Street View Insights lets you analyze imagery data from Google Maps' Street View to derive statistical insights. The data is made available to customers for geospatial imagery analysis using Vertex AI.
About Geospatial Imagery Data
Google Maps curates high-resolution Street View imagery for areas worldwide. Street View Insights makes this geospatial imagery data available so that you can derive insights based on the analysis of specific physical assets: utility poles and street signs.
To use Street View Insights you write queries or develop machine learning models that return statistical insights about the Street View data. These insights let you answer questions such as:
- What is the lean angle distribution of utility poles in a specific district?
- What is the count of operational street signs along a new highway project?
- How many utility poles with a height over X meters are present in a service area?
- Where is the highest concentration of utility poles that use the specific lamp make and model Y?
The aggregation and analysis of this data can support a multitude of use cases such as:
- Asset Inventory & Maintenance: Accurately locate, measure, and monitor the condition of physical assets like utility poles before storms or for routine inspection.
- Infrastructure Planning: Assess the existing density and characteristics of street signs and utility infrastructure for new developments or capacity upgrades.
- Safety and Compliance: Identify and prioritize utility poles that exceed a safety threshold for lean angle.
About Vertex AI
By making the analysis of geospatial imagery available through Vertex AI, Street View Insights lets you:
- Develop and deploy machine learning models to analyze imagery and uncover insights for your specific infrastructure needs.
- Use the same Vertex AI tools and framework that you are already using for your private AI workflows and custom model training.
- Harness the power of Google Cloud's AI platform for scalable, high-performance analysis of Street View image datasets with ease.