Image: Google
Google has released three Google Maps application programming interfaces (APIs) for developers to map solar potential, air quality and pollen levels. The three APIs apply artificial intelligence (AI) and machine learning, along with aerial imagery and environmental data, to provide up-to-date information about these three variables, enabling developers, businesses, and organizations to build tools that map and mitigate environmental impact.
The Solar API utilizes mapping and computing resources to design detailed rooftop solar potential data available for more than 320 million buildings across 40 countries including the United States, France and Japan. To obtain this data, the AI model extracts 3D information about roof geometry from aerial imagery, while considering past weather patterns and energy costs, enabling quicker installation of solar panels.
The Air Quality API shows air quality data, pollution heatmaps, and pollutant details for more than 100 countries around the world. The API validates and organizes several terabytes of data an hour from multiple data sources — including government monitoring stations, meteorological data, sensors and satellites — to provide a local and universal index.
Google Maps uses machine learning and live traffic information to predict different pollutants in an area at a given time. The Air Quality API offers companies in healthcare, the automotive market and other forms of transportation the ability to provide accurate and timely air quality information to their users.
The Pollen API shows current pollen information for common allergens in more than 65 countries. The API provides localized pollen count data, heatmap visualizations, detailed plant allergen information, and actionable tips for allergy-sufferers to limit exposure. To obtain this information, Google Maps uses machine learning to determine where specific pollen-producing plants are located.