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California adopts ALERTCalifornia, an AI system using over 1,000 cameras, to rapidly detect wildfires and alert first responders.

The state of California has turned to artificial intelligence (AI) in its ongoing battle against wildfires. More than 1,000 cameras, strategically installed throughout the region, feed their footage into an AI system named ALERTCalifornia. This technology aims to rapidly detect emerging wildfires and alert first responders.

A recent success story of the AI program comes from the Cleveland National Forest, approximately 50 miles east of San Diego. At 3 a.m., the ALERTCalifornia system detected a fire, allowing rapid response teams to arrive and douse the flames within 45 minutes, as confirmed by Cal Fire.

This groundbreaking technology is a result of collaboration between the University of California San Diego (UCSD) engineers and DigitalPath, a company situated in Chico, California. Together, they established a network of 1,038 cameras, each capable of rotating 360 degrees, set up by various public agencies and power utilities.

Since the program's inception on July 10, there have been instances where the AI has identified potential fires before any 911 calls were received. Cal Fire, while acknowledging these successes, notes that a full evaluation of the system's performance is still underway.

Neal Driscoll, of UCSD, emphasized the preliminary nature of findings, indicating that more data is needed to draw any definitive conclusions. Yet, the broader hope for this technology is clear: to offer a model that can be replicated in regions worldwide, especially as the frequency and intensity of wildfires increase.

Developed by engineers at the University of California San Diego using AI from DigitalPath, a company based in Chico, California, the platform relies on 1,038 cameras put up by various public agencies and power utilities throughout the state, each one capable of rotating 360 degrees at the command of remote operators.

Suzann Leininger, a Cal Fire intelligence specialist based in El Cajon, points out the global applicability of this system. Its relevance is heightened given the dramatic shift in fire patterns and climate change impacts witnessed globally.

According to US News, an integral component of ALERTCalifornia's evolution is the machine learning process. As the system identifies potential fires, specialists review and confirm its accuracy, helping to refine the AI and reduce false detections. Through this process, Driscoll mentions that the system's accuracy has witnessed improvements in just a few weeks.

Beyond mere detection, the platform collects a wealth of data, such as aerial surveys, infrared data via airplanes and drones, and measurements of environmental parameters during winter. This wealth of information, which is made available to private companies and academic researchers, presents possibilities for enhancing AI applications in environmental studies.

Given the urgency of addressing wildfires and the broader climate crisis, leveraging technology like ALERTCalifornia becomes paramount. Driscoll emphasized the collective responsibility to harness technology in mitigating these challenges.

Eunice is a sustainability writer whose passion is sharing accessible eco-friendly practices with GreenCitizen's global readership. She enjoys birdwatching during her downtime, often deriving inspiration from nature's resilience. An enthusiastic cyclist, she is also an ardent advocate of eco-friendly transport.

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