Device and method for detecting, classifying and scaring a flying animal

Abstract

The present invention relates to a device and a method for detecting, classifying and scaring a flying animal, and in particular an avian species or a bat. The invention relates to a device for detecting and scaring a flying animal, comprising at least means for acquiring data in a monitoring area, means for analysing the acquired data, means for generating at least one scaring signal and optionally means for regulating the operation of a structure of an area of activity. The invention is particularly applicable in the fields of aeronautics, agriculture, energy production, such as wind or photovoltaic energy, environmental protection and any field of human activity carried out in sites having sensitive facilities. A device and a method according to the invention are particularly useful for detecting and scaring birds when they enter a critical area around sites of human activity.

Description

[0001] DESCRIPTION

[0002] Title of the invention: Device and method for detecting, classifying and scaring away a flying animal

[0003] The present invention relates to a device and a method for detecting, classifying, and scaring away a flying animal. A device and a method according to the invention are particularly useful for detecting and scaring away birds when they enter a critical zone located around sites of human activity.

[0004] The present invention therefore falls within the field of animal deterrent systems, and in particular those for animals belonging to avian species. The invention finds particular application in the aeronautical, agricultural, and energy production sectors, such as wind and photovoltaic energy, as well as in environmental protection and any area of ​​human activity carried out at sensitive installation sites.

[0005] Some ecosystems associated with human activity, such as airports, offer birds a protected natural space and serve as a stopover for migratory species. However, collisions between birds and the structures of these activity sites generate significant bird mortality and cause material damage and / or reduced site functionality. Species posing a danger to these facilities include birds of prey and species with gregarious behavior. Flying animals around human activity sites can be injured or killed: avian species can be injured or killed in collisions with the blades of operating wind turbines, and bats can be injured by the significant pressure differences around operating wind turbines.

[0006] Bird risk prevention involves reducing the presence of birds in the vicinity of sensitive activity sites. Bird scaring takes various forms, such as driven hunts, regulated hunting, the use of audible or visual alarms, or the rearing of natural predators that act as deterrents near these areas.

[0007] EP 2 779 827 B1 describes a method and device for scaring animals away from areas sensitive to human activity. The scaring method includes the generation of at least one looming visual signal, this signal comprising at least one image of variable size over time.

[0008] WO 2014 / 085328 describes a system comprising a camera that detects the presence and proximity of a bird within a defined area, and a means for emitting ultrasound or projecting substances intended to influence the flight path of a bird. US 2013 / 0050400 describes a device for preventing bird collisions with wind turbines, in which at least one panoramic camera installed directly on a wind turbine generates images of its surroundings, and an evaluation system detects the presence of birds in those surroundings.

[0009] US Patent 5,774,088 describes a device that emits microwaves to alert birds flying near areas of human activity. The emissions are detected by the birds' hearing and alert them to the presence of a protected area. The system can remain in standby mode until an antenna detects a bird and activates the microwave emission system.

[0010] In the presence of protected species, local legislation may require regulation of activity, as slowdowns and shutdowns result in a loss of productivity. It is therefore desirable to have measures in place to protect birdlife while optimizing the operation and use of human activity sites located near bird habitats or migratory routes.

[0011] The present invention aims to overcome the aforementioned drawbacks. It relates to a device and a method for detecting and deterring flying animals, particularly avian species, near an activity site. Where applicable, the present invention also regulates the operation of structures at an activity site based on the collision risk previously assessed by the device.

[0012] BRIEF DESCRIPTION OF THE INVENTION

[0013] The inventors have developed a device and a method for the detection, classification and scaring away of a flying animal when it flies near a sensitive site of human activity, as well as the management of the operation of at least one structure of said site of activity.

[0014] A device and a method according to the invention offer the advantage of providing an environmentally friendly and non-lethal solution that respects both the environment and wildlife. The effectiveness of this device and method is immediate and long-lasting. Furthermore, they are easy to install and use.

[0015] Thanks to its analytical means, a device according to the invention allows, where appropriate, a precise identification of avian species and an analysis of the behavior of the avifauna, the data are analyzed in a flexible and global way, the efficiency of the systems can be identified, and corrections or adjustments can be made if necessary.

[0016] In the context of use in the vicinity of a wind farm, a device and a method according to the invention meet the requirements for measurement, monitoring, and analysis during the various phases of the wind farm project, from its design to its operation. They provide a reliable and scalable solution that meets increasing regulatory constraints and biodiversity protection requirements.

[0017] A device and method according to the invention have demonstrated their high effectiveness in scaring away birds of prey flying near wind farms. By combining an effective detection and scaring system with optimized site management, in which the operation of structures is modified only when necessary after scaring, a device and method according to the invention protect birdlife while limiting disruptions to operations and the losses resulting from these disruptions.

[0018] The invention has as its first object a device for detecting and scaring away a flying animal comprising at least: means for acquiring data in a surveillance area, means for analyzing the acquired data, means for generating at least one scaring signal and optionally means for regulating the operation of a structure in an activity area.

[0019] The invention has as its second object a method for detecting and scaring away a flying animal comprising at least the following steps: acquisition of data relating to any flying object in a surveillance area, analysis of the data acquired and, where appropriate, generation of at least one scaring signal and optionally the activation of the regulation of the operation of a structure in an activity area.

[0020] The invention also relates to a classification model, pre-trained on a training dataset, for the detection and characterization of a flying animal and, where applicable, for generating means of scaring away a flying animal and optionally for regulating the operation of a structure within an activity zone. The invention further relates to the use of a device, method, or classification model according to the invention for the detection and scaring away of a flying animal. Finally, the invention relates to a structure comprising a device according to the invention.

