ES2940349A1 - METHOD AND SYSTEM FOR THE DETECTION AND DISTRIBUTED FIGHT AGAINST UNMANNED VEHICLES (Machine-translation by Google Translate, not legally binding) - Google Patents

Abstract

Method and system for the detection and distributed fight against unmanned vehicles. Method and system of detection, location and identification of unmanned systems which allow the supply of information (location, textual, graphic, etc.) about unmanned systems to a central system and mobile devices (for example, mobile phones, telephones smartphones or "smart phones", tablet systems or "tablets" or similar devices). (Machine-translation by Google Translate, not legally binding)

Description

DESCRIPTION

METHOD AND SYSTEM FOR THE DETECTION AND DISTRIBUTED FIGHT AGAINST

UNMANNED VEHICLES

TECHNIQUE SECTOR

This invention falls within the fields of systems for detecting and combating unmanned vehicles (Counter-UV or CUV), in particular systems for detecting and combating unmanned aerial vehicles (Counter-UAS or CUAS) or drones. This invention also consists of elements from the field of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and social media .

Drones are increasingly present in our society and in the daily life of cities and other inhabited areas, an aspect that is worrying from a security point of view. Therefore, it is necessary for society to have systems and methods to detect and minimize the risks caused by unmanned vehicles that operate outside the areas permitted or regulated for this purpose by the competent authorities. All this with the aim of protecting and increasing the safety of people, private property and society in general.

Commercially operated drones also raise several concerns for us as far as citizen privacy is concerned. This is because most drones can be equipped with high-resolution, high-range cameras and sensors with the potential to invade people's privacy, capturing information, images and conversations in a way that is not permitted. Such camera-equipped drones make it possible to instantly capture high-definition images and videos of virtually anyone or anything within their flight path, images and videos that can be shared on any social network in a matter of seconds or illegally stored and distributed. to third parties. In short, we can state that drone operators can fly over private property, view and record anyone without their consent.

Therefore, a system and method to detect and defeat drones is required to increase security, protect privacy, and decrease potentially illegal activities. To minimize or avoid the possibility of unauthorized drones obtaining confidential information in an unauthorized manner, it must be possible to detect such drones when they are flying over the airspace of an urban area, public areas and particularly over any private property. However, the drone detection systems that currently exist are expensive, difficult to implement and in some cases impossible to use in populated areas (let us think, for example, that the radiation emitted by some radars makes their use unfeasible in densely populated areas).

In this particular invention, a system and a method are presented that allow the detection of unmanned vehicles (especially unmanned aerial vehicles or drones) based on information (text, graphics, images, videos, audio or any other type) provided by the users of a social network, which is managed through said social network and which allows its improvement through the use of advanced techniques in the fields of artificial intelligence, machine learning, object recognition or the expert opinion of users of the social network. The invention presented aims to lay the foundations for developing surveillance and early detection systems for unmanned vehicles that allow the authorities to take the necessary corrective measures in each case.

BACKGROUND OF THE INVENTION

Despite the proliferation of unmanned systems, today there is no standardized way to detect and identify such unmanned systems or their owners, operators, or pilots while in the air. Some proposals are that all unmanned aerial systems be registered in some way with the authorities. However, this registry would only be effective if the police or other civil or military authorities could identify the owner/operator of said systems, which is not possible in most cases on a practical level. It is therefore necessary to have a system that allows the detection and identification of an unmanned aerial system while it is in the air, preferably allowing the capture of relevant data such as its position and altitude, its manufacturer and model, its pilot and the position of said pilot, etc.

Most of the systems proposed in the state of the art are based on the installation in the specific areas to be monitored of a variety of monitoring and identification devices to surveil and monitor the airspace over that area by detecting unmanned aerial systems within those areas. areas. These monitoring systems can be daisy-chained to cover large customizable coverage areas, or they can be connected to a central system allowing monitoring of multiple areas. Identification devices used may include, but are not limited to, video cameras, acoustic sensors, infrared cameras, electro-optical sensors, radars, and radio frequency (RF) systems.

