DeepWatcher Forest Fire Protection System
Forests will be protected from fires with DeepWatcher, an integrated Fire Alarm Prediction-Detection and Tracking System independently developed by Canovate with Artificial Intelligence (AI) and Deep Learning technologies. Thus, trees and wildlife will be safe.
In addition to being able to predict the possibility of a fire, DeepWatcher-AI stands out with its feature of quickly detecting the location of the fire at the first moment it breaks out, before it spreads, and informing the authorities. Additionally, detecting and prosecuting arsonists who deliberately set fires, as well as detecting illegal loggers, thanks to DeepWatcher, will increase the protection of forest resources..
DeepWatcher Capabilities
– AI based fire rapid detection and warning system
– Detection of sabotage, if any, in case of fire
– Smuggling detection to protect forest assets
– AI based Fire prediction system based on weather conditions
– AI based Creating a regional and temporal (weekly, monthly, annual, seasonal) prevalence probability map with recorded data
Deepwatcher can be easily integrated into forest watchtowers or connected to an adjustable mast
AI based forest fire rapid detection and warning system
DeepWatcher Thermal Radar monitors forests uninterruptedly, day and night, with infrared and daytime cameras, with the help of artificial intelligence and deep learning technologies, within a radius of 20 km, 360° panoramic horizontally and 90° vertically from near to far.
Equipped with advanced artificial intelligence algorithms, this radar system scans forest areas and detects newly emerging smoke or hot spots.
Fire, smoke or flame is determined in advance and an alarm is generated along with the location information of the point where the fire broke out on the map, ensuring that fire extinguishing teams are directed to the right point without wasting time.
Thanks to rapid intervention, the fire is taken under control before it grows.
Detection of fire smoke from the system interface with both a day camera and a thermal camera, and a sample image showing the location of the fire on the radar in the middle.
Close-up view of the detected smoke
Detection of sabotage, if any, in case of fire
Image showing the person who lit a fire from dry grass while walking around the forest area and started a fire
Another advantage offered by the Thermal Radar is its ability to detect fire sabotage situations. The system detects and tracks people and vehicles by constantly monitoring before and after a fire breaks out. In this way, while the cause of the fire is being investigated, it can be easily determined whether there was any previous sabotage and the identity of the people who committed the sabotage can be easily revealed.
Smuggling detection to protect forest assets
Another advantage offered by the DeepWatcher Thermal Radar is the fight against unauthorized felling of forest assets and smuggling.
DeepWatcher, which monitors the forests 24/7, day and night, with Infrared and daytime cameras, also prevents financial damage to the country by monitoring crimes such as illegal tree felling.
When a possible smuggling incident is detected, the system quickly generates an alarm and provides timely intervention by indicating the correct location to the relevant units.
The tree integrity of forests is constantly monitored
As seen in the middle area, the image of detecting that the integrity of the trees is broken and trees being cut down and creating an alarm system with the location
AI based fire prediction system based on weather conditions
In the forest area where the DeepWatcher system is installed, critical meteorological values (Temperature, Pressure, Humidity, Wind direction and intensity) are constantly measured with sensors integrated into the system. These data are taken instantly on-site and compared with set values to generate alarms regarding possible fire situations and to ensure that additional measures are taken.
AI based Creating a regional and temporal (weekly, monthly, annual, seasonal) fire probability map with recorded data
Example of mapping possible european forest fires
Since the meteorological data of the region where the system is installed will be recorded continuously in time, weekly, monthly, yearly and seasonal fire outbreak probabilities are calculated with artificial intelligence technologies, taking into account the regional conditions, and a temporal dynamic fire map of the region is created with constantly updated data. It is offered to fire teams.
DeepWatcher thermal radar, an innovative forest surveillance and control system, creates an effective line of defense against forest fires (before they break out or at the first moment they break out), sabotage incidents, smuggling and criminal elements.
In this way, an important step has been taken to protect natural resources and leave a clean environment for future generations.