[0021] The objects and features of the invention will become clear upon reading the detailed description thereof, the examples and figures whose legend is described.

[0022] In the description of the present invention, the term "for" as in the expression "for detection" means "configured for detection".

[0023] When an interval or range of values ​​is indicated, the cited bounds are considered to be part of the interval or range of values.

[0024] DETAILED DESCRIPTION OF THE INVENTION According to a first object, the invention relates to a device for detecting and scaring away a flying animal, said device comprising at least: a) means for acquiring data relating to a surveillance zone located around an activity site, b) means for analyzing the data acquired during step a), said means being configured for at least one of the following actions: i) detecting and identifying flying objects present in the surveillance zone, ii) classifying objects according to their nature and optionally according to their species, where appropriate classifying an object as a flying animal, iii) estimating the trajectory and speed of objects, iv) estimating the distance between the object and at least one structure of the activity site, v) assessing the risk of collision between the object and said structure and, where appropriate, triggering an action, c) means for generating at least one scaring signal,said at least one signal being managed by management means and emitted by transmission means, and (d) optionally, means for regulating the operation of at least one structure of the activity site, characterized in that the means for data acquisition, the means for data analysis, the means for generating at least one scaring signal, and optionally the means for regulating the operation of at least one structure are interconnected.

[0025] More specifically, a detection device according to the invention comprises at least: a) means for acquiring data relating to a surveillance zone located around an activity site, and to a critical zone included within said surveillance zone; b) means for analyzing the data acquired during step a), said means being configured for the actions of: i) detecting and identifying flying objects present in the surveillance zone; ii) classifying objects according to their nature and optionally according to their species, where appropriate classifying an object as a flying animal; iii) estimating the trajectory and speed of objects; iv) estimating the distance between the object and at least one structure of the activity site; and v) assessing the risk of collision between the object and said structure and, where appropriate, triggering an action; c) means for generating at least one deterrent signal.said at least one signal being managed by management means and emitted by transmission means, upon the entry of a flying animal into said critical zone and (d) optionally, means for regulating the operation of at least one structure of the activity site, characterized in that the means for data acquisition, the means for data analysis, the means for generating at least one scaring signal, and optionally the means for regulating the operation of at least one structure, are interconnected.

[0026] The term "flying animal" refers to any animal belonging to the class of vertebrates and capable of flight. This group includes, in particular, avian species, that is to say birds, belonging to the class "Aves", and chiropterans, or bats.

[0027] The invention relates particularly to a device for detecting and scaring away an animal classified among avian species.

[0028] The term "avian species" refers to a bird species as defined by the classification of birds into orders and families. Many avian species can be detected, identified, and deterred by a device according to the invention. Birds of prey, in particular, are likely to be detected by such a device. Among known birds of prey, one can mention, in particular: eagles, buzzards, harriers, falcons, sparrowhawks, kites, vultures, etc. Other birds can also be detected and deterred by the device according to the invention, such as corvids, seabirds like gulls, terns, auks, skuas, and procellariiformes.

[0029] The term "site of activity" refers to a sensitive site of human activity, including an airport facility, an onshore or offshore wind farm, a photovoltaic park, an agricultural area, an area for the installation of large electrical pylons, and any area including buildings or structures that animals flying in the area could hit and / or damage during a collision.

[0030] A "surveillance zone" refers to an airspace surrounding one or more operational structures that can be monitored by at least one data acquisition system. The dimensions of the surveillance zone depend on the location of the facility and the technical capabilities and sizing of the data acquisition system and the bird-scaring signal used. For example, for a visual bird-scaring signal that emits at least one image, the size of the display panel is important: the larger the panels, the greater the detection range for birds. For instance, 4m x 4m display panels can cover both an aircraft taxiway and a takeoff area.

[0031] The term "critical zone" refers to an airspace volume, included within the airspace volume of the surveillance zone, located around one or more structures at the site of activity. The critical zone is the portion of the surveillance zone where the risk of a flying animal colliding with a structure is higher than anywhere else within the surveillance zone. In the case of a wind farm, for example, the critical zone can be defined as a distance of 300 meters or less from at least one wind turbine. Depending on the performance of the data acquisition means of a device according to the invention, this distance can be increased. Generally, the critical zone includes an airspace volume between 300 and 1000 meters around a structure of activity. Figure 1 illustrates a particular embodiment in which a 350-meter protective dome is located around a wind turbine.

[0032] By "regulation of the functioning of at least one structure of the site of human activity" we mean, for example:

[0033] - for an airport: 1a regulation of aircraft takeoffs and landings,

[0034] - for a wind farm: the regulation of the operation of one or more wind turbines by decreasing, stopping, restarting and / or increasing activity.

[0035] The means for acquiring data relating to any flying object present in the surveillance area are configured to provide data concerning that area. These means are chosen from:

[0036] - Visual detection methods: such as a camera, which provides images and video data; this data comes from high-resolution cameras (particularly PTZ or thermal cameras), allowing continuous monitoring of the area. These methods allow for the visual analysis of moving objects.

[0037] - auditory recording systems, such as directional or omnidirectional microphones that capture sound data; this data is used to detect calls or other specific sounds emitted by birds, and

[0038] - Radar-type detection methods measure precise parameters such as the position, speed and trajectory of detected objects; they are very effective for monitoring objects in low visibility conditions such as fog or night.

[0039] A device according to the invention comprises at least one, two, or three detection means, of a similar or different nature. For example, a device according to the invention comprises at least one camera, one microphone, and one radar. The combination of multiple detection means ensures reliable multispectral data collection, covering all environmental conditions and providing redundancy between the sensors.

[0040] At least one detection device is installed to optimize data acquisition for monitoring the activity site. In one particular embodiment, the acquisition devices, such as microphones and thermal cameras for detecting bird and / or bat activity, are installed above the access door to a wind turbine for ground-based studies and in a nacelle for studies around the turbine rotor. Each detection device is connected to the data analysis system.

[0041] More specifically, a device according to the invention is configured for at least one of the following actions:

[0042] - the detection and classification of animal species located in a surveillance zone, around a sensitive site of human activity,

[0043] - the emission of at least one bird-scaring signal as soon as the monitored bird enters a critical zone near said sensitive area of ​​human activity, and

[0044] - monitoring the bird's trajectory during and after the emission of said scaring signal and, optionally, regulating the function of at least one structure of said sensitive site of human activity.

[0045] Preferably, a device according to the invention is configured to perform at least the three aforementioned actions.

[0046] The means for analyzing data from a device according to the invention include, in particular, a system for recognizing images, sounds, and radar data. The means for data analysis are configured to process all image, sound, and / or radar data and perform the analysis of this data. In practice, the means for data analysis of a device according to the invention are configured to perform at least one of the following operations:

[0047] - object detection,

[0048] - classification of objects,

[0049] - estimation of the trajectory and speed of objects,

[0050] - estimation of the distance between an object and at least one structure at the activity site,

[0051] - assessment of the risk of collision between the object and said structure and, if necessary, to trigger an action.

[0052] In practice, the means for analyzing the data of a device according to the invention are configured to perform one, two, three, four or all of the following operations:

[0053] - object detection,

[0054] - classification of objects,

[0055] - estimation of the trajectory and speed of objects,

[0056] - estimation of the distance between an object and at least one structure at the activity site,

[0057] - assessment of the risk of collision between the object and said structure and, if necessary, to trigger an action.

[0058] Object detection refers to the processing of data collected by data acquisition systems, using algorithms, to identify the object(s) present in the monitored area. The goal is to identify objects in real time while combining data from multiple sensors to maximize detection reliability.

[0059] By "object classification," we mean the categorization of objects according to their nature (for example: bird, drone, debris, or other) and, if possible, their species. For an object classified as an animal, data analysis methods allow for the identification of the animal's species, particularly its avian species. This identification is based on at least one criterion, such as its size, speed, trajectory, and behavior.

[0060] The purpose of estimating the trajectory and speed of the object is to predict whether an object is approaching a structure dangerously and, if so, to estimate its time of arrival on said structure.

[0061] Estimating the distance between an object and at least one structure at an activity site involves assessing whether the detected object is within a critical distance of the structure. Radar data combined with visual data allows for the calculation of the precise distance between the object and at least one structure. If the object is within a threshold distance of a structure, it has crossed the threshold into the critical zone. The system considers this a risky situation and triggers an action. In other words, an object flying within a threshold distance is located in a critical zone around a structure or activity site. In the case of wind turbines, the threshold distance can be as low as 300 meters.

[0062] The means for data analysis are therefore configured to make a decision when a situation considered risky occurs and to trigger an action intended to implement one or more appropriate measures to limit or avoid any collision.

[0063] The means for data analysis are further configured to send a signal to the means for generating at least one scare signal when the animal crosses the entry threshold into a critical area of ​​the surveillance zone.

[0064] Optionally, the means for analyzing the data of a device according to the invention are configured to send a signal to the means for regulating the operation of the structure(s) at the activity site that the object is approaching. This signal is intended to reduce and / or stop the operation of the structure, urgently when necessary, if the result of the calculation indicates a risk of collision exceeding a predetermined value.

[0065] Optionally, depending on the nature of the structure or activity site, the action consists, in a second step, of sending a signal to the control means for the operation of the structure(s) at the activity site that the object is approaching. According to a particular embodiment, the data analysis means of a device according to the invention are configured to calculate the probability of collision of the flying animal with at least one of the structures at the activity site. This calculation is based on the analysis of image, sound, and / or radar data, the analysis of its trajectory, and the estimation of its speed and the position of at least one structure at the activity site, with which the data analysis means have been previously programmed.The result of the collision probability calculation is then compared with a predetermined value, programmed in the means for data analysis; if the result of the calculation indicates a risk of collision greater than a first determined value, the activation of a module regulating the operation of said structure, to decrease and / or stop the operation of the structure.

[0066] According to a particular embodiment, the means for analyzing the data of a device according to the invention are configured to send an activation signal to a module regulating the operation of said structure, to increase or restart its operation if the result of the calculation indicates a risk of collision lower than the determined value.

[0067] Finally, the means for analyzing data from a device according to the invention are configured so that, when the flying object in question is located outside the critical zone, the system reverts to a standard monitoring phase, ready to detect and manage other potential threats. A device according to the invention thus makes it possible to ensure continuous monitoring of the activity site concerned.

[0068] According to a particular embodiment of a device according to the invention, the means for analyzing the data acquired by the detection means are based on a computer tool comprising a decision intelligence (DI, business intelligence or BI) module based on artificial intelligence (AI) technologies.

[0069] According to this particular implementation, artificial intelligence performs complex analyses on the collected data and the business intelligence platform transforms the raw data into actionable information to aid decision-making.

[0070] The data collected by the sensors is processed using advanced algorithms to identify objects within the surveillance area. In specific implementations: video data is analyzed by convolutional neural network (CNN) models such as YOLO (You Only Look Once) or SSD (Single Shot Detector); these algorithms quickly detect moving objects (birds, drones, or others); radar data is analyzed to identify objects based on their position, altitude, and movement; and a spectral analysis of the sound data is performed to recognize the specific sound signatures of bird species. Such a system enables real-time object identification while combining data from multiple sensors to maximize detection reliability.

[0071] In one particular embodiment, once objects have been detected, they are classified according to their nature and, if possible, their species. Data classification is performed using a convolutional neural network model: detected objects are categorized, for example, as a bird, a drone, or debris. If specific models have been previously trained, the system can recognize precise species, particularly protected or endangered ones.

[0072] Where applicable, sound signatures and radar-detected trajectories help to refine the classification.

[0073] This classification step allows us to prioritize objects requiring immediate intervention, particularly birds that are close to or belong to sensitive species.

[0074] Estimating the trajectory and speed of detected objects is crucial for anticipating their behavior. Video and radar data are used to model current trajectories and predict future movements using Kalman filters or other mathematical modeling methods. Radar sensors measure the speed of objects to assess the risk of impact or passage through critical areas. This step allows us to predict whether an object is approaching structures dangerously and to estimate its time of arrival.

[0075] Distance estimation and critical threshold verification are performed after estimating the object's trajectory and speed. Data analysis methods assess whether the detected object is at a critical distance: Radar data combined with visual data allows for the calculation of the precise distance between the object and the structures. If the object is at a distance less than a predetermined threshold, the system considers this a risky situation and triggers an action. More specifically, in a device according to the invention, this threshold can be set at 300 meters from the structures. This step aims to activate, if necessary, an appropriate signal to mitigate the risk of collision.

[0076] More specifically, in a device according to the invention, the means for data analysis have been previously trained with a relevant dataset.

[0077] More specifically, the means for data analysis were previously trained with a dataset relating to at least one avian species, in order to determine precisely whether the animal belongs to said avian species.

[0078] By "determination of the entry threshold into the critical zone" we mean the prior programming of the means of data analysis with the localization of the entry threshold into the critical zone, and the analysis of image, sound and / or radar data, according to the results of the data analysis, determination of the crossing by the animal of the entry threshold into the critical zone is carried out.

[0079] The means for data analysis are configured to send an activation signal to the means for generating at least one scare signal when the animal crosses the entry threshold into a critical area of ​​the surveillance zone.

[0080] According to a particular aspect, in a device according to the invention, the means for generating at least one scaring signal are managed by at least one management means and emitted by at least one emitting means.

[0081] The use of light stimuli such as flashing lights and laser beams is widely described. Sonic deterrents exploit the hearing sensitivity of birds by emitting different types of sounds: ultrasound, predator calls, distress calls, or disruptive artificial sounds.

[0082] In a device according to the invention, a scaring signal can be chosen from: a visual signal, in particular a light signal or a signal comprising at least the diffusion of an image, an auditory signal, in particular an ultrasound signal, or a combination of signals.

[0083] The means for generating said scaring signal are well known to a person in the trade.

[0084] The aforementioned transmission devices are placed in locations selected for their visibility or accessibility to a flying animal within the surveillance area. These transmission devices are located in the critical zone. A person skilled in the art can determine the optimal installation locations based on the nature of the activity site. In one particular embodiment, round LED screen-type illuminated panels with a diameter of at least 1 meter are fixed to the mast of a wind turbine at a height of between 6 and 12 meters above the ground. In another particular embodiment, illuminated panels are installed at various strategic points within the activity area, depending on the layout of the activity site.

[0085] More particularly, the invention relates to a device for the visual detection and scaring away of a flying animal, according to which the scaring signal is a looming signal in which the size of at least one image varies over time, an increase in the size of the image simulating an approach by increasing the size of the image.

[0086] The looming effect is an optical illusion created by projecting an image of an object of varying size. As the image size increases, the viewer perceives the object as rapidly growing larger, as if it were approaching the viewer at high speed. A signal exhibiting the looming effect simulates an imminent collision or attack for a bird, triggering its flight. The term "looming" means "imminent" or "appearing" in English (Hausberger et al. "Wide-eyed glare scares raptors: from laboratory evidence to applied management", PLOS One, October 11, 2018, https: / / doi.org / 10.1371 / journal.pone.0204802).

[0087] Observations made during the scaring of raptors show that the use of such a signal leads to a rapid change in raptor behavior and that this effect is lasting, even when the bird population is large locally (Hausberger et al, 2018).

[0088] In a device according to the invention, a looming effect can be achieved using an image representing concentric black circles on a white background, or an image symbolizing one or two eyes, by enlarging the image size. The animation of the concentric circles is designed to maximize the effect of rapid looming. Preferably, in a device according to the invention, the image used for the visual signal consists of a pair of black discs.

[0089] Birds of prey likely to be startled by a looming signal include: kites, falcons, eagles, buzzards, harriers, sparrowhawks, vultures, etc.

[0090] According to a particular aspect, in a device according to the invention, the means for generating at least one visual scaring signal, in which said visual signal comprises at least one image, are managed by at least one management means and emitted by at least one emitting means.

[0091] The visual scaring signal includes at least the emission of an image, figurative or abstract, for a variable duration depending on the programming of the device according to the invention, according to a form and a sequence chosen in order to cause the scaring of at least one flying animal, depending on the species considered.

[0092] The means of emitting the visual scaring signal are chosen from: screens, such as LED screens.