Once said systems detect a drone, the signature of said drone is transferred to a control center or central system that contains a drone recognition library or database which contains information on all types of drones known by said system. . Said information may contain the visual signature, the acoustic signature, the radar signature, the electromagnetic signature and other signatures or a combination of them characterizing each type and model of drone previously stored in said library. Some of the existing systems use sensor networks working cooperatively, that is, they use a set of nodes where there are mobile or fixed sensors that can perceive, identify and cooperatively track one or more unmanned vehicles from different positions, perspectives, and using various technologies. Once the systems detect an unmanned vehicle, the phase of tracking, detailed identification and neutralization in the case of unauthorized systems can be initiated. In other words, without an early detection and warning system, the monitoring, identification and neutralization phases of a potential threat cannot be used with the speed required to protect people and the critical infrastructures of a city, which require detection systems. early detection of threats that are fast, reliable, and distributed.

One potential solution is the one pointed out by the DARPA program called "Aerial Dragnet" which aims to detect and track small UAS in urban areas, a task that they recognize as very complicated. This program seeks innovative technologies to provide persistent and area surveillance coverage of all UAS operating below 1,000 feet in a major city While the focus of this program is on protecting troops operating in complex urban environments, the system would be of civil application to help protect the metropolitan areas of a country against terrorist threats that use unmanned aerial systems or drones. One of the solutions used for drone detection was to place display radar systems on large hot air balloons flying over an urban area at a height of up to 125 meters, as well as on rooftops and communication towers in cities, as well as other drones incorporating various types of sensors flying over the area of interest, that is, drones are used to detect drones. Once an unwanted intrusion is detected, the monitoring stage involved several drones sent to the area where the unauthorized drones were detected to carry out said task. However, the key challenge is distinguishing unauthorized drones from other objects in the area of interest, including ground vehicles and birds. An additional problem in dense urban environments is the "clutter" or interference that appears in the data collected by said radar systems and other sensors (which is normal and logical considering a congested radio frequency environment such as a large city where multiple bounces of the signals in buildings, vehicles, rooftops, etc., and that makes it difficult and sometimes prevents the detection of a target, creating "dark" or shadow areas where no system allows to detect a drone. Let's not forget that a deployment of sensors covering an entire city can be enormously expensive.One way to minimize the problems caused by clutter is to refine the signal processing algorithms used by radar and other detection systems.

Another simple solution to achieve the necessary situational awareness about the location of unmanned systems over a large city is to provide all unmanned systems and drones with "beacons" ( "beacons" in Anglo-Saxon terminology) that allow them to be tracked throughout. moment by the competent authorities. These technologies are already used to track manned vehicles at sea, on roads and in airspace. The big disadvantage is that terrorist groups, criminals or even just people who want to fly their commercial drones in areas that are not allowed will not use drones with said beacons or they will eliminate or silence them in those drones that they use.

It is also crucial to consider the implications for society of any measures to detect and combat drones and how such solutions impact citizens, including:

• Psychological aspects : the presence of anti-drone systems increases the perception of being under threat and can generate psychological stress in societies, especially in densely populated areas. The deployment of these types of systems in civilian contexts can provoke feelings of unease and fear.

• Aspects of physical security and health : due to exposure to radio frequency signals used by detection systems (for example, radar), to neutralization systems (for example, interference or "jamming" systems, laser or energy systems directed, etc.) and others that can be dangerous for people in densely populated areas.

• Financial and economic aspects : currently existing anti-drone detection systems are not designed to work in urban environments, but rather in open spaces, which makes their economic viability difficult to cover extensive urban areas (think of the city of Madrid, for example). in Spain with several million inhabitants and an approximate area of 600 km2) with innumerable areas difficult to cover due to the presence of tall buildings, communication antennas and mobile network transmitters, and the innumerable interferences of all kinds present in an urban area .

