“Early wildfire detection sits at the crossroads of several transformative trends in cleantech. Advances in AI, IoT sensors, nanosatellites, and edge computing are converging to shrink the wildfire detection window from hours to minutes; a difference that can determine whether a blaze consumes 10 acres or 10,000.

However, many agencies and utilities deploy disparate systems that rarely “talk” to one another, a gap that’s slowing widespread adoption.

Innovation is abundant, but uptake is constrained by funding limitations, operational silos, and integration challenges, rather than a lack of technology. Still, pressure from insurers and liability exposure is driving more organizations to invest in early detection as a form of financial risk management. Winners will be those who integrate detection and suppression into seamless systems, bridging data, automation, and physical firefighting capability.”

– Sunena Gupta

Interview with Sunena Gupta, Cleantech Group

By Suzanne Forcese

WT: Please introduce yourself to our viewers giving us a brief bio, your position at Cleantech Group and your area of expertise.

Gupta: I am an Associate at Cleantech Group, a global market intelligence and advisory firm focused on climate, energy, and sustainability innovation. I lead our research on resources and environmental management.

My work supports investors, corporations, and other decision-makers by analyzing where climate and sustainability markets are headed particularly across climate resilience and adaptation, water and wastewater, environmental monitoring, and sustainable natural resource development.

I focus on early-stage technologies and startups, building market landscapes, assessing investment and market entry opportunities. I have experience across adjacent climate technologies such as grid resilience, data centers, green hydrogen, sustainable aviation fuels, and mining exploration, and I regularly translate complex insights into clear, actionable perspectives for client briefings and industry events.

WT: The headlines are everywhere --"Millions at Risk in Australia"; "One Year After in LA Recovery is a Battleground"; "Tens of thousands will die from wildfires in the US Over the Next 25 Years" "Europe Experienced Its Worst Wildfire Season"; "Wildfires are Blazing Across Africa" ... This is a global crisis that cannot be ignored.

Gupta: Wildfire Tech is certainly one of the biggest topics we have been focusing on recently at Cleantech Group, and an exciting one innovation-wise.

WT: Why are wildfires more than an environmental challenge? What are the structures, agencies, etc. that are impacted? Are insurers putting pressure on innovation?

Gupta: Wildfires hit public health through smoke exposure, housing through displacement and uninsurable homes, energy systems through grid shutoffs, and local governments through lost tax revenue and spiraling recovery costs. Unlike some other natural disasters, wildfires don’t just happen and move on but they keep coming back to the same places, year after year.

Utilities are now on the front line because of ignition liability. Insurers are pulling back from entire regions.

Mortgage markets and real estate values are being reshaped.

Even employers are affected when smoke shuts down outdoor labor or schools close for weeks at a time.

Once you zoom out, it becomes clear that wildfire is a macroeconomic and governance issue rather than just a climate one.

Insurers are absolutely putting pressure on innovation, and in my opinion, they’re the most powerful force in the system to get the needle moving right now. In many regions, insurers are acting faster and more decisively than policymakers. Beyond pricing risk, they are forcing decisions by demanding proof of mitigation, narrowing coverage, or walking away entirely. That’s why the market is moving away from standalone detection tools and toward integrated systems that can show real impact: earlier detection, faster response, better allocation of resources. If technology can’t demonstrate avoided loss, it’s going to struggle to scale, no matter how impressive it looks in a pilot.

WT: How is this world phenomenon changing the perspective? What needs to be explored?

Gupta: We’re seeing a shift in how wildfires are understood and planned for. Rather than episodic disasters, they’re being increasingly treated as a persistent condition that has to be managed continuously in certain regions. 

The key question is no longer “How do we respond to this fire?” but “How do we manage repeated exposure across entire portfolios of assets, communities, and infrastructure over decades?” That framing changes how risk is priced, how capital is allocated, and what kinds of solutions are considered viable.

What still needs much deeper exploration is how these systems actually work together.

We have an abundance of technology, but there is an issue of fragmentation. Tools are often deployed in isolation, while coordination across agencies, utilities, insurers, and emergency services remains slow and structurally misaligned.

There are also major blind spots. Smoke remains vastly under-accounted for, despite turning wildfires into population-scale public health and economic events far beyond burn areas.