[0093] Preferably, when the visual signal is generated, it is visible for a duration of 5 to 10 minutes, depending on the presence detected in the critical area. The image size can increase gradually, with a constant or variable rate of increase. The rate of increase is configured based on a fixed parameter or on an estimate of the bird's approach speed or its distance from the activity site structure. The frequency of signal size increase is also configured based on a fixed parameter or on an estimate of the bird's approach speed or its distance from the activity site structure.

[0094] A device according to the present invention comprises at least one means for generating a visual signal, this means being in particular chosen from: an electronic screen (or panel) which directly displays the visual signal and a projection system which projects the signal onto a chosen surface.

[0095] In a device according to the invention, the means for data acquisition, the means for data analysis, the means for generating at least one scaring signal, and optionally the means for regulating the operation of at least one structure, are interconnected.

[0096] The detection and analysis means are computer-based and are interconnected using RJ45 and / or HDMI cables for LED screens.

[0097] According to a particular embodiment, the invention relates to a device for the visual detection and deterrence of a flying animal, said device comprising at least: a) means for acquiring data relating to any flying object in the surveillance zone located around an activity site, for detecting the possible presence of at least one flying object, and tracking the trajectory of any flying object in said surveillance zone; b) means for analyzing the data acquired during step a), said means being configured to: i) detect and identify objects present in the surveillance zone; ii) classify objects according to their nature and optionally according to their species; iii) estimate the trajectory and speed of objects; iv) estimate the distance between the object and at least one structure of the activity site; v) assess the risk of collision between the object and said structure and, if necessary, trigger an action.(c) means for generating at least one visual deterrent signal, comprising at least one image, said at least one visual signal being managed by management means and emitted by transmission means, a looming signal in which the size of at least one image varies over time, simulating an approach by increasing the size of the image, said at least one signal being managed by management means and emitted by transmission means; (d) means for regulating the operation of at least one structure of the activity site, characterized in that the means for data acquisition, the means for data analysis, the means for generating at least one deterrent signal, and optionally the means for regulating the operation of at least one structure are interconnected.

[0098] According to this particular embodiment, a device according to the invention comprises means for regulating the activity of a mobile structure: slowing down, stopping, emergency stopping, resuming activity, and regulating speed after the animal has passed. This device is particularly suitable when said structure is a wind turbine.

[0099] In the latter case, depending on the result of the data evaluation, the means for data analysis are capable of sending a signal: i. to the means of generating a visual scaring signal and / or il. to the means of regulating the operation of at least one structure of the activity site.

[0100] According to a second object, the invention relates to a method for detecting and scaring away a flying animal, this method comprising at least the following steps: a) acquiring data relating to any flying object in a surveillance zone located around an activity site, in order to detect the presence of at least one flying object, b) analyzing the data acquired during step a), comprising at least one of the steps for: i) detecting and identifying the objects present in the surveillance zone, ii) classifying the objects according to their nature and optionally according to their species, iii) estimating the trajectory and speed of the objects, iv) estimating the distance between the object and at least one structure of the activity site, v) assessing the risk of collision between the object and said structure and, where appropriate, triggering an action, c) where appropriate, generating at least one scaring signal.said at least one signal being managed by management means and emitted by transmission means, d) optionally, the regulation of the operation of at least one structure of the activity site.

[0101] More specifically, a method for detecting and scaring away a flying animal according to the invention comprises at least the following steps: a) acquiring data relating to any flying object in a surveillance zone located around an activity site, and in a critical zone included in said surveillance zone, to detect the presence of at least one flying object; b) analyzing the data acquired during step a), comprising the steps for: i) detecting and identifying the objects present in the surveillance zone; ii) classifying the objects according to their nature and optionally according to their species; iii) estimating the trajectory and speed of the objects; iv) estimating the distance between the object and at least one structure of the activity site; and v) assessing the risk of collision between the object and said structure and, if necessary, triggering an action.(c) where appropriate, the generation of at least one deterrent signal when the flying animal crosses the entry threshold into said critical zone, said at least one signal being managed by management means and emitted by transmission means; (d) optionally, the regulation of the operation of at least one structure of the activity site.

[0102] Figure 2 illustrates a particular embodiment of a method according to the invention for monitoring a wind turbine, showing the different steps of the method. These steps include, in particular: data acquisition, data analysis, activation of the deterrent system, activation of the wind turbine's operating control module, and continued monitoring.

[0103] A method for detecting and scaring away a flying animal according to the invention is characterized in that the acquisition of data relating to any flying object in the surveillance zone located around an activity site is carried out for the entire duration of the presence of the animal in the surveillance zone, and more particularly for the duration of the presence of the animal in the critical zone and at least until its exit from the critical zone.

[0104] More specifically, the invention relates to a method for detecting and scaring away an avian species.

[0105] More particularly, the invention relates to a method for visually detecting and scaring away an avian species, according to which the scaring signal is a looming signal in which the size of at least one image varies over time, an increase in the size of the image simulating an approach by increasing the size of the image.

[0106] According to one particular aspect, a method for detecting and scaring away a flying animal according to the invention further comprises:

[0107] I) the calculation of a risk of collision of the flying animal detected during step b) with a structure of the activity site, ii) if the result of the calculation indicates a risk of collision greater than a first determined value, the activation of a module to regulate the operation of said structure, to reduce and / or stop the operation of the structure.

[0108] According to this particular embodiment, a method according to the invention is implemented during the monitoring of an activity site comprising wind turbines, the activity of which is regulated according to the probability of collision of a flying animal with at least one wind turbine.

[0109] According to one particular aspect, a method for detecting and scaring away a flying animal according to the invention further comprises, after the activation of a control module for the operation of said structure, when the probability of collision of the flying animal with the structure is less than a second determined value, the control module for the operation of said structure is activated to increase and / or restart the operation of the structure.

[0110] More particularly, the invention relates to a method for the visual detection and deterrence of an avian species, this method comprising at least the following steps: a) the acquisition of data relating to any flying object in a surveillance zone located around an activity site, in order to detect the presence of at least one flying object, b) the analysis of the data acquired during step a), to identify among said flying object the presence of at least one animal, and where appropriate to assess its trajectory and speed in the surveillance zone, the calculation of a risk of collision of the flying animal detected during step b) with a structure of the activity site, and, if the result of the calculation indicates a risk of collision greater than a first determined value, the activation of a module for regulating the operation of said structure, in order to reduce and / or stop the operation of the structure,c) detection of the animal crossing the entry threshold into a critical zone of the surveillance area and the emission of at least one visual deterrent signal upon crossing the entry threshold into the critical zone, to move the animal away from at least one structure of the activity site, d) monitoring of the animal's trajectory in the critical zone, and e) after the activation of a module regulating the operation of said structure, when the probability of collision of the flying animal with the structure is less than a second determined value, the module regulating the operation of said structure is activated to increase and / or restart the operation of the structure.

[0111] According to a third object, the invention relates to a classification model, previously trained on a training dataset, configured to analyze the input data provided by the detection means of a device according to the invention.

[0112] A "classification model" is defined as a pre-trained machine learning algorithm, particularly one trained through supervised learning, along with a training dataset for the algorithm and an evaluation dataset. A classification model may consist of a computer program, which can be written in any suitable programming language known to a person skilled in the art. This computer program is capable of being run on a computer to generate a technical result. Examples of such technical results are provided below.

[0113] The training dataset can include a training set and a test set for the model. The model can thus be tested against the test dataset, and the test set can be used to determine whether the model training is satisfactory. The training and test sets can be different. Alternatively, the test set can correspond to a portion of the training set. The classification model according to the invention detects and identifies risks by implementing fine discrimination; the different types of observation (visual, auditory, and radar) are correlated, and the generated data sets are quickly analyzed and utilized. Furthermore, the site configuration can be used to amplify the analytical power and improve risk qualification.

[0114] A classification model according to the invention is adapted for classifying (among birds and within bird species...) based on at least one characteristic of said flying object, to analyze the input data provided by the detection means and classify a device according to the invention as either "aircraft" or "bird," as well as "which bird species," "which trajectory," and "which speed." Such a classification model offers savings in time, cost, and performance compared to existing tools on the market.

[0115] In the case of the classification model, the input data are chosen from:

[0116] - images with objects,

[0117] - sound recordings,

[0118] - data from radar.

[0119] The output data consists of objects with a label: a percentage of belonging to a specific species.

[0120] The training dataset may include a multitude of pairs of data, each pair of data comprising a first data point representing at least one characteristic of said flying object (bird) and a second data point representing membership in a given avian species.

[0121] The classification model can be implemented on a computer to generate a technical result consisting of classifying an object, based on its characteristics, into a particular bird species. The classification model is considered to have achieved a satisfactory level of learning across all profiles in the test set if the classification achieves, in particular, a minimum Fl score of 70%, 75%, 80%, 85%, 90%, 91%, or 92%. According to a particular embodiment of a device according to the invention, the data analysis means implement a Kalman algorithm. This algorithm allows for the processing of key functionalities such as:

[0122] - Real-time tracking: estimation of object positions and speeds from noisy data and continuity of tracking even in the event of temporary data interruptions,

[0123] - Filtering of noisy data: smoothing of data from sensors (cameras, radars, lidars) to generate coherent trajectories,

[0124] - Trajectory prediction: anticipating movements to predict future positions and application in bird-scaring and PTZ camera adjustment systems,

[0125] - Multi-sensor data fusion: combining data from multiple sensors to improve accuracy,

[0126] - Anomaly detection: identification of unusual behaviors, such as a sudden change of direction,

[0127] - Reduction of false positives: reduction of extraneous objects by modeling the typical movements of birds,

[0128] - Automatic Controls: triggering specific actions, such as scaring away or stopping wind turbines.

[0129] In one embodiment of a device according to the invention, a classification model is combined with a Kalman algorithm to improve real-time detection and tracking. This coupling enables the processing of noisy data and the anticipation of the movements of detected objects. In an example of an AI and Kalman algorithm implementation of a device according to the invention, bird detection and tracking include:

[0130] - Detection: a neural network detects birds in images / videos; the detected coordinates (x, y) are used as inputs for the Kalman algorithm.

[0131] - Prediction and Update: inputs (Positions (x, y, z) and velocities with uncertainties), outputs (Corrected trajectories and future predictions), steps: prediction phase: (modeling of the movement to estimate the new positions) and update phase (adjustment of the predictions with the new measurements).

[0132] The invention also relates to a classification model, previously trained on a training dataset, to detect and classify, in a process according to the invention, at least one bird species or a bat.

[0133] According to a particular aspect, a classification model according to the invention meets at least one, at least two, or all of the following characteristics:

[0134] - Model architecture based on a YOLO (You Only Look Once) neural network - the model is supervised and requires at least 1500 images and annotations per category,

[0135] - the main layers are convolutional (Conv2D) for feature extraction,

[0136] - A "Batch Normalization" step leads to stabilizing the learning,

[0137] - A "Dropout" step reduces overfitting,

[0138] - a "Pooling Layers" step reduces dimensionality.