• Privacy Aspects : anti-drone systems are surveillance systems and should be treated as such. They collect information about drone users, collect images, generate visual data, and provide geolocation information, but they can also collect information about users and citizens that have nothing to do with drone identification. Therefore, its use must comply with the applicable data protection regulations.

The currently known state of the art does not sufficiently address or solve these problems. The following represents a list of inventions and techniques related to the problem presented:

• US20170039413A1 Commercial drone detection, Disney Enterprises Inc. • US9529360B1 System and method for detecting and defeating a drone, Cellantenna International Inc.

• US20170261613A1 Counter drone system, Raytheon BBN Technologies Corp.

• US20190219682A1 Systems and methods for detecting, tracking and identifying small unmanned systems such as drones, Xidrone Systems Inc. • US10825345B2 Devices, methods and systems for close proximity identification of unmanned aerial systems, Aozora Aviation LLC

• US9805273B1 Systems, methods, apparatuses, and devices for identifying and tracking unmanned aerial vehicles via a plurality of sensors, Dedrone Holdings Inc.

• US20180165972A1 Drone alerting and reporting system, Dronetraffic LLC. • US9119027B2 Sharing of location-based content item in social networking service, Meta Platforms Inc.

• US20170310772A1 Inferring the location of users in online social media platforms using social network analysis, HRL Laboratories LLC.

• US10841542B2 Locating a person of interest using shared video footage from audio/video recording and communication devices, A9 com Inc, Ring Inc. • US9282446B2 Location-aware content and location-based advertising with a mobile device, Golba LLC.

• US9503533B2 Network manager system for location-aware mobile communication devices, Green Dot Corp.

As drones become more technically sophisticated, it is essential that in addition to having fast detection systems that cover all areas of interest in an urban area and that resolve the drawbacks of the aforementioned systems , aviation authorities, security forces law enforcement, local, regional and national governments and other stakeholders create unified drone threat reporting systems by reporting sightings and incidents to ensure a consistent drone threat reporting system to effectively identify incidents and address modus operandi of criminals using these technologies. This will further help distinguish the risks created by irresponsible drone pilots from those created by criminals and terrorist groups.

EXPLANATION OF THE INVENTION

The present invention is related to the field of detection and identification technologies of unmanned systems, artificial intelligence, image processing and computer vision, deep learning and object recognition, as well as the field of networks. social. The present invention can be applied to the field of smart cities (“Sm art Cities”) and smart security (automated process that allows the collection and analysis of indicators of possible threats to security to later evaluate these threats and take appropriate action). appropriate actions).

In order to solve the aforementioned drawbacks, the present invention describes and refers to a method of detection, location and identification of unmanned systems, a system, a device and a computer program which allow the provision of information (location , textual, graphic, etc.) about unmanned systems to a central system and to mobile devices (for example, mobile phones, smartphones or "smart phones", tablet systems or "tablets" or similar devices). The phases or basic blocks that define our method and system according to one of its realizations are presented in Figure 1 and would be:

1. Detection by a citizen or user of the social network of an unmanned system in their proximity.

2. Upload on the social network by the citizen of information of interest for sharing about the detected unmanned system, either in the form of text, coordinates with the user's location, photographs, audio and video or any other in another format. .

3. Representation in the social network of the location of all sightings reported by citizens on a map or in a detailed list.

4. Classification in the social network of unmanned vehicles detected based on the threat level assessment by users of the social network or by automatic Artificial Intelligence systems, based on geographic criteria or any other criteria.

5. Generation and issuance of alerts to other systems, to the competent authorities or to citizens in the proximity of the unmanned systems detected and present in the social network.

In one embodiment, when a user detects (whether visually, acoustically or otherwise) an unmanned aerial system, said user through the social network application available on his mobile notifies the presence of said unmanned system. to the system of our social network, adding textual information, location, images, videos, audios or others referring to the unmanned system taken by said user. In another embodiment, an authorized user may use the mobile device to query an unmanned aerial system application server/database to add information about the detected unmanned aerial system as well as its threat level.

In one embodiment, a user of our social network located within an area where another user has reported the existence of an unmanned aerial system, can receive information about the presence of said unmanned system along with data from the global positioning system. to locate the user who has reported the sighting, position data and images of said unmanned system and, in some cases, processed or raw text information about the sighting of the unmanned system provided by other users and experts connected to the system. In some embodiments, the mobile device may retrieve information from at least one database using available unmanned system identification information. The social network application on the mobile device can thus show the user the information of the unmanned system associated with the manufacturer and model from at least one database.

The present embodiments allow the images, videos or any other type of information captured by user mobile devices to be transferred to the social network and shared with anyone who has access to the unmanned vehicle detection social network and with the authorities. competent, issuing alerts in real time for those users registered to receive them.

In any urban area, many people have such devices as smartphones, which are equipped with cameras and microphones and are capable of capturing audio and/or video from any unmanned vehicle that is located in the vicinity of the user. The communications network that facilitates the exchange of information about said drones is the mobile network of each user (whether 4G, 5G, Wifi or other). The use of this system facilitates the identification of citizens reporting the sighting, being an agile early warning method for the authorities.

The main advantages of our invention include:

1. Citizens are involved in the generation of information related to sightings and detection of unmanned vehicles, eliminating most of the elements that cause stress in citizens regarding new surveillance systems.

2. Health and safety risks due to exposure to radio frequency signals used by current detection systems (for example, radar) that may be dangerous to people in densely populated areas are eliminated .

3. Unmanned vehicle detection time is reduced by having a huge base of citizens and devices at any location in the surveillance area or urban area. The density of sensors (taken in this case as citizens who have a mobile terminal) means that the probability of detecting unmanned vehicles in real time is several orders of magnitude higher than current systems .

4. The detection and information to citizens of any incident related to unmanned vehicles is automated.

5. The use of an infinite number of low-cost mobile devices whose location varies over time and that allow unmanned vehicles to be detected both indoors and outdoors is allowed.

6. The existence of dead spots where unmanned vehicles cannot be detected is reduced and even eliminated.

7. The investments required to detect unmanned vehicles are reduced.

BRIEF DESCRIPTION OF THE DRAWINGS

To complement the description that is being made and in order to help a better understanding of the characteristics of the invention, a set of drawings is attached as an integral part of said description where, for illustrative and non-limiting purposes, what has been represented has been following:

Figure 1. - Figure 1 represents the basic blocks of the invention, according to one of its embodiments, where block 101 detects an unmanned system by a social network user. In block 102 said user uploads to the social network information of interest regarding the detected unmanned system for sharing with other users of the social network. In block 103, the social network locates the unmanned system detected by the user in the informed coordinates for its representation in the social network of the location together with all the sightings reported by the users of the social network. In block 104, our social network system classifies the unmanned vehicles detected based on various parameters (criticality, type of vehicle, location, information generated by expert users, etc.). In block 105, the social network system generates and issues alerts to the competent authorities or to the citizens who receive them through the mobile user application of the social network.

Figure 2. - Figure 2 represents an embodiment of the system where a social network system (201) and a mobile user application (202) are presented, as well as an embodiment of its components and subsystems.

The social network system (201) comprises:

• A module for sending and receiving information (2011) that performs all the management of receiving information sent by the user mobile applications (202) as well as sending information to the user mobile applications (202) that can include information location of all detected unmanned systems, detailed information of said systems, information related to the trajectory recorded in the past, currently and estimated that these unmanned systems will follow, etc.

• A location processing module (2012) that receives the reported location of all detected unmanned systems, of which users of the social network, and that allows to manage and define locations marked as critical (those that should not fly over unmanned vehicles), etc.

A Content Publishing module (2013) that, based on all the information collected from users through the user's mobile applications (202) and others generated by other modules, allows the generation of content for publication both in the mobile applications of user (202) as in other modules of the social network system (201). In one embodiment, this information could be information on the detected drone model, comments about it made by drone identification experts, results of automatic drone identification modules based on image recognition using artificial intelligence algorithms, etc.

A graphic representation module in the form of maps (2014) that allows, based on the information collected and processed by other modules, to represent the position of all unmanned vehicles detected by users of the social network on a graphic map, as well as critical locations, buildings or marked places, etc.

A representation module in the form of a list (2015) that allows, based on the information collected and processed by other modules, to represent in a list detailed data of all the unmanned vehicles detected by the users of the social network, including their position, the manufacturer and model data, height, and any other graphic or textual information stored in the social network system.

An Unmanned Systems Database (2016) that allows to store all the information sent by the users of the social network through their user mobile applications (202) as well as information generated by other users and by other modules of the social network (201). In one embodiment, this database would store information on all sighted unmanned systems, images, videos, audios and user comments regarding this sighting, etc. This database would also store information about all types of drones, their main characteristics, images, etc. of all known manufacturers and models on the market, as well as new models discovered through different runs of the social network system (201) in a city or in all cities where the social network system (201) of shape independent.

• An alert Generation and Issuance module (2017) that is responsible for generating alerts according to different conditions and issuing them so that they are presented to the relevant users in their mobile user applications (202).

The mobile user application (202) comprises:

• A module for issuing and receiving information (2021) that performs all the management of receiving information sent by the social network system (201) as well as sending information from user mobile applications (202) to the communication system. social network (201) that can comprise location information of all detected unmanned systems, user location information, photographs, videos, audios, texts and comments about the situation, etc.

• A location processing module (2022) that receives the reported location of all detected unmanned systems, from users of the social network, which allows managing and defining locations marked as critical (those that should not fly over unmanned vehicles). ), etc. and that allows the management of the location of the user's mobile application (202)

• A Content Publishing module (2023) that, based on all the information collected from users through the user's mobile applications (202) and others generated by other modules, allows content to be generated for publication in the user's mobile application. user (202) as well as in the social network system (201). In one embodiment, this information could be information on the detected drone model, comments about it made by experts in drone identification, results of automatic drone identification modules based on image recognition using artificial intelligence algorithms, user's own information, etc

• A graphical representation module in the form of maps (2024) that allows, based on the information collected and processed by other users and the social network system (201), to represent the position of all detected unmanned vehicles on a graphic map. by users of the social network, as well as critical locations, buildings or designated places, etc. as well as the user's own location.

• A representation module in the form of a list (2025) that allows, based on the information collected and processed by the social network system (201), to represent in a list detailed data of all the unmanned vehicles detected by the users of the social network including its position, manufacturer and model data, height, and any other graphic or textual information stored in the social network system.

• An Unmanned Systems Database (2026) that allows the storage of all or part of the information sent by users of the social network through their mobile user applications (202) as well as information generated by other users and by others. modules of the social network system (201). In one embodiment, this database would store information on all sighted unmanned systems, images, videos, audios and user comments regarding this sighting, etc. In another embodiment, this database would also store information about all existing types of drones, their main characteristics, images, etc. of the drones sighted in the city or in the area where the user is located.

• An alert Presentation and Management module (2027) that is responsible for presenting and managing the alerts sent by the social network system (201) so that they are presented to the user in his mobile user application (202).

Figure 3. - Figure 3 represents an embodiment of the system where a social network system (301) and several social network user mobile applications (302) are presented, as well as several unmanned systems (303) located in different areas from a city where they are detected by different citizens (304) who have the social network user mobile application installed on their mobile devices (302). Through said mobile application (302) citizens (304) or members of the police (305) report the location and existence of an unmanned system (303) to the social network system (301) providing text information describing the situation, photographs, videos and audio of the unmanned system and any other information that may be of interest. The social network system (301) receives all the information from the different unmanned systems (303) sighted by users of the social network (304 and 305), using the location information provided by the users to store the position at all times. of these systems manned and in turn distribute this information to user mobile applications (302). In this way, users can see in the map application included in the user's mobile application (302) of the social network the location of all sighted unmanned systems (303) and receive the relevant notifications in said mobile application.

PREFERRED EMBODIMENT OF THE INVENTION

Figure 1 graphically explains the method used in a preferred embodiment of our invention:

• In block 101, the detection of an unmanned system (303) by a user (304) of the social network is performed, either visually, acoustically or otherwise.

• In block 102 said user (304) uploads to the social network (301) information of interest regarding the detected unmanned system (303) for sharing with other users of the social network. Said user (304) through the user's mobile application (302) available on his mobile notifies the presence of said unmanned system (303) to the social network system (301), adding textual information, location, images, videos, audios or other related to the unmanned system taken by said user.

• In block 103, the social network (301) locates the unmanned system detected (303) by the user (304) in the informed coordinates for its representation on a map in the social network (301) and/or on a map in the user's mobile application (302) together with all the sightings reported by users of the social network.

• In block 104, our social network system (301) classifies the unmanned vehicles (303) detected based on various parameters (criticality, type of vehicle, location, information generated by expert users, etc.).

• In block 105, the social network system (301) generates and issues alerts to the competent authorities (305) or to citizens (304) who receive them through the mobile user application (302) of the social network.

According to a second aspect, this description discloses a computer system comprising a processor, memory, and instructions stored in memory that, when executed by the processor, cause the computer system to perform one or more of the described methods. For example, the social network system (201) may comprise a processor and memory containing instructions that, when executed, cause the system to perform a method of receiving and providing information to users of the social network, the method comprising : determine the position of all unmanned aerial systems within a space from the information received from all user mobile applications (202) and transmitting said information from the social network system (201) as well as alerts to all user mobile applications (202).

For example, the mobile user application system (202) may comprise a processor and memory containing instructions that, when executed on a mobile device, cause the system to perform a method of receiving and providing information to users of the application. social network (304), comprising the method: determining the position of an unmanned aerial system (303) detected by the user (304) within a space and transmitting from the user's mobile application (202) to the social network system (201) information of said unmanned system (303) detected, this information comprising photographs, videos, audios, locations and coordinates, texts and comments.

Regarding the Industrial application of our invention, this invention applies to services required by institutional clients (local, regional, national governments, fire brigades, police and armies), private (corporations or companies), which require early and real-time detection of intrusions by unmanned aerial vehicles in their control and/or action areas, being of special application in:

• Smart Cities Control Centers.

• Airspace Control Centers.

• Police Control Centers.

• Deployments of police or military forces in urban areas.

Claims (8)

1. Method to detect unmanned aerial vehicles comprising: to. Detection by a citizen or user of the social network of an unmanned system in their proximity either visually, acoustically or in any other way. b. Upload to the social network system (201) through a mobile application (202) by the user of information of interest for sharing about the detected unmanned system, whether it is information in the form of text, coordinates with the location of the user or unmanned system, photographs, audio and video or any other information in another format. c. Representation on the social network of the location of all sightings reported by users on a map or in a detailed list. d. Classification in the social network of unmanned vehicles detected based on the evaluation by users of the social network or by automatic Artificial Intelligence systems, or based on geographic criteria or any other criteria (criticality, type of vehicle , location, information generated by expert users, etc.). and. Generation and issuance of alerts to other systems, to the competent authorities or to the users' mobile applications (202) reporting the presence of unmanned systems detected through the social network. 2. Method according to any of the preceding claims comprising: to. One or more social network systems (201). b. One or more user mobile applications (202). A method according to any of the preceding claims, wherein the social network system (201) comprises: to. A module for sending and receiving information (2011) that performs all the management of receiving information sent by the user mobile applications (202) as well as sending information to the user mobile applications (202). b. A location processing module (2012) that receives the reported location of all detected unmanned systems, from the users of the social network, and that allows to manage and define locations marked as critical (those that should not fly over unmanned vehicles), etc. c. A Content Publishing module (2013) that allows generating content for publication both in user mobile applications (202) and in other modules of the social network system (201). d. A graphic representation module in the form of maps (2014) that allows, based on the information collected and processed by other modules, to represent the position of all unmanned vehicles detected by users of the social network on a graphic map, as well as critical locations, buildings or marked places, etc. and. A representation module in the form of a list (2015) that allows, based on the information collected and processed by other modules, to represent in a list detailed data of all the unmanned vehicles detected by the users of the social network, including their position, the manufacturer and model data, height, and any other graphic or textual information stored in the social network system. F. An Unmanned Systems Database (2016) that allows the storage of all or part of the information sent by users of the social network through their mobile user applications (202) as well as information generated by other users and by other modules of the social network system (201), as well as information about all types of drones, their main characteristics, images, etc. from all known manufacturers and models on the market, as well as new models discovered through different runs of the social network system (201). g. An alert Generation and Issuance module (2017) that is responsible for generating alerts according to different conditions and issuing them so that they are presented to the relevant users in their mobile user applications (202). A method according to any of the preceding claims, wherein the mobile user application (202) comprises: to. A module for issuing and receiving information (2021) that performs all the management of receiving information sent by the social network system (201) as well as sending information from user mobile applications (202) to the network system social (201). b. A location processing module (2022) that receives the reported location of all the unmanned systems detected, from the users of the social network, that allows to manage and define locations and that allows the management of the location of the mobile application of the user (202) c. A Content Publishing module (2023) that from all the information collected from users through the user's mobile applications (202) and others generated by other modules, allows generating content for publication in the user's mobile application (202) as well as in the social network system (201). d. A graphic representation module in the form of maps (2024) that allows, based on the information collected and processed by other users and the social network system (201), to represent on a graphic map the position of all unmanned vehicles detected by the users of the social network, the position of critical locations, buildings or designated places, etc. as well as the location of the user himself. and. A representation module in the form of a list (2025) that allows, based on the information collected and processed by the social network system (201), to represent detailed data of all unmanned vehicles detected by network users in a list including your position, manufacturer and model data, height, and any other graphic or textual information stored in the social network system. F. An Unmanned Systems Database (2026) that allows the storage of all or part of the information sent by users of the social network through their mobile user applications (202) as well as information generated by other users and by other modules of the social network system (201), as well as information about existing or known types of drones. g. An alert Presentation and Management module (2027) that is responsible for presenting and managing the alerts sent by the social network system (201) so that they are presented to the user in their user mobile application (202). A method according to any of the preceding claims, wherein the social network system (201) comprises: to. An automatic learning system that automatically detects an unmanned vehicle from the information (images, videos, audio, text or any other) provided by users of the social network. b. An automatic learning system that automatically locates an unmanned vehicle based on the information (coordinates, images, videos, audios, texts or any other) provided by users of the social network. c. An automatic learning system that allows to automatically identify an unmanned vehicle from the information (images, videos, audios, texts or any other) provided by the users of the social network. A method according to any of the preceding claims, wherein the mobile user application (202) comprises: to. An automatic learning system that automatically detects an unmanned vehicle from the information (images, videos, audio, text or any other) provided by users of the social network. b. An automatic learning system that automatically locates an unmanned vehicle based on the information (coordinates, images, videos, audios, texts or any other) provided by users of the social network. c. An automatic learning system that allows to automatically identify an unmanned vehicle from the information (images, videos, audios, texts or any other) provided by the users of the social network. 7. System configured to implement the method according to any of the preceding claims, characterized in that the system comprises: a. One or several data connections to collect data from the internet, databases, mobile devices or any other external storage medium. b. At least one memory device. c. At least one processor. d. At least one computer program that when executed on at least one processor performs the method according to any of the previous claims. and. At least one database that stores the information of the unmanned systems detected by the users of the social network. F. At least one database that stores information about all the types of drones existing on the market or known, their main characteristics, images, etc. for all known manufacturers and models on the market, as well as new models discovered through the system presented here. 8.

System configured to implement the method according to any of the preceding claims, characterized in that the system comprises: to. A social network system (201) running at one or more locations. b. A social network mobile application system (202) running on mobile devices.