Sensor fusion multispectral analysis diagram

Vision Nest

Our integrated fire detection systems provide advanced, continuous wildfire monitoring, leveraging thermal imaging, high-resolution cameras, and smoke sensors. The core of our system, powered by proprietary machine learning algorithms, analyzes data from Vision Nest alongside satellite data for rapid fire threat identification. The Hybrid Vision Nest enhances this capability, utilizing autonomous drones to broaden surveillance and ensure comprehensive coverage. Adopting a camera-agnostic approach, our platform accommodates a wide range of devices, including your existing cameras. Equipped with an intuitive interface, it offers immediate alerts and actionable insights, enabling a swift response to mitigate wildfire risks effectively.

Sensor fusion and multispectral analysis

Using a Multispectral Sensor System

Our multispectral sensor system captures diverse environmental data across multiple wavelengths, enhancing wildfire detection accuracy and speed.

ML algorithm accuracy

Precision and Accuracy of ML Algorithms

Our machine learning algorithms provide high precision and accuracy, minimizing false alarms and ensuring efficient resource allocation during fire incidents.

Satellite data for wildfire detection

Integration of Satellite Data

Our system enhances wildfire detection by integrating satellite data, addressing its traditional gaps with ground-based insights for comprehensive coverage and improved reliability across diverse environments.

Continuous monitoring

Continuous, Monitoring in Remote Areas

We offer continuous, 24/7 monitoring, especially in remote areas, ensuring constant surveillance and improved response times to wildfires in hard-to-reach locations.

Camera Agnostic

Vision Nest

Extended Nest