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AI Company Builds Country Scale Maps in 3 Months: A Case Study
Technology Category
- Drones - Drone Flight & Navigation Software
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Buildings
- Marine & Shipping
Applicable Functions
- Quality Assurance
Use Cases
- Movement Prediction
- Smart Lighting
Services
- System Integration
- Testing & Certification
The Challenge
A leading AI cloud computing company was faced with the challenge of creating a large scale, end-to-end mapping solution for the entire UAE within a span of three months. The company needed to build high precision, country scale maps with rapid refresh rates, a task that is both expensive and extensive. The process involved building a map at a UAE level, adding 50+ custom attributes, performing quality checks and conflict resolution, and constantly maintaining and refreshing map data. The company also needed to derive map data intelligence from multiple imagery sources, which was a time-consuming process. The data structures used by different routing and navigation engines like OSRM and others vary by routing engine type. The client needed map data that could easily integrate with their existing routing and navigation engines.
About The Customer
The customer is a leading AI cloud computing company that was in need of a bespoke, cost-effective mapping solution. They required a solution that could efficiently map the entire UAE in a short span of three months. The company needed a large scale, end-to-end solution with custom map data attributes. They also required the map data to easily integrate with their existing routing and navigation engines. The company was looking for a solution that could effortlessly integrate with their downstream routing and navigation engines, produce map data that could be easily consumed with minimal/no assistance from map solution providers, and follow the standard schema and tagging structure along with tailored specifications provided by them.
The Solution
The solution involved a specialized approach that blended AI with map expertise. A platform was built to overlay proprietary imagery data in an integrated map-editing platform. This platform was able to merge and align proprietary street level imagery, private imagery and open source imagery, integrate client’s proprietary imagery data, incorporate the derived data intelligence into one map stack, and follow the schema and tagging structure of the client’s internal routing and navigation engines. AI modules were used to efficiently extract map attributes from street and satellite imagery. A tasking platform was utilized to leverage existing OpenStreetMap (OSM) schema for lower cost and faster turnaround time. A custom QA tool was built to perform strict platform checks on attributes to ensure high quality.
Operational Impact
Quantitative Benefit
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