Google has begun offering new sustainability APIs for the Google Maps Platform, that apply machine learning (ML) and artificial intelligence (AI), in conjunction with aerial imagery and environmental data to provide information on solar potential, air quality and pollen levels.
The company's Solar API uses mapping and AI to show solar potential for rooftops in, "320 million buildings across 40 countries, like the US, France and Japan".
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Google trained an AI model to extract 3D information about roof geometry from aerial images, along with details on trees and shade. The Solar API also accounts for weather patterns, energy costs, and more.
This API will help businesses see how much sunlight a rooftop receives before visiting the area. Homeowners can use this information to guide them in installing solar panels.
The second API is built for Air Quality information. It shows pollution heat maps and pollutant details for more than 100 countries around the world.
The Air Quality API sources information from multiple sources, updating them every hour to provide a local index. It also accounts for traffic information such as congestion and car volume in an area. Google says it uses ML to predict different pollutants present in an area.
Lastly, the Pollen API shows current pollen information, accounting for most common allergies in over 65 countries. It includes a localized pollen count, heat maps, plant allergen information and tips to limit exposure.
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Google says it uses ML to predict where pollen producing plants may be located. It also calculates seasonality and the amount of pollen grains together with wind pattern information.
The company says that with these APIs, "businesses can access comprehensive and up-to-date environmental information to develop sustainability products and help people adapt to the impacts of climate change".
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