Implementation of Smart Transportation Services in Gimhae City
Inavi Systems, a subsidiary of Thinkware specializing in mobility map platform development, announced on June 24 that it has been selected as the final recipient in the '2025 Small-Scale Smart City Development Project (Climate Crisis Response Type)' competition hosted by the Ministry of Land, Infrastructure and Transport.
This project is part of a government policy aimed at implementing eco-friendly smart transportation services at the city level using digital twin technology, with Gimhae City confirmed as the demonstration site. Inavi Systems plans to establish a carbon-reducing transportation system by integrating K-MaaS (Korean-style Mobility-as-a-Service) with Gimhae City's public transportation and pedestrian infrastructure.
The core of the demonstration project lies in integrating high-precision spatial data with real-time traffic and infrastructure information to simultaneously enhance mobility efficiency and safety within the city. To achieve this, Inavi Systems will build an urban digital twin platform that connects with real-time data based on its core technologies: the integrated map and special-purpose route search.
In particular, the company will implement a carbon-reducing navigation service that minimizes energy consumption for transportation by utilizing special-purpose route search technology that incorporates elevation data from the integrated map and traffic flow data. This technology goes beyond simple navigation by supporting traffic flow dispersion and optimizing connections with public transportation, thereby making a practical contribution to the establishment of a sustainable urban transportation system.
A representative from Inavi Systems stated, "This demonstration project marks an important starting point for implementing a city-scale digital twin platform based on our integrated map and special-purpose route search technologies," adding, "We will contribute to the realization of sustainable smart cities by leveraging precise and highly consistent spatial data."
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