Awareness for the environment and the execution of actions focused on the planet conservation These are two of the objectives that affect the evolution of society in a transversal way, with multiple companies and organizations carrying out actions oriented in this same direction.
Google has been one of the last companies to make headlines for it. Taking advantage of the celebration of Google Cloud Next, The American company has presented three new APIs that allow it to offer users real-time information on the changes that are taking place on the planet in terms of the environment. These new functionalities are based on Artificial Intelligence and Machine Learning to provide different data that allow minimize the impact of climate change.
Forecast of the most common allergens
One of the consequences of the increase in global temperatures and greenhouse gas emissions is the increase in places where pollen-producing plants grow with its corresponding impact on all those people who suffer from seasonal allergies.
Google has gathered information on the most common allergens that are present in more than 65 countries and, based on them, offers the user detailed information about their presence in our location. Machine learning makes it possible to determine the main locations of the producing plants and together with the wind patterns to calculate the volume of pollen grains and their displacement.
The power of solar energy
The second of the APIs focuses on the potential of solar energy and its objective is to encourage the use of this energy, in line with the sunroof project that they launched in 2015 and that has allowed the company to have a large amount of data. Currently, it shows the information related to the solar incidence in more than 320 million buildings distributed in more than 40 countries.
Google has worked on an Artificial Intelligence model that allows extracting 3D information about the geometry of the roofs, relying on aerial images not only of the buildings, but also of the vegetation and shaded areas that he has been collecting in recent years.
The aggregated data set can be used in different directions. For example, the owners of these buildings have the possibility to check if their building meets the conditions to install solar panels and bet on sustainable energy as a power source. On the other hand, companies engaged in the installation of this type of technology They can also collect information about the best areas to promote this type of service, even without having to go to the area in question.
Air quality
The last of the three updates focuses on air quality, following the path that other applications already show us and that allows us to collect valid information for multiple actions. This API takes care of create pollution heat maps and different details related to this issue in more than 100 countries around the world.
To display these dashboards, it relies on collecting data sources like weather stations and different sensors that make it possible to provide a local index and, later, cross it with the information on traffic density in a specific area. Machine learning helps predict pollution patterns that may lurk in certain areas.