Our solution directly aligns with Gap 2 : Real-time detection, monitoring, and analysis of threats and hazards, aiming to enhance response times to environmental threats and improve operational efficiency in critical areas like firefighting, pollution control, and wildlife monitoring.
CamIA, a winner of the EcoNum (Economie du Numérique) call for projects under the France 2030 funding plan, is a multi-use, multi-spectral, and multi-vector detection and alert Case aimed at addressing the increasing threats posed by climate change. Our solution is designed for early detection of hazards, such as wildfires, by enabling real-time monitoring. It can be deployed on fixed masts, drones, or our Helia tethered aerostat, offering a flexible, Plug&Play approach that eliminates the need for multiple products.
The Case is capable of detecting a variety of events simultaneously, such as early smoke detection or nighttime person detection, by integrating specific cameras tailored for several use cases. It significantly reduces energy consumption compared to current video surveillance systems, where cameras transmit continuous video streams to control centers, often requiring massive resources for storage then analysis with high energy costs.
Moreover, CamIA’s built-in AI enables real-time event detection, which is crucial in differentiating smoke from other visual phenomena, like fog or dust clouds. The system is designed with GDPR compliance in mind, processing only necessary data and avoiding the storage or transmission of personal images, thus promoting societal acceptance.
We are currently at TRL 8, with a fully qualified product through extensive real-world testing, including the SecurIT project (June 2023) and the ongoing Force 06 project (since June 2024), with near 100% true positives during summer 2024. Our solution has already been contracted in regions such as Loire and Thailand for wildfire detection. We are now in the industrialization phase, with our partner.
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Our objective in applying for the Direktion Awards is to increase awareness of our product, particularly in other European countries heavily impacted by wildfires. Having already validated our solution for wildfire detection, we now aim to industrialize it to protect European forests. One of our goals is to advance certification processes, including CE marking, APSAD certifications (quality of service awarded by CNPP), and continue applying industrial development approach also for our AI models ay higher level than recommended by the Artificial Intelligence Act.
Additionally, we focus on the protection of natural spaces, which are both an economic and cultural heritage. With better prevention, more protected areas can remain accessible for sustainable nature tourism. In high-tourism zones, our solution also aims to reduce the impacts of incivilities, such as wildfires caused by careless actions like cigarette butt disposal, which remain a significant fire risk. one use case under development is the detection of sea pollution especially close to coast.
Moreover, we seek to secure the forestry and wood industry. For example, the french industry is valued at €60 billion annually, which faces long-term losses due to wildfires (e.g., in Landiras, 30% of trees destroyed were under 15 years old and will not be harvestable for 20 years). As the demand for low-carbon construction materials increases, protecting this sector becomes increasingly critical.
Today, early detection of wildfires is primarily done by human spotters or cameras mounted on fixed masts, which have height limitations and require image analysis in control centers. This method is both inefficient and resource-intensive, especially in terms of human resources.
CamIA represents a breakthrough in wildfire detection. It is a compact Case equipped with multiple cameras (visible and thermal) and powered by our Embedded AI, which processes the images onboard in real-time. When a fire is detected, an alert is sent (typically on our web application) with the detection image and geolocation, a capability of doubt leverage thanks to the capability to center and zoom on the detection, enabling a fast response from the operator to validate and dispatch intervention forces.
It can be deployed on a variety of platforms (drones, aerostats, towers, fixed masts, etc.), offering flexibility in both application and deployment. The AI is trained to detect multiple types of events simultaneously, such as smoke, hot spots, people, and vehicles, expanding its versatility. Moreover once the high risk period of wild fires is ended our CamIA can be dismounted (2 screws) from the PTZ turret then integrated on the gimbal of drones or other high points for other use cases, like S&R or routable roads during floods, all the year. A key innovation of CamIA is the ability to deploy image processing directly near the sensors (edge computing). This allows us to extract only useful data at the source, ensuring efficient data transmission.
One of the main challenges overcome is performing this processing with minimal power consumption while keeping the system compact enough to dissipate energy efficiently.
Furthermore, the potential applications of CamIA are vast, especially when integrating multi-spectral sensors (visible or infrared), which provide more detailed information but require more complex processing.
Our solution addresses several key operational challenges met in firefighters’ activity, and other environmental monitoring and crisis management.
Forest fire response : Rapid intervention is crucial for combating wildfires. Our Case detects smoke at the earliest stages, sending alerts that allow firefighters to act long before the fire spreads, preventing it from becoming uncontrollable.
Expansion of surveillance coverage : Our Case can be deployed in remote areas without internet connectivity. It adapts to various communication systems (LTE, 4/5G, Satellite (soon), optical fiber if available), ensuring alerts are transmitted efficiently in challenging environments.
Autonomous monitoring : The Case operates 24/7 without the need for constant human oversight. It only requires human intervention when needed for critical actions, such as confirming alerts or conducting maintenance tasks (e.g., changing drone batteries or recharging helium for the Helia aerostat, not any action on High Points with PTZ turret).
Confidentiality : Protecting sensitive data is a top priority. Our system ensures privacy by only transmitting images associated with detected alerts and geolocation, never storing or transmitting unnecessary data. This ensures compliance with privacy regulations and maintains security.
Additionally, our solution reduces the environmental impact by utilizing low-energy edge computing, which processes data close to the sensor, avoiding the huge impact of the video streaming. The system's flexibility allows for a wide range of applications, from fire detection to monitoring pollution and wildlife, thus enhancing operational capacity in a variety of sectors.
Diverse cultural, generational, and technical strengths. Frédéric FERESIN (CEO) brings over 30 years of experience to ensure strategic alignment. Lionel DANIEL (CTO) contributes 10 years in AI and industry to guide technical decisions. Jérôme JACQUES excels in complex systems with 20+ years of experience. Jilane EL KHOULY leads marketing and sales. Oumaima El Moumen optimizes the deployment of the embedded SW. Ange Kokotakis focuses on AI, while Louis Vraie works on AI & full-stack development.
Diverse cultural, generational, and technical strengths. Frédéric FERESIN (CEO) brings over 30 years of experience to ensure strategic alignment. Lionel DANIEL (CTO) contributes 10 years in AI and industry to guide technical decisions. Jérôme JACQUES excels in complex systems with 20+ years of experience. Jilane EL KHOULY leads marketing and sales. Oumaima El Moumen optimizes the deployment of the embedded SW. Ange Kokotakis focuses on AI, while Louis Vraie works on AI & full-stack development.