METHOD FOR PRODUCING, ORGANIZED AND DISTRIBUTING GEOREFERENCED DIGITAL CONTENT ON THE GO, AND RELATED METHOD FOR DEVELOPING CONTEXTUAL MULTIMEDIA GUIDES, THROUGH THE USE OF ARTIFICIAL INTELLIGENCE AND THE USE OF GEOLOCATED DIGITAL AND / OR VIRTUAL MAPS

Description

I0206715-SB “Method for producing, organizing and distributing content georeferenced digital data on the move, and related method for the development of contextual multimedia guides, 5 through the use of artificial intelligence and use of geolocalized digital and / or virtual maps” DESCRIPTION TECHNOLOGICAL BACKGROUND OF THE INVENTION Scope of application. 10 The present invention relates in general to the technical field of production, organization and distribution of georeferenced digital content in mobility, carried out through electronic processing. The present invention also relates to 15 in the field of multimedia guide development contextual through the use of artificial intelligence and use of geolocalized digital maps, in particular attention to the development of tourist guides contextual multimedia, generated by Intelligence 20 Artificial based on position, direction parameters, user speed and element recognition visual and informative present in virtual maps and geolocalized historical or design reconstructions. Description of the known art. 25 The field of digital tourist guides is a application enabled by the spread of devices furniture equipped with GPS or other georeferencing systems, from navigators to smartphones, tablets and “smart glasses”. 5 The sectors with the greatest employment are tourism and cultural heritage, but there are also contextual applications linked to the fields of marketing, services, of building and construction, transport or others. The state of the art includes solutions that allow 10 to deliver content to users according to rather logics elementary, connected to points of interest arranged in the territory or on a map or according to sequential itineraries, without a particular methodology dedicated to the production, organization and distribution of content. 15 On the other hand, guidance systems are spreading tourism based on "computer vision" techniques, which recognizing the monuments, they do not take into account factors relevant such as the speed of the user's movement, or the scale of importance of the points of interest present, or 20 still the availability of reconstructions of the past and of the future of the surrounding environment, and therefore leave the above needs are unsatisfied and the above issues are unresolved technical problems. Among the various technical problems not resolved by the 25 known solutions, the question can also be mentioned regarding attention to ergonomic and safety of a moving user, be it a pedestrian, on two or four wheels: the user on the move has the need to engage the sight in monitoring the environment, without 5 distracting you from driving or otherwise from the route with messages written, visual or interactive touch interfaces, graphics or gestural. Furthermore, the difficulty of developing systems is critical low-cost content production and management 10 dynamically adaptable, dedicated to the production of content specifically intended for distribution in mobility. Although recent models have emerged of Generative Artificial Intelligence, potentially in 15 able to produce relevant content, and despite being geolocalized immersive maps have been known for some time (for example Google “Street View®”, virtual tours or 3D reconstructions), such general technical innovations are to date poorly understood considered in the context of production, organization and 20 distribution of georeferenced digital content in mobility, and in the development of guides contextual multimedia. In this respect, it is therefore particularly felt the need to solve the technical problems outlined above, 25 and, more generally, to have effective methods, flexible and reliable production, organization and distribution of georeferenced digital content in mobility, and the development of contextual multimedia guides. These needs, as illustrated above, are not currently 5 fully satisfied with the known solutions available. SUMMARY OF THE INVENTION It is the object of the present invention to provide a method of producing, organizing, and distributing georeferenced digital content on the move, 10 carried out by electronic processing, which allows us to at least partially overcome the inconveniences complained about above with reference to the known technique, and to meet the aforementioned needs particularly felt in the technical sector 15 considered. This aim is achieved through a method in agreement to claim 1. Further embodiments of this method are defined by claims 2-16. It is also an object of the present invention to provide 20 a method for developing multimedia guides contextual, using the above method. This purpose is achieved by a method in accordance with the claim 17. It is also an object of the present invention to provide 25 a corresponding electronic processing system in able to perform the above methods. This purpose is achieved through a system in accordance with the claim 18. Further embodiments of this system 5 are defined in claims 19-25. BRIEF DESCRIPTION OF THE DRAWINGS Further features and advantages of the method and of the system according to the invention will result from the description below of favorite examples of 10 realization, data for indicative and non-limiting purposes, with reference to the attached figures, in which: - figure 1 is a diagram representing in simplified form the method of the invention, according to a embodiment, illustrating in particular 15 interactions between a user's mobile device and a map immersive; - figure 2 is a schematic representation simplified view of the main components of a platform included in one embodiment of the 20 system according to the invention, capable of carrying out the above method. DETAILED DESCRIPTION. A method is described for producing, organizing and distribute georeferenced digital content in 25 mobility. The method is carried out by electronic processing. The method first of all involves preparing or access at least one geolocalized digital map, designed to provide a visual three-dimensional model, and / or 5 including other digital multimedia content, of each of a plurality of points of interest present in a geographical area covered by the digital map geolocalized. The method then includes the phase of obtaining or 10 determine a user's geolocation data, including at least one user location and information related to the user's movement. The method also includes the step of determining, based on the aforementioned geolocation data 15 of the user, a digital point of view of the user, within the geolocalized digital map, representative of a real user point of view in real space, dynamically variable depending on of the user's movement. 20 This digital point of view is associated with at least one of the above three-dimensional models present in the geolocalized digital map, