How IoT sensors and machine learning help identify wildfires risks earlier
Wildfires are becoming one of the most significant environmental challenges across many parts of Europe. Rising temperatures, prolonged droughts and changing weather patterns are increasing both the frequency and intensity of wildfires, placing millions of hectares of forests and natural areas at risk every year.
Although Switzerland is less exposed than southern European countries, prolonged dry periods have increased wildfire risks in several regions, particularly in mountainous and forested areas. For public authorities, infrastructure operators and land managers, the difference between a contained incident and a large-scale wildfire often comes down to minutes.
Traditional detection methods continue to play an essential role, but on their own they are no longer sufficient to provide the level of responsiveness required in increasingly complex environmental conditions.
This is where advanced sensor-based technologies can transform wildfire management, helping organisations move beyond reactive firefighting towards proactive, early intervention.
When every minute counts in forest fire protection
Climate change is creating increasingly favourable conditions for wildfires throughout Europe.
Higher temperatures, extended periods of drought and changing vegetation patterns significantly increase both the likelihood and severity of fires. At the same time, many forests are located in remote areas that are difficult to access and challenging to monitor continuously.
Across the Securitas Group, organisations responsible for managing large forest areas and critical natural environments have been looking for more effective ways to detect potential fires before they escalate.
The challenge is clear: identifying risks as early as possible.
Traditional monitoring methods—including patrols, CCTV cameras and satellite imagery—often detect fires only after smoke or flames have already become visible. In addition, mountainous terrain, dense vegetation and natural obstacles frequently create "shadow zones" that cannot be effectively monitored using conventional technologies.
By the time a fire becomes visible, valuable response time may already have been lost, particularly in remote locations where emergency intervention can take longer.
From detection to anticipation: the real challenge
The real challenge is not simply detecting fires.
It is detecting them early enough to make a meaningful difference.
Traditional systems are primarily reactive. Cameras identify smoke. Satellites detect heat signatures. People report visible flames. Under dry and windy conditions, however, a fire may already be spreading rapidly before any of these systems generate an alert.
This is why organisations increasingly require solutions that can:
- Detect the earliest signs of wildfire risk before flames spread.
- Operate autonomously in remote environments.
- Reduce the need for continuous human monitoring.
- Minimise false alarms.
- Support a sustainable, long-term prevention strategy.
Beyond early detection, the system must also be capable of continuously monitoring large forested areas, providing reliable real-time information, integrating with existing emergency response structures and operating effectively in environments with limited communications or electrical infrastructure.
At the same time, the solution must remain robust, energy efficient, cost-effective and easy to maintain.
Many natural environments simply cannot support traditional security infrastructure at scale.
The challenge is therefore to combine advanced detection capabilities with practical, field-ready deployment—without increasing complexity for emergency services or operational teams.
IoT sensors that learn the “scent” of the forest
To address these challenges, the Securitas Group has developed innovative solutions based on IoT sensors enhanced with machine learning capabilities.
Rather than relying solely on predefined thresholds, these sensors gradually learn the natural chemical and environmental profile—or "scent"—of the forest where they are installed.
Over time, they establish a detailed baseline of what constitutes normal environmental conditions for that specific location.
The sensors continuously analyse environmental data, comparing subtle changes in air composition and atmospheric conditions with an extensive laboratory-developed database containing fire signatures associated with different vegetation types.
When an anomaly indicating an elevated wildfire risk is detected, the system automatically generates an alert and transmits it to the monitoring centre.
Several key design features make this approach particularly effective:
- Machine learning–driven detection → sensors adapt to local conditions instead of relying on fixed thresholds
- Solar-powered operation → enabling autonomous use in remote areas without external infrastructure
- Automatic alerting → anomalies are transmitted instantly, without requiring on-site monitoring
Day-to-day operation: how technology and people work together
In daily operation, the system is designed to integrate seamlessly into existing monitoring and emergency response processes.
Sensors are strategically deployed throughout protected forest areas where they operate continuously using solar power.
As they collect environmental data, they progressively refine their understanding of what constitutes normal conditions within each specific location.
Whenever abnormal changes in air composition or other indicators associated with wildfire risk are identified, the system automatically generates an alert.
The alert is immediately transmitted to the monitoring centre, where operators assess the information, determine its priority and notify the appropriate stakeholders, including operational teams, public authorities or emergency services when necessary.
Response teams can then be deployed much earlier than would be possible using conventional detection methods alone.
This workflow significantly reduces the need for continuous manual monitoring in the field.
Technology provides uninterrupted surveillance while people remain responsible for interpreting information, making operational decisions and coordinating emergency response.
Impact: Improved sustainability, prevention and faster intervention
The benefits of this approach are both operational and strategic.
For organisations responsible for protecting forests and natural environments, intelligent monitoring delivers measurable improvements across several areas.
These include:
- Earlier detection, enabling faster intervention before fires escalate.
- Improved sustainability, with solar-powered sensors reducing infrastructure requirements and environmental impact.
- Scalable deployment, making it possible to monitor extensive forest areas and remote natural environments.
- Enhanced risk management, through continuous environmental monitoring and real-time operational insights that support more informed decision-making.
Beyond helping reduce environmental damage, earlier intervention can also help limit disruption to infrastructure, nearby communities and economic activities.
Conclusion: from reacting to fires to helping reduce the risk
Wildfires will remain a significant environmental challenge for many countries in the years ahead.
However, as innovation across the Securitas Group demonstrates, combining IoT technology with machine learning has the potential to fundamentally transform how organisations monitor, detect and prevent wildfire risks.
By learning the unique environmental characteristics of each forest and continuously monitoring subtle atmospheric changes, intelligent sensors enable earlier detection, faster decision-making and more effective intervention.
Rather than replacing people, technology empowers them with better information, earlier warnings and greater situational awareness—helping organisations move from reacting to fires towards actively reducing the risk before they occur.
Let’s explore what this could mean for you
If you are responsible for protecting forests, critical infrastructure or large natural areas, early detection is no longer simply a technical consideration.
It is becoming a strategic priority.
As part of Securitas AB, Protectas combines local expertise with global innovation to help organisations explore intelligent monitoring solutions tailored to their operational environment, risk profile and long-term objectives.
If you would like to learn more about how connected technologies and advanced sensing solutions could strengthen your wildfire risk management strategy, our experts would be pleased to discuss your specific requirements.