywood, VP of Global Strategy at ONESTRUCTION, said the collaboration pointed toward a future where standardised building data could be useful “in the context of everything else that describes a city.” Ashok Krishnan, VP of Commercial Business and Revenue at CDPG and DataKaveri, described the construction industry as sitting on “a goldmine of data” that rarely travels beyond the boundaries of individual projects.The two firms said they would jointly explore AI use-cases drawing on combined construction and urban datasets, and pursue bilateral funding opportunities. Both said they hoped the model could be replicated internationally.

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