Additionally, recovery continues to be treated as an afterthought. Delayed damage assessment, insurance disputes, and permitting bottlenecks routinely turn rebuilding into a second crisis. Until recovery and health impacts are fully integrated into how we define wildfire risk, upstream resilience efforts will remain incomplete.

WT: What are the transformative trends surfacing across the tech landscape? What are the gaps that need to be addressed? What are the obstacles? What are you forecasting for 2026?

Gupta:1. Solution stacking is the defining trend

We’ve largely solved the question of how to detect fires early, but the more consequential question is what happens in the minutes immediately after detection. I’m starting to see interesting momentum from companies actively stitching detection and suppression together. For example, Dryad’s ultra-early detection was already incredibly powerful, but what really stands out to me is that Dryad is explicitly building toward autonomous suppression through its drone program. Seneca is another great example. They are building an integrated system that links early detection with autonomous or semi-autonomous suppression in a single workflow. That kind of end-to-end design matters because it reduces handoffs, where crucial minutes are often lost in wildfire response.

2. Suppression remains the clearest gap and the biggest opportunity.

This is where the avoided-loss logic is strongest, and also where deployment is hardest. We’re seeing aerial suppression shift from piloted aircraft to autonomous or semi-autonomous systems capable of operating in smoke, wind, and darkness, alongside ground robotics taking on specific high-risk roles like reconnaissance and perimeter work. These systems are capital intensive, but when a single wildfire routinely costs millions to contain, the economics increasingly justify faster, more automated response.

3. If suppression is about speed, asset protection is about scale

Two distinct models are emerging. The first is data-led vegetation intelligence, where earth observation and AI are used to identify where clearing, trimming, or prescribed burns will have the greatest impact. Companies like Overstory and Gridware have built strong utility partnerships by translating wildfire risk into actionable maintenance and compliance decisions. The second model is mechanized treatment, led by innovators like Burnbot, which brings precision and repeatability to fuel reduction and prescribed fire, addressing one of the biggest bottlenecks in prevention: labor and capacity. What’s notable is how quickly these solutions are moving out of pilot mode as insurers and utilities convert risk models into real budget line items.

4. California will remain a critical testbed, but no longer the only one that matters

Another dynamic I think is often under-discussed is that wildfire innovation has historically been very California-centric, and that’s starting to change. California has been the natural proving ground since fire risk is extreme, budgets are larger, regulatory pressure is real, and success there is a powerful credibility signal. However, what scales in a state with dense connectivity, tower access, and strong public funding doesn’t automatically translate to more remote, lower-resource, or globally diverse fire contexts. Now that the wildfire tech market is getting more saturated, accessibility, usability, and adaptability to different governance and resource contexts are becoming just as important as technical sophistication. For example, Satellites on Fire is a great innovator in that regard. By fusing public satellite data, cameras, and community reports and pushing alerts through WhatsApp and SMS, they’ve dramatically lowered the barriers to adoption in regions where new infrastructure simply aren’t realistic in the short term. They have homed in on the idea that wildfires aren’t waiting and neither can the tech, which has allowed them to scale rapidly across Latin America and given them an edge in south-to-south technology transfer.

Looking ahead to 2026, my view is that the market will decisively favor platforms over point solutions. The winners will be technologies that sit directly in utility, insurer, and agency workflows and can prove faster containment, reduced losses, or improved recovery outcomes. Suppression investment will continue to accelerate, asset protection will scale fastest where ROI is clearest, and insurance pressure will increasingly determine which solutions move from pilots to standard practice. 

WT: Where are you seeing innovation?

Gupta: From the Forest Floor: IoT and Gas Sensors

Dryad is a key example of a ground-up approach. The company deploys solar-powered, AI-enabled gas sensors in forests to identify trace gases released in the earliest stages of combustion, long before flames are visible. By connecting thousands of sensors via an IoT mesh network, Dryad’s system can detect fires within minutes, a dramatic improvement over camera or satellite-based models that can take hours.

What’s compelling is the company’s ambition to combine detection and suppression through “SilvaGuard,” an autonomous drone system designed to extinguish small fires immediately after detection. If proven at scale, this model could represent a paradigm shift: moving from alert-based systems to active wildfire prevention ecosystems.

However, sensor networks can face operational hurdles: dense deployment requirements and calibration needs make them most suitable for high-risk, high-value regions where the economics of early detection are easiest to justify.

