Initial deployment in Southern California will demonstrate how real-time, on-site intelligence can strengthen climate resilience and emergency response
San Diego Gas & Electric (SDG&E), Qualcomm Technologies, Inc. and the University of California San Diego’s Scripps Institution of Oceanography today announced Edge Alert Sentinel (EAS), a new collaboration that will bring artificial intelligence (AI) directly to the front lines of wildfire and extreme-weather response. Designed to detect and analyze rapidly changing conditions in real time, the initiative represents a new approach to environmental intelligence — processing critical data at the point of risk to help utilities and emergency responders act faster when it matters most.
While the initial deployment is in San Diego, the collaboration is intended to demonstrate how edge-based AI can support grid reliability, emergency preparedness and climate resilience.
Southern California faces some of the most complex wildfire and extreme-weather conditions in the nation, with Santa Ana winds, drought and highly varied terrain creating rapidly changing and often unpredictable risk. In these environments, conditions can shift in minutes, and delays are not an option. EAS will integrate environmental sensors, edge AI computing and atmospheric science to generate near-instant insights where conditions are unfolding — not minutes later in distant data centers. The first system is being installed on Mt. Palomar, where it will begin analyzing wind, weather and environmental data to provide earlier visibility into conditions that influence wildfire behavior and extreme-weather impacts.
“For nearly two decades, our region has avoided a catastrophic electrically caused wildfire because we chose to lead early and never stop looking ahead,” said Scott Crider, President of SDG&E. “Edge Alert Sentinel reflects that same mindset. By working with Qualcomm Technologies and UC San Diego, we’re bringing world-class technology and science together, so intelligence lives where the risk lives — on the front lines — and communities are safer because of it.”
EAS reflects a shared effort to anticipate tomorrow’s climate risks today — aligning utility operations, breakthrough technology and climate science into a coordinated approach designed to support faster, more informed decisions when seconds matter.
In parallel, Qualcomm Technologies and SDG&E are working to apply AI directly integrated on field devices and real-time connectivity to support automated inspections of critical utility infrastructure through autonomous aerial operations, extending the same intelligence-at-the-edge approach to physical grid assets.
Intelligence-at-the-Edge — Where Conditions Unfold
Traditional monitoring systems often rely heavily on remote cloud processing, which can introduce delays — particularly during severe weather or emergencies. EAS will process data at the point of collection, enabling rapid analysis even when connectivity is strained.
“Through this collaboration, we’re intending to bring real-time intelligence directly to the front lines of wildfire response,” said Nakul Duggal, EVP and Group GM, Automotive, Industrial and Embedded IoT, and Robotics, Qualcomm Technologies, Inc. “By combining on-site AI with advanced sensing and connectivity, we’re helping deliver faster, more reliable insights where conditions are changing — so responders can assess risk and act with greater speed and confidence.”
This on-site processing enables near-instant analysis, reducing delays that can cost critical time during wildfire response and helping utility responders move more quickly from observation to action during fast-changing conditions.
At the core of the deployment is a ruggedized edge AI gateway platform powered by the Qualcomm Dragonwing™ IQ9 processor, a high-performance, multi-core application processor that features a neural-processing unit capable of delivering up to 100 trillion operations per second. Using an MLOps platform from Edge Impulse, a Qualcomm company, on-device models help forecast conditions that could impact grid infrastructure in residential areas, to support more proactive decision-making for utility operators. Monitoring data and predictive alerts can be transmitted directly to SDG&E’s control center via its private cellular network.
These localized analytics and telemetry data will help identify emerging risks earlier, strengthening operational decision-making, safety and overall grid resilience.
Industry and Academia Unite to Deliver Actionable Intelligence
EAS unites complementary strengths across industry and academia:
- Qualcomm Technologies will provide advanced on-device AI processing capabilities and low-latency, edge-computing architecture to support SDG&E’s environmental intelligence, autonomous inspection and grid-resilience efforts at the edge.
- SDG&E will contribute operational expertise, grid infrastructure and weather-data networks.
- Scripps Institution of Oceanography will provide long-standing observational data and scientific expertise to enhance modeling and real-time analysis.
Together, the collaborators are building a continuous loop of live data, on-site AI analysis and actionable insights designed to translate rapidly changing conditions into timely action that enhance safety, reliability and grid resilience.
Why This Matters for the Region
By delivering intelligence directly at the point of risk, EAS is designed to reduce latency, improve preparedness and strengthen coordination across utilities and emergency responders — helping protect lives, communities and critical ecosystems in regions facing increasingly complex weather risks.
While developed in Southern California, the approach is designed to scale to other regions facing increasingly frequent and severe climate-driven events — from wildfires to extreme storms — where real-time, location-specific intelligence can improve how decisions are made under pressure.
“Scripps has been making real-time observations of atmospheric conditions throughout San Diego County since the turn of the millennium, building a uniquely rich dataset that advances our understanding of wildfire and extreme weather risk in Southern California,” said Frank Vernon, director of the University of California Scripps Institute of Oceanography High Performance Wireless Research and Education Network. “With this new onsite AI capability, we're moving beyond observation to predicting impact in real time — at the exact moment and place where danger emerges. That's what becomes possible when industry brings operational scale, real-world deployment experience, and urgent community needs together with academia's scientific rigor and long-term observational record.”
What’s Next
During the upcoming Public Safety Power Shutoff season, the companies will evaluate the performance of the initial Palomar Mountain deployment, a high-elevation site critical for wildfire and extreme-weather monitoring in the region, with plans to expand the technology to additional sites beginning next year. Insights from the pilot phase will inform expansion, enhanced modeling capabilities and broader regional applications, with a wider rollout targeted for 2027. The collaboration will also explore joint training and coordination opportunities to support emergency preparedness across Southern California and other regions facing similar risks.
Message funded by SDGE shareholders.