Edge AI in Smart Meters to Fight Wildfires and Power Outages

CAMBRIDGE, Mass. – February 02, 2026 – A groundbreaking software solution announced today by grid intelligence firm Sense aims to transform the humble smart meter into a frontline defender against power outages and catastrophic wildfires. The company's new Fault Detection Solution embeds advanced artificial intelligence directly into next-generation meters, providing utilities with an unprecedented, real-time view into the most vulnerable part of the electrical grid.

This new technology, powered by Sense's proprietary Waveform AI, is designed to detect hazardous conditions like electrical arcing, downed power lines, and failing equipment the moment they occur. By moving this intelligence to the 'edge' of the grid—the millions of endpoints in homes and businesses—the system promises to give utilities the critical, early warnings needed to prevent disasters, improve safety, and keep the lights on.

"Utilities need fast, accurate visibility into what's happening on the distribution grid," said Sense CEO Mike Phillips in a statement. "By moving intelligence to the edge, we're giving operators actionable insight the moment something goes wrong – without requiring new hardware or specialized field equipment."

A Critical Blind Spot in the Grid

For decades, the greatest challenge to grid reliability has been a fundamental lack of visibility. According to the U.S. Energy Information Administration, more than 90 percent of all power outages in the United States originate not on the massive transmission lines or at large substations, but on the local distribution grid. This sprawling network of poles, wires, and transformers that carries electricity down the final mile to consumers has historically been a 'black box' for utility operators.

Traditional fault detection systems are typically located upstream, providing a high-level view but little detail about the specific conditions on neighborhood circuits. When a fault occurs, finding its precise location often requires dispatching crews to patrol miles of power lines manually—a time-consuming, expensive, and often dangerous process, especially during severe weather. This operational gap leads to longer outages for customers and increased risk for utility personnel.

Sense's approach aims to eliminate this blind spot. By embedding its software in the very meters that connect homes to the grid, it effectively creates millions of intelligent sensors, all reporting back on the health of the local network in real time.

Intelligence at the Edge: How It Works

The technological heart of the new solution is what Sense calls Waveform AI. This software runs inside modern AMI 2.0 (Advanced Metering Infrastructure) smart meters, analyzing the high-resolution electrical data—the voltage and current 'waveforms'—at a rate of thousands of times per second. By scrutinizing these detailed electrical signatures, the AI can identify the subtle anomalies that signal a developing problem.

This 'edge computing' model, where data is processed locally at the meter rather than being sent to a central server, is a key differentiator. It eliminates latency, allowing for instantaneous detection. It also represents a significant strategic advantage for utilities. Instead of undertaking costly and complex projects to deploy new hardware like pole-top sensors or radio-based locators, utilities can activate this advanced fault detection capability as a software upgrade within their existing or planned smart meter rollouts.

This software-first approach maximizes the return on investment for the billions being spent on grid modernization, transforming the smart meter from a simple billing device into a powerful operational powerhouse for utility engineers and grid operators.

From Pilot Programs to Public Safety

The promise of this technology has already been validated in a series of utility pilot programs. According to Sense, the solution has successfully identified incipient faults that would have been invisible to traditional systems. These included early-stage problems caused by vegetation growing too close to power lines and previously undetected issues with aging field infrastructure—both of which are common precursors to major outages and potential fire starters.

The public safety implications are profound. In wildfire-prone regions like California and the American West, electrical arcing and downed power lines are a primary cause of ignition for some of the most destructive blazes. The ability to detect these conditions instantly and de-energize a line before it can spark a fire is a game-changer for risk mitigation. Furthermore, the system enhances safety for lineworkers, who can be alerted to dangerous arcing events before they arrive at a job site.

By pinpointing the exact location of a fault, the technology also dramatically accelerates restoration times. Utilities can dispatch crews directly to the source of the problem, reducing outage durations and minimizing the economic and social disruption that power failures cause.

The New Economics of Grid Modernization

For utilities, the business case for adopting such technology is compelling. The financial benefits extend far beyond improved reliability. By enabling precise fault location, the system drastically reduces 'truck rolls,' one of the most significant operational expenses for a utility, saving on fuel, vehicle maintenance, and labor hours. This operational efficiency directly impacts the bottom line.

Moreover, the data on equipment degradation provides a foundation for predictive maintenance. Instead of replacing equipment on a fixed schedule, utilities can prioritize replacements based on real-world conditions, extending the life of healthy assets and preventing the failure of those at risk. This data-driven approach to asset management optimizes capital spending and enhances overall grid resilience.

As regulators increasingly tie utility performance to reliability metrics like the System Average Interruption Duration Index (SAIDI), technologies that shorten outages become not just operationally desirable but financially necessary. In an era of increasing climate-driven threats and a complexifying grid, solutions that offer a cost-effective path to enhanced safety, reliability, and resilience are becoming essential tools for the modern utility. This level of granular insight is a crucial step in building a more robust and responsive energy infrastructure for the future.