Client Description and Challenge
Cellnex, a leading telecommunications infrastructure company, faced the challenge of improving early wildfire detection. Wildfires are a growing global problem, causing extensive damage to nature, wildlife, and communities. Every year, thousands of acres of forests and natural areas are affected. Early detection is essential to prevent their spread and minimize damage, but current monitoring methods, such as satellites and drones, have limitations due to cloud cover, autonomy, and image resolution.
Project Overview
Dive collaborated with Cellnex to develop a computer vision solution called Nature Vision, which analyzes and monitors in real-time, 24/7, for early fire detection, covering large areas with smart cameras on towers and hot air balloons. Once a fire is detected, the system provides monitoring and prediction of the most probable routes of spread, as well as diagnosing the most effective intervention in terms of location and timing to prevent its spread.
Solutions Implemented
To address the challenge, Dive implemented an innovative and efficient solution for early wildfire detection using a combination of helium balloons, surveillance towers, satellite imagery, and deep learning-based image recognition technologies under an edge computing model.
The system analyzes 360° images using machine vision techniques, and when signs of a fire are detected, the images are taken at a higher frequency and sent to a data processing center for more detailed inspection before alerts are issued. This allows for a quick and effective response to wildfires.
Technology for Specialized Services
Our models are based on Deep Learning techniques. These algorithms identify patterns in the images to predict whether there is a wildfire. One of the challenges is collecting datasets with the necessary variability. For this, we use Generative AI techniques (Stable Diffusion, Dall-E) to generate more data volume with the different scenarios we want to differentiate.
The combination of aerial imagery and AI allows Dive to monitor large areas and collect data to be analyzed in real-time, aiding timely decision-making.
Results
The implementation of the Nature Vision solution bolstered safety and early fire detection, preventing and reducing damage, risks, and costs associated with wildfires. The ability to analyze and predict the fire’s spread routes in real-time significantly improved the response capability of authorities and emergency teams.
Why Dive?
Dive stands out for its personalized approach and ability to develop AI solutions that address specific industry challenges. Our mission is to transform our clients’ operational processes, maximizing efficiency and productivity through innovation in artificial intelligence and advanced technologies. With Dive, companies not only adopt cutting-edge solutions but also prepare for a more efficient and competitive future.
Working with Dive has been crucial in improving our wildfire detection and response capabilities. Their computer vision solution has allowed us to act more quickly and effectively, minimizing environmental damage and risks to communities.
