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Google harnesses AI to combat wildfires and extreme heat

August 29, 2024 | Governmental Organization, Standing Committees, California State Senate, Senate, Legislative, California


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Google harnesses AI to combat wildfires and extreme heat
In a recent government meeting, officials discussed innovative strategies to combat the increasing frequency of wildfires and extreme heat events, emphasizing the role of artificial intelligence (AI) in enhancing emergency response efforts.

The meeting highlighted the success of SOS alerts, which have provided timely safety information to over 30 million people during 120 wildfire events globally in 2023. A key tool in this initiative is the wildfire boundary tracker, which utilizes AI and satellite imagery to map large fires in near real-time, updating every 15 minutes. This service is currently available in fire-prone regions of the U.S., Canada, Mexico, and Australia, with plans for expansion.

Collaboration with the U.S. Forest Service aims to implement the most significant updates to fire spread models in 50 years. This new model, powered by machine learning, will enhance the understanding of fire dynamics, aiding firefighters in training and operational effectiveness during large-scale incidents.

The discussion also addressed the rising public health concerns associated with extreme heat. In response, the introduction of extreme heat alerts provides critical information about impending heat waves, including safety tips and health considerations. Additionally, cities are being equipped with tools to combat urban heat islands. The tree canopy tool uses AI to identify optimal areas for tree planting, while the cool roofs tool maps solar reflectivity to guide urban planners in deploying reflective roofing solutions.

Looking ahead, the meeting underscored the potential of AI in emergency management through the development of early warning systems and predictive analytics. The Google Cloud AI platform is set to empower emergency management agencies to create custom predictive models that analyze extensive data sets, identify patterns, and generate actionable insights. This integration aims to enhance situational awareness and decision-making, ultimately contributing to more effective emergency responses and saving lives.

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