[0139] According to a particular aspect, a training algorithm for a classification model according to the invention meets at least one, at least two, or all of the following characteristics:

[0140] - Optimizer: Adam (improved gradient descent),

[0141] - Loss function: cross entropy,

[0142] - Number of epochs: at least 30, adjusted according to observed performance. Overfitting should be avoided.

[0143] - Performance and Validation Criteria: A minimum Fl score of 70% is required to consider the model as performing, preferably a classification model according to the invention achieves a minimum Fl score of 75%, 80%, 85%, 90%, 91% or 92%.

[0144] The predictions consist of probabilities of detected objects belonging to specific classes.

[0145] According to a fourth object, the invention relates to the use of a device, method, or model according to the invention for detecting and scaring away a flying animal, in particular an animal of an avian species, near at least one site of human activity. A device, method, and model according to the invention are usable during the design, construction, and / or operation of an activity site.

[0146] More specifically, the invention relates to the use of a device, method, or model according to the invention for the detection and deterrence of avian species, particularly birds of prey, near a wind farm. Even more specifically, the invention relates to the use of a device, method, or model according to the invention in which the deterrence signal is a looming signal.

[0147] Furthermore, the invention relates to the use of a device, method or model according to the invention for evaluating the effectiveness of a scaring signal.

[0148] According to a fifth object, the invention relates to a fixed structure, in particular a wind turbine, characterized in that it comprises, or is connected to, a device for detecting and scaring away a flying animal, in particular a bird species, and in particular a visual scaring device with a looming effect, according to the invention. A wind turbine comprises a tower equipped with a nacelle containing an electric generator, said electric generator being driven in rotation by a rotor equipped with blades subjected to the action of the wind, the generator producing electricity when a shaft is driven in rotation.

[0149] The present invention will be better understood by reading the following examples, which are given to illustrate it and not to limit its scope.

[0150] Figure 1 represents a critical zone represented by a protective dome with a radius of 350 meters around a wind turbine.

[0151] Figure 2 schematically illustrates a particular embodiment of a process according to the invention, with different successive steps of the process.

[0152] EXAMPLES

[0153] Example 1: Device for detecting bird species near a wind farm

[0154] The inventors have developed and perfected an artificial intelligence-based bird detection and protection solution.

[0155] A detection and deterrent device according to the invention is configured for the detection of multiple objects and comprises the following detection means: visual detection (fixed camera or Pan Tilt Z (PTZ)), sound detection, and radar. The combination of different detection sources, for example, sound and visual, allows for the correlation of observations.

[0156] The surveillance area is defined by the installation of the bird monitoring and detection system on the mast of a wind turbine at a height between 5 and 15 m. The acquisition elements (microphones / camera and thermal cameras) are fixed to the structure of the wind turbine using neodymium magnets.

[0157] The images, sound data and radar data from the detectors are processed by the device's analysis means, to which they are connected.

[0158] The analytical tools include a technical decision-making module that uses all the data collected by the various sensors to analyze the movement of flying objects within the area monitored by the detectors. This technical module consists of artificial intelligence (AI) and a Business Intelligence (BI) platform.

[0159] The technical module includes, in particular:

[0160] - a convolutional neural network (CNN) for multi-object detection configured for automatic visual detection of presence in the surveillance area, - a convolutional neural network for classification, trained for the detection of at least one avian species, configured for assisted identification of at least one avian species chosen from: red kite, black kite, black stork, vultures, buzzards, seabirds, etc. any species of flying animal is potentially identifiable according to the prior training of the classification model.

[0161] The infrastructure of a device according to the invention includes a public cloud-based deployment, an on-premises server available with a Linux x86_x64 host and real-time multi-camera scenarios, and the ability to deploy at sites with low or no connectivity.

[0162] The system components are computer-based and interconnected using RJ45 and / or HDMI cables (for LED screens). All system components are powered by electricity from the wind turbine.

[0163] In the event of a lack of connectivity, remote monitoring systems provide continuous updates on any potential malfunctions. If necessary, contacting the site operator allows for the triggering of an emergency on-site intervention.

[0164] The tasks performed by the analysis methods are: a) the detection of multiple objects, by implementing at least one of the methods below, and preferably by combining the methods below:

[0165] - SSD / Yolo type convolutional neural network (CNN) for processing a streaming video source,

[0166] - High-frequency image analysis,

[0167] - Convolutional neural network (CNN) localization based on radar data (Radar Detect), b) object classification using the convolutional neural network (CNN), c) trajectory detection and analysis using classical mathematical analysis, d) decision making using a decision module based on user-defined rules.

[0168] The detection performance of a device according to the invention makes it possible to obtain:

[0169] - Accurate detection and counting of birds from ground-based cameras (fixed or Pan Tilt Z motorized tilting camera with zoom),

[0170] - accurate avian classification, even in challenging environments,

[0171] - Precise detection of small and large birds; the reference detection ranges for an AXIS Q1555-PLE camera with a resolution of 1920x1080 pixels are, for example, approximately 170 m for a wingspan of 0.68 m and approximately 400 m for a wingspan of 1.60 m; birds are detected down to 5x5 pixels. A detection device according to the invention therefore allows for the identification, tracking, and analysis of the behavior of different bird species in real time and continuously.

