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In today’s climate, it’s becoming increasingly rare to go more than a short time without encountering news related to wildfires. Arvind Satyam, co-founder and chief commercial officer of Pano AI, emphasizes that these incidents can no longer be contained to a specific season. His company leverages deep learning artificial intelligence (AI) alongside advanced computer vision to automatically detect, verify, and classify wildfires in real time.
Satyam elaborated on Pano AI’s mission during a discussion with Paul Gerke from Factor This at the DISTRIBUTECH (DTECH) event in March, highlighting how the company integrates cutting-edge technology—such as AI and ultra-high-resolution cameras—to furnish actionable intelligence for fire agencies, utility companies, and other relevant stakeholders.
Ongoing communication with key individuals, including fire chiefs and personnel at utility operations centers, has shaped Pano AI’s approach to wildfire detection. “Feedback has indicated a strong desire for better situational awareness and improved visibility regarding fire incidents,” Satyam noted. “Key questions include the fire’s location, real-time developments, and how to allocate resources most effectively.”
Pano AI endeavors to provide a comprehensive, 360-degree perspective—hence the name, which invokes a panoramic view—of wildfire threats.
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According to Satyam, the utility sector is increasingly seeking tools that allow them to differentiate between incidents caused by utility operations and those stemming from natural events. This understanding can foster proactive responses, including resource allocation and measures to preemptively de-energize areas while considering community safety.
Pano AI, currently operational in ten states, has recently announced a partnership with Arizona Public Service (APS) to extend their services to thirty locations across Arizona. As the capabilities of artificial intelligence continue to evolve, Satyam believes its applications within the grid will expand.
“AI is increasingly effective in detecting incidents, often in remote locations and sometimes even before they are visible to the human eye, thanks to deep learning techniques utilizing a dataset of over a billion images,” he shared with Factor This. “This technology enables us to observe smoke from considerable distances, whether in mountainous regions or arid environments. Our systems are deployed in challenging terrains, including the Pacific Northwest, and can even detect heat signatures in the dark. Additionally, we integrate satellite data, enhancing our AI capabilities even further.”
Satyam added, “The predictive aspects of AI can also significantly elevate our understanding and management of wildfires when we synthesize various data inputs.”
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www.renewableenergyworld.com