Traffic teams missed flooding data trapped in silos. Now, Vision Language Models scan 30,000 feeds to alert all city agencies instantly.
One of Taiwan's largest cities monitors 30,000 camera feeds across isolated departments like water management and transportation.
Departmental silos prevented agencies from sharing critical data, meaning traffic bureaus remained unaware of flooding detected by water management...
“Through the innovations of generative AI and VLM, we aim to demonstrate the immense potential of vision AI in smart city development. Integrating NVIDIA technologies, our solutions are becoming more efficient and valuable. The collaboration with NVIDIA showcases how smart technologies can align with urban visions to create meaningful and impactful changes.”
Linker Vision's Urban incident detection is part of this use case:
AI platform for physical monitoring and smart city infrastructure automation.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Related implementations across industries and use cases
With 2.5 staff, manual counts slowed signal timing. Vision AI now tracks 55k vehicles in a live 3D twin to optimize flow continuously.
Zoning rules buried in thousands of PDF pages caused permit denials. An AI agent now interprets codes to guide applicants instantly.
Most video went unwatched. AI now monitors live feeds, flagging crimes and wildlife threats for officers in seconds.
With 2.5 staff, manual counts slowed signal timing. Vision AI now tracks 55k vehicles in a live 3D twin to optimize flow continuously.
Most video went unwatched. AI now monitors live feeds, flagging crimes and wildlife threats for officers in seconds.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Teams manually monitored 395km of track. Now, AI predicts faults like wire sagging in real time, targeting 20% less downtime.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Traffic teams missed flooding data trapped in silos. Now, Vision Language Models scan 30,000 feeds to alert all city agencies instantly.
One of Taiwan's largest cities monitors 30,000 camera feeds across isolated departments like water management and transportation.
Departmental silos prevented agencies from sharing critical data, meaning traffic bureaus remained unaware of flooding detected by water management...
“Through the innovations of generative AI and VLM, we aim to demonstrate the immense potential of vision AI in smart city development. Integrating NVIDIA technologies, our solutions are becoming more efficient and valuable. The collaboration with NVIDIA showcases how smart technologies can align with urban visions to create meaningful and impactful changes.”
Linker Vision's Urban incident detection is part of this use case:
AI platform for physical monitoring and smart city infrastructure automation.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Related implementations across industries and use cases
With 2.5 staff, manual counts slowed signal timing. Vision AI now tracks 55k vehicles in a live 3D twin to optimize flow continuously.
Zoning rules buried in thousands of PDF pages caused permit denials. An AI agent now interprets codes to guide applicants instantly.
Most video went unwatched. AI now monitors live feeds, flagging crimes and wildlife threats for officers in seconds.
With 2.5 staff, manual counts slowed signal timing. Vision AI now tracks 55k vehicles in a live 3D twin to optimize flow continuously.
Most video went unwatched. AI now monitors live feeds, flagging crimes and wildlife threats for officers in seconds.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Teams manually monitored 395km of track. Now, AI predicts faults like wire sagging in real time, targeting 20% less downtime.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.