The world is frequently engulfed in flames, quite literally. In order to maintain a reasonable quality of life in the future, it is crucial to predict and address such disasters before they escalate. This is a global issue of immense proportions, and Alphabet, the parent company of Google, believes it can contribute to its resolution.
This week, Alphabet’s moonshot factory X officially introduced Project Bellwether, its latest endeavor to leverage technology in tackling major problems. In this case, the focus is on utilizing AI tools to swiftly identify natural disasters like wildfires and floods. If implemented effectively, this could revolutionize the response capabilities of first responders.
According to project head Sarah Russell, Bellwether is X’s ambitious initiative to comprehend and anticipate changes occurring across the planet. This would enable any organization, community, or business to ask more intelligent and timely questions about the natural and built environment. Russell emphasizes that applying AI to geospatial inquiries has historically been extremely challenging and costly. However, the team has successfully incorporated recent advancements in machine learning, along with solid engineering, to completely rethink the approach.
The unveiling of Project Bellwether coincides with the announcement that the United States National Guard’s Defense Innovation Unit (DIU) will be utilizing the organization’s “prediction engine.” The current technology has the potential to significantly reduce response times, which could otherwise result in extensive damage to both human life and property.
Colonel Brian McGarry of the National Guard highlights the current process, wherein analysts must spend considerable time sifting through images to locate those covering the areas most affected by natural disasters. Subsequently, they need to correlate these images with surrounding infrastructure, label relevant features, and only then can they identify significant damage and relay the information to first responder teams. This time-consuming process can lead to delays of hours or even days.