[0172] The device enables the identification, tracking, and real-time analysis of bird behavior in environments such as wind farms. This device includes a decision-making intelligence module that combines two main technologies:

[0173] - Artificial Intelligence (AI): This technology performs complex analyses based on the collected data,

[0174] - Business Intelligence (BI): This platform transforms raw data into actionable information to support decision-making. This module uses data captured by various devices such as cameras, radar, and microphones to analyze bird movement and behavior.

[0175] Statistical analysis of observations of birds of prey and corvids shows that they are deterred by the visual stimulus without habituation. This deterrence is demonstrated by a decrease in the number of birds within the stimulus's visibility zone, despite an increase in the total number of birds across the entire site during the observation period.

[0176] Example 2: Detection and deterrent device and method according to the invention in the vicinity of a wind farm

[0177] According to a particular embodiment of the invention, cameras, recorders and radar are installed near a wind farm on the mast of each wind turbine or on a delivery point present in the area.

[0178] These detection methods are connected to analysis methods as described in Example 1. The technical module includes, in particular, a convolutional neural network for classification, trained to detect several bird species, including the red kite. The critical zone is defined, in accordance with current regulations, as being at a distance of 300 meters or more from any wind turbine. The technical module is configured to detect when at least one bird crosses the threshold into the critical zone.

[0179] The infrastructure of the device also includes at least means of emitting a visual warning signal as soon as the bird crosses the entry threshold into the critical zone, the warning consisting of the emission of looming effect signals, and means of regulating the operation of the monitored structure.

[0180] The bird's trajectory and speed within the monitoring zone are assessed. If necessary, a visual looming signal is triggered as soon as the bird enters the critical zone. The bird's trajectory is continuously monitored as long as it remains within the critical zone.

[0181] If the bird deviates from its flight path after the visual warning signal is triggered, its flight is tracked until it leaves the critical zone. If the bird does not deviate from its flight path, or not sufficiently, the wind turbine's operating control system is activated: depending on the situation, the turbine's operation is slowed down or, more rarely, stopped. The bird's flight path is tracked until it leaves the critical zone.

[0182] In the event that the bird's trajectory makes a collision with the wind turbine blades likely upon entering the critical zone, the wind turbine's operating regulation device is activated in order to trigger an emergency shutdown.

[0183] Statistical analysis of observations of birds of prey and corvids shows that they are deterred by the visual stimulus, without habituation. This deterrence is demonstrated by a decrease in the number of birds within the stimulus's visibility zone, despite an increase in the total number of birds across the entire site during the observation period.

Claims

DEMANDS

1. A device for detecting and deterring a flying animal, said device comprising at least: a) means for acquiring data relating to a surveillance zone situated around an activity site, and to a critical zone included within said surveillance zone, b) means for analyzing the data acquired during step a), said means being configured for the actions of: I) detect and identify flying objects present in the surveillance area, ii) classify objects according to their nature and optionally according to their species, where appropriate classifying an object as a flying animal, iii) estimate the trajectory and speed of objects, iv) estimate the distance between the object and at least one structure of the activity site, and v) assess the risk of collision between the object and said structure and, where appropriate, trigger an action, c) means for generating at least one bird-scaring signal, said at least one signal being managed by management means and emitted by transmission means, as soon as a flying animal enters said critical area, and d) optionally, means for regulating the operation of at least one structure of the activity site, characterized in that the means for data acquisition, the means for data analysis, the means for generating at least one bird-scaring signal,and optionally the means for regulating the operation of at least one structure are interconnected.

2. Device according to the preceding claim, characterized in that said flying animal is classified among avian species.

3. Device according to any one of claims 1 or 2, characterized in that said scaring signal is a looming visual signal in which the size of at least one image varies over time, simulating an approach by increasing the size of the image.

4. A method for the visual detection and deterrence of a flying animal, comprising at least the following steps: a) acquiring data relating to any flying object in a surveillance zone located around an activity site, and in a critical zone included within said surveillance zone, to detect at least one flying object; b) analyzing the data acquired in step a), comprising the steps for: I) the detection and identification of objects present in the surveillance area, ii) the classification of objects according to their nature and optionally according to their species, iii) the estimation of the trajectory and speed of objects, iv) the estimation of the distance between the object and at least one structure of the activity site, and v) the assessment of the risk of collision between the object and said structure and, where appropriate, the triggering of an action, c) the generation of at least one deterrent signal when the flying animal crosses the entry threshold into said critical zone, said at least one signal being managed by management means and emitted by transmission means, d) optionally, the regulation of the operation of at least one structure of the activity site.

5. Method according to claim 4, characterized in that said scaring signal is a visual signal with a looming effect, in which the size of at least one image varies over time, simulating an approach by increasing the size of the image.

6. A method according to any one of claims 4 or 5, further comprising: i) calculating the risk of collision of the flying animal detected during step b) with a structure of the activity site, ii) if the result of the calculation indicates a risk of collision greater than a first determined value, activating a module for regulating the operation of said structure, to reduce and / or stop the operation of the structure.

7. A method according to any one of claims 4 to 5, characterized in that it further comprises, after the activation of a control module for the operation of said structure, when the probability of collision of the flying animal with the structure is less than a second determined value, the control module for the operation of said structure is activated to increase and / or restart the operation of the structure.

8. Classification model for implementing a device according to any one of claims 1 to 3 or a method according to any one of claims 4 to 7.

9. Use of a device according to any one of claims 1 to 3, of a method according to any one of claims 4 to 7, or of a model according to claim 8 for the detection and scaring away of a flying animal.

10. Fixed structure, in particular wind turbine, characterized in that it is connected to a device for detecting and scaring away a flying animal according to any one of claims 1 to 3.

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