From Space: Satellites and AI-Driven Thermal Intelligence

Orbiting above, innovators like OroraTech and ICEYE are redefining what’s possible from space.

OroraTech, spun out from the Technical University of Munich, has developed a thermal-infrared nanosatellite constellation capable of identifying fire hotspots as small as four square meters, even through smoke or at night. Its biggest differentiator is on-orbit AI processing where data is analyzed directly in space within minutes, instead of waiting for downloads to ground stations that can take over an hour. This dramatically reduces the time from ignition to alert.

OroraTech’s coverage also fills what it calls the “afternoon gap,” when most public satellites miss critical activity due to orbit schedules. With plans for a 100-satellite network, it’s on track to deliver near-continuous global wildfire monitoring, a leap toward predictive, autonomous risk management.

ICEYE, based in Finland, has taken a complementary approach using Synthetic Aperture Radar (SAR) satellites. Its technology penetrates smoke and clouds, providing near-real-time mapping of fire damage even when optical imagery fails. During the 2025 Los Angeles wildfires, ICEYE achieved over 99% precision in identifying destroyed structures, feeding rapid data to emergency managers and insurers within 24 hours, a stark contrast to traditional methods that take weeks.

The company’s scale is unmatched, with over 50 active satellites and production ramping toward 150 per year. While ICEYE’s model is more capital-intensive, it’s one of the few offering both satellite manufacturing and data services, giving it a defensible market position.

From the Hills: Smart Cameras and Visual Intelligence

Pano AI brings precision and immediacy through dual ultra-HD cameras mounted on towers, delivering 360° coverage and scanning every minute. These systems have proven capable of detecting fires within 3–15 minutes in regions like Colorado and Oregon.

While camera technology itself isn’t new, Pano’s differentiator lies in AI-powered verification that reduces false positives and enhances reliability. Its partnerships with utilities and over 250 first-responder agencies underscore strong market traction in the U.S.

However, scalability is a challenge: each camera station can cost around $50,000 per year, limiting deployments in resource-constrained regions. Moreover, reliance on human validation in its alert process slows automation, a gap that competitors leveraging fully AI-driven models are quickly closing.

From the Cloud: Data Fusion and Accessibility

At the opposite end of the spectrum, Satellites on Fire (Argentina) is building a bridge between sophistication and accessibility. Rather than investing in proprietary hardware, it fuses public satellite feeds, camera inputs, and community-sourced reports into a unified AI platform that pushes alerts via WhatsApp and SMS, a clever adaptation for low-connectivity regions.

This approach democratizes wildfire intelligence, offering near-real-time alerts every five minutes at a fraction of the cost of more hardware-heavy systems. While technically replicable by larger firms, the platform’s community network of 50,000+ contributors create a feedback loop that strengthens its models over time, an example of innovation grounded in inclusivity rather than capital intensity.

WT: Please tell us about the Wildfire Tech discussion you will be hosting. What's on your agenda?

Gupta: I am hosting a discussion titled Outpacing the Flames, which will build on much of what I have highlighted above: the move toward integrated solutions, the pressure to prove real-world impact, and the challenge of scaling beyond pilots. What makes this discussion especially valuable is the range of perspectives I will bring together from the three different speakers. XPRIZE Wildfire brings a frontier, systems-engineering view of what it takes to move from promising prototypes to integrated solutions. Tokio Marine Group offers the insurer lens, which is increasingly shaping adoption by demanding measurable risk reduction and scalability. Dryad Networks provides the on-the-ground innovator perspective of what it actually takes to deploy technology, detect fires earlier, and close the loop toward suppression.

WT:What’s next on ‘The Innovation Frontier’?

Gupta:The frontier of wildfire detection lies not in any single technology but in system integration. The next generation of innovators will combine detection, forecasting, and suppression into continuous, autonomous ecosystems.

In the next decade, the most competitive systems will pair AI-driven predictive models with automated drone and satellite coordination, achieving sub-five-minute detection-to-response cycles. These solutions will likely become mandated for critical infrastructure and standard practice in high-risk regions.

Additionally, cross-sector convergence is reshaping investment and resilience strategies. Dual-use applications such as wildfire detection tech repurposed for defense or flood monitoring, are attracting more stable funding and insulating companies from policy volatility. Tech giants like Google’s FireSat, NVIDIA, and IBM are entering the space, bringing massive computing power and capital that could accelerate the path from pilot to planet-scale deployment.