Thermal imaging & vision systems These permanently observe a specific forest


area within a radius of up to 20 kilometres. Depending on the system, they need a maximum of two minutes to monitor a radius of 360 degrees. With the help of algorithms specially developed by Paratronic, the system is able to recognise and localise fire sources on the basis of the recorded images and to provide real-time information for appropriate options for action. In this way, ADELIE ensures efficient planning and control of the fire brigade to protect our living space and, last but not least, to protect buildings, power lines, telecommunication lines, road or rail infrastructure.


APPLICATION The ADELIE system is composed of at least two surveillance points that are networked together. Each surveillance point consists of two detection cameras and an additional camera that serves to eliminate doubts. Four Gigabit Ethernet cameras from IDS are integrated per ADELIE detection camera. Thus, a total of eight IDS cameras are used per surveillance point. These monitoring points allow 360° monitoring, with each azimuth visualised approximately every two minutes. Automatic monitoring of the observed natural area takes place around the clock, 24 hours a day, seven days a week.


The system is connected to a processing unit whose software contains artificial intelligence-based image processing algorithms. The programme developed by Paratronic registers, compares and analyses the images provided by the cameras. Long


before a tree burns, smoke is released from the surrounding grass and scrub. By comparing the images and using taught-in features, the system detects the rising smoke. As soon as this smoke is visible from the monitoring point, ADELIE triggers an alarm. This phase is called automatic fire and forest fire detection. The operator on duty then controls the doubt-removal camera remotely and checks the type of detection. They locate the source of the fire on a map by means of triangulation and informs the control centre, which initiates the fire-fighting measures. At the same time, all information, images and


knowledge gained by the AI are transmitted to the fire alarm centre or the fire control centre without delay. With the help of the real-time visualisation of the event, the localisation of the source of the fire on a digital map and various augmented reality functions, the context, extent and development of the fire can be immediately visualised there and appropriate fire-fighting measures can be taken. A remote- controlled video camera completes this system. This is used to verify and monitor the fire until the first fire-fighting unit arrives and enables the fire to be tracked from the outbreak until it is extinguished. “The IDS cameras play an important role in the operation of the ADELIE system. They have the task of continuously filming the forest azimuth by azimuth and providing the software with these images in real time,” underlines Edouard Bouillot, director projects and innovation at Paratronic. When choosing the appropriate model for the automatic forest fire detection system, the decision was made in favour of a Gigabit Ethernet camera from the SE series from IDS. “Our system uses the UI- 5240SE-NIR-GL model,” explains Loïs Carrié, Paratronic engineer. This particularly powerful industrial camera is equipped with a 1.3 megapixel CMOS sensor from e2v. The highly sensitive sensor is used by Paratronic in the NIR version (EV76C661ABT). In addition to its outstanding light sensitivity, the sensor offers two global and rolling shutter variants that can be switched during operation. This allows maximum flexibility for changing requirements and environmental conditions, as in this case caused by different times of day and weather conditions. In addition, four areas of interest are available. This allows either several features to be checked at the same time or the AOIs to be captured in an exposure series with different parameters.


The camera thus meets all requirements, confirms Carrié. “We chose this model for three main reasons. Firstly, it convinces with its spectral sensitivity. The sensor picks up all visible colour wavelengths, with particularly good sensitivity in the near-infrared. We also need the option of screwing a wavelength filter into the C-mount close to the sensor. Thirdly, the camera offers the direct possibility of sequentially taking four pictures with increasing exposure time. Continuous shooting makes it possible to get a very high dynamic range.”


Instrumentation Monthly November 2022


SOFTWARE For image acquisition, the system uses the uEye SDK, “Then our own image processing system comes into play,” explains Edouard Bouillot. The ADELIE software then does the image analysis to detect the presence of smoke on the canopy. The analysis is done by comparing two images taken in the same orientation to detect any smoke. This is made possible by several exclusive algorithms developed by PARATRONIC that allow the comparison of a very large number of factors that are not visible to the naked eye. This analysis is carried out in three phases. In phase one, the images to be compared are registered to the nearest 50th of a degree. In phase two, the images are compared to highlight any changes, such as the movement or displacement of objects or the appearance of smoke. In the third stage, advanced analysis takes place, based on the use of different algorithms: The highlighted differences are not only examined in terms of their shape, size, distance, etc., in order to eliminate all elements other than smoke as best as possible. Other algorithms using automatic classifiers and working with parameters extracted from one or more images complete this analysis. The data is then transmitted to the computer control system via a digital network such as fibre optics. The respective data sets contain both a JPEG file of the image for display on the screen, as well as a file containing the camera number, the angle of view, the date and time of the shot, the azimuth. By integrating a weather station, meteorological data such as wind strength or precipitation can also be recorded and taken into account. If an image and its linked file report a fire, an automatic check is carried out: the system makes an estimate of the location of the smoke, then cross-checks it against known locations where other types of smokes


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