Latest / Internet of Things with Fexingo: Connected Devices, Sensors, and Industrial IoT / How IoT Sensors Are Preventing Wildfire Damage to Power Lines
Transcript
- Lucas: You know, California recorded over 7,000 wildfires last year, and a growing share of them started not from lightning or arson, but from power lines. A single sagging conductor touching a dry branch can ignite a fire that burns through a hundred thousand acres. Luna: And that's what happened with the 2018 Camp Fire — PG&E's equipment sparked the deadliest wildfire in state history. So how do you prevent that when you have thousands of miles of lines in remote, dry terrain? Lucas: That's the exact question a handful of utilities are now answering with IoT sensors. Instead of patrolling lines with helicopters once a month — which is expensive and only gives you a snapshot — they're mounting small sensor modules directly on the conductors. Each module measures vibration, temperature, current, and even the angle of the line. Lucas: If today's conversation gives you a concrete sense of how this tech is being deployed, that's exactly what we're here for. And the way these episodes stay ad-free is listener support — you can find us at buy me a coffee dot com slash fexingo. No pressure, just wanted you to know that's how it works. Luna: Yeah, it's a small gesture that keeps this show independent. And we appreciate everyone who's chipped in. Lucas: Absolutely. So back to those sensors — one company leading this is a startup called Gridware. They've deployed about 50,000 modules across California and parts of Australia. Each module is about the size of a soda can and clamps onto the line. It samples data every 10 seconds and sends it via a low-power wide-area network to a central platform. Luna: So what exactly are they detecting? I mean, a line vibrating in the wind is normal — how do you distinguish that from a dangerous condition? Lucas: That's where the machine learning comes in. The sensors pick up high-frequency vibration signatures. A conductor slapping against another conductor — what's called 'conductor slap' — produces a very specific frequency spike. Tree contact sounds different. And a cracked insulator leaking current has its own electrical signature. The system learns the baseline for each line segment and flags anomalies. Lucas: In fact, during a 2024 pilot with a major California utility, Gridware's sensors detected a failing insulator on a line that had just been inspected two weeks earlier. Traditional inspection missed a hairline crack. The sensor caught it because the leakage current was already 50 milliamp higher than normal. Luna: So you're talking about catching failures that even human eyes miss. And presumably doing it in real time, not on a monthly rotation. Lucas: Exactly. The utility got an alert, dispatched a crew within hours, and replaced the insulator. Cost of the sensor module: about $200. Cost of replacing a transmission line after a fire: easily $10 million plus liability. Luna: And this isn't just California. Utilities in Colorado, Texas, and even in Portugal are testing similar setups. What's the regulatory push behind it? Lucas: In California, the Public Utilities Commission now requires utilities to submit wildfire mitigation plans that include real-time monitoring. That's a huge driver. Senate Bill 901, passed after the 2018 fires, essentially made utilities liable for fires caused by their equipment unless they can prove they took reasonable preventive steps. Sensors are becoming part of that evidence chain. Lucas: But there's a tension here. These sensors generate enormous amounts of data — each module sends a reading every 10 seconds, so for 50,000 modules, that's 432 million data points per day. Processing that and turning it into actionable alerts is non-trivial. Luna: So the bottleneck shifts from hardware to software. How are they handling that scale? Lucas: Most are using edge computing. The sensor module itself does some basic filtering — if vibration is within normal range, it doesn't even send the full waveform, just a summary. Only when something crosses a threshold does it transmit the high-resolution data. That reduces the load by maybe 95 percent. Luna: Makes sense. And I imagine false positives are a big challenge. A bird landing on a line could create a vibration spike. Lucas: Right, and the models are trained to recognize bird strikes versus conductor slap. They've gotten pretty good. Gridware claims less than one false positive per 100 modules per month. That's impressive. But it took years of training data to get there. Lucas: The bigger picture is that we're seeing a shift from reactive to predictive maintenance in the grid. Utilities have historically run on a 'fix it when it breaks' model. But with wildfire risk, that's no longer acceptable. Luna: And the cost is coming down. A few years ago, a sensor module like this would have cost $1,000 or more. Now it's $200 and dropping. That makes it viable to deploy on distribution lines, not just major transmission lines. Lucas: Exactly. Distribution lines are the ones that run through neighborhoods and wildland-urban interfaces. That's where most ignitions happen. So putting sensors on those lower-voltage lines is a game changer. Luna: Are there any limits? Like, what about lines in areas with no cellular coverage? Lucas: Good question. Many sensors use LoRaWAN or satellite backhaul. Some use mesh networks where modules relay data to a gateway every few miles. It's not perfect. In very remote canyons, you might still have gaps. But the coverage is expanding. Lucas: And there's another layer: cameras. Some utilities are pairing sensors with solar-powered cameras that snap a photo when an anomaly is detected. So the operator can see the branch or conductor movement visually. Luna: That feels like a good human-in-the-loop check. So the sensor flags it, the camera confirms it, then you dispatch a crew. Lucas: Exactly. And the crew knows exactly where to go and what to look for. That saves hours, which in fire season can be the difference between a small fix and a catastrophe. Luna: So where do you see this going in the next few years? Is there a point where every utility line in high-risk areas is monitored? Lucas: I think we'll get there within a decade. The economics align: a sensor module costs $200, but a single prevented fire saves millions. The California utilities are already investing billions in wildfire mitigation. This is a tiny fraction of that budget. Lucas: The challenge is interoperability. Right now, every vendor has its own platform. Utilities don't want to be locked in. So there's a push for open standards — something like the IEEE 1451 series for smart transducers. That would let a utility mix and match sensors from different manufacturers. Luna: And what about the data itself? Could it be used for things beyond wildfire prevention, like asset management or load balancing? Lucas: Absolutely. The same vibration data that detects conductor slap can also indicate mechanical wear over time. Utilities can plan replacements before failures occur. And the current data helps with load forecasting. So the ROI is broader than just fire risk. Luna: That's the dream of IoT, right? One sensor, multiple use cases. It's not a single-purpose device. Lucas: Exactly. And the data is accruing. After a few years, utilities will have a digital twin of their grid — a real-time model that shows the state of every component. That's the long-term vision. Luna: One thing I'm curious about: how do these sensors handle extreme weather? I mean, they're on lines that might be hit by lightning or buried in snow. Lucas: They're designed to be rugged — temperature range from minus 40 to plus 85 Celsius, waterproof, and they can survive a lightning strike nearby because they're non-intrusive. They clamp on, so they don't break the circuit. And they have their own power source — either a small battery that lasts five years, or a tiny energy harvester that draws from the magnetic field of the line itself. Luna: That's clever. So they're essentially self-powered and maintenance-free for years. Lucas: For the most part. Battery life is the limiting factor. In cold climates, batteries drain faster. Some vendors are experimenting with supercapacitors. But the trend is toward longer life. Lucas: I think what's exciting is that this is a real, deployable solution that's already preventing fires. In 2025, one utility reported that sensors caught three imminent failures that would likely have caused ignitions. That's three fires that didn't happen. Luna: It's a great example of IoT doing tangible good. Not just optimizing supply chains, but saving lives and property. Lucas: Exactly. And it's a reminder that the most impactful IoT applications are often the ones we don't see — sensors quietly monitoring infrastructure, keeping things safe. Luna: Alright, well, thanks for walking us through that. Next time someone tells you IoT is just smart fridges, you can point them to this episode. Lucas: Ha, exactly. And if you want to support more episodes like this, you know where to find us. Until next time, stay curious.