Dtonic Presents Its Vision for the Evolution from Smart City to AI City at WSCE 2026

Dtonic sales representative explains the company’s D.Hub AI OS to visitors at WSCE 2026.

Dtonic presented its vision for the next stage of urban intelligence at the 2026 World Smart City Expo, or WSCE 2026. The company demonstrated how cities can move beyond data connectivity and centralized monitoring toward an “AI City” model in which AI understands urban relationships and context and supports operational decision-making.

Dtonic operated an AX PAVILION booth at the event, held from September 9 to 11 at BEXCO in Busan, showcasing its technology and project experience in supporting AI transformation across cities and enterprises.

During the three-day exhibition, Dtonic engaged with hundreds of domestic and international visitors, including representatives from approximately 50 companies and public institutions across 10 countries, such as France, the UAE, Vietnam and Ghana. Discussions focused on potential AI City applications, domain-specific AI transformation and ways to adapt Dtonic’s technology to different urban environments and operational systems.

From Data Connectivity to Decisions and Execution

At the exhibition, Dtonic demonstrated how its D.Hub AI platform integrates heterogeneous data from different systems and sources. Semantic technologies and ontology then structure the meaning of the data and the relationships between business and urban entities.

This structured information can be combined with knowledge graphs and hybrid retrieval-augmented generation to help AI identify and use evidence for its outputs. D.Hub can also orchestrate collaboration among multiple AI agents according to defined operational objectives and business logic.

Together, these capabilities provide an end-to-end AX foundation spanning data integration, knowledge structuring, response planning and support for human decision-making and execution.

Public-sector visitors showed particular interest in urban data standardization and integrated operations across disaster management, transportation and public safety. Enterprise representatives focused on connecting existing systems and heterogeneous data, structuring business logic and applying ontology-based decision support.

Dtonic is coordinating follow-up discussions with a number of organizations and companies introduced during the event as it develops new AX business opportunities.

An AI Operating Foundation for Cheonan and Asan

Dtonic also participated in the exhibition area dedicated to the Cheonan–Asan AI Specialized Pilot City in South Chungcheong Province.

With a total planned investment of KRW 610.9 billion, the initiative aims to connect data and AI services across Cheonan and Asan as a shared metropolitan living area, extending beyond individual administrative boundaries.

Dtonic introduced an urban AI operating foundation that standardizes and connects data from both cities while enabling AI services and physical AI systems to operate together within a unified environment.

Advancing from Smart Cities to AI Cities

Dtonic has built and operated data hubs for major metropolitan and provincial governments across South Korea, including Seoul, Busan, Ulsan, South Gyeongsang, South Chungcheong, North Chungcheong and Jeju.

Its recent participation in the Busan Smart City Specialized District and the Cheonan–Asan AI Specialized Pilot City reflects the company’s continued expansion from smart-city infrastructure toward AI City operations.

Dtonic CEO Yong Joo Jun described this transition as the addition of an intelligent operational layer to the connected sensing and data infrastructure established by smart cities. In this model, an AI City can understand relationships and context, coordinate multiple AI systems and support increasingly autonomous urban operations.

Drawing on its experience across the public and industrial sectors, Dtonic plans to work with customers throughout the complete AX lifecycle—from connecting and structuring data to supporting decisions and real-world execution.



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