--- title: "AI for Transportation & smart cities" description: "Turn camera feeds, sensor data and service requests into operational signals — with people deciding what happens next." url: https://lidvizion.ai/industry/transportation-smart-cities/ site: Lid Vizion index: https://lidvizion.ai/llms.txt --- [Industries](https://lidvizion.ai/industry/home/) · Transportation & smart cities # AI for transportation & smart cities. Turn camera feeds, sensor data and service requests into operational signals — with people deciding what happens next. [Talk through your workflow](https://lidvizion.ai/contact/?need=milestone-delivery&from=%2Findustry%2Ftransportation-smart-cities%2F#write) · [Start with a workflow audit](https://lidvizion.ai/workflow-audit/) Where it helps ## Three places to start. Illustrative workflow patterns, not results from a specific customer. Transportation & smart cities ### Parking and curb occupancy Detect which spaces are free or occupied and feed the count to signage or an app. Transportation & smart cities ### Incident and request triage Classify incoming service requests and route them to the right crew with a summary. Transportation & smart cities ### Asset condition checks Flag damage or obstructions in routine inspection images for a person to confirm. Use cases ## See the full workflow. - [Movement and activity analysis from video](https://lidvizion.ai/use-cases/video-movement-analysis/): Sports & field operations Count repetitions, score form or track activity from ordinary video, with results a coach or supervisor can check. - [Public service request routing](https://lidvizion.ai/use-cases/public-service-request-routing/): Customer support Classify incoming service requests from residents, such as potholes, streetlights, missed collections or blocked drains, add the location and a short summary, flag duplicates and route each one to the right crew or department. - [Support triage and reply drafts](https://lidvizion.ai/use-cases/support-triage/): Customer support Classify incoming tickets, find the relevant answer, and draft a reply for an agent to check. - [Parking and space occupancy from cameras](https://lidvizion.ai/use-cases/parking-and-space-occupancy/): Facilities & operations Use existing cameras to count which spaces are free or occupied and feed the count to signage, an app or a dashboard, with people checking anything unusual. - [Street asset defect reports from routine drives](https://lidvizion.ai/use-cases/street-asset-defect-reports/): Facilities & operations Use images captured on routine drives to flag likely road, sign and street-furniture defects with a location, so an inspector confirms each one and real defects become work orders. - [Driver vehicle inspection reports](https://lidvizion.ai/use-cases/driver-vehicle-inspection-reports/): Operations Turn drivers’ daily vehicle check photos and checklists into consistent inspection records, and send defects straight to maintenance with the photo attached, so problems are fixed before they become breakdowns. - [Service interruption updates for customers](https://lidvizion.ai/use-cases/service-interruption-updates-for-customers/): Customer support Draft clear customer updates for planned work and service interruptions from the operations log, and answer “is it fixed yet?” questions from the latest approved status, so the contact team spends less time repeating the same update. Related ## Go deeper. - [Build the missing piece](https://lidvizion.ai/services/custom-software/): Custom tools and applications for the gaps that matter. - [Automate the repeatable](https://lidvizion.ai/services/automation/): Give recurring work an owner, a trigger, and a stop rule. - [Edge vs. cloud deployment](https://lidvizion.ai/resources/basics/edge-vs-cloud-deployment/): Where a model should run: next to the camera or sensor, or in a data centre. - [When should a company build custom AI software instead of using existing tools?](https://lidvizion.ai/answers/when-should-a-company-build-custom-ai-software/): Build custom AI software when a valuable workflow still has a material gap after existing products, connectors, APIs, configuration, and automation options have been evaluated. Custom software should solve a specific operating constraint rather than duplicate capabilities already available in the AI ecosystem. - [What is an AI agent in a business setting?](https://lidvizion.ai/answers/what-is-an-ai-agent-for-business/): An AI agent is software that uses a language model to carry out a multi-step task — reading information, deciding the next step and using connected tools — within limits the business sets, with people approving actions that matter. - [Run a computer vision proof of concept](https://lidvizion.ai/guides/run-a-computer-vision-proof-of-concept/): A four-step playbook to test whether computer vision can support a real decision, using your own images and a clear pass-or-fail test agreed up front. - [Automate one workflow in 30 days](https://lidvizion.ai/guides/automate-one-workflow-in-30-days/): A four-week playbook to take one recurring workflow from manual to automated, with an owner, approval points and a measured result. Bring the messy version ## One workflow. A better way to run it. Show us the tools, the handoffs, and the part that keeps slowing your team down. [Let’s map your workflow](https://lidvizion.ai/contact/) · [Read our approach](https://lidvizion.ai/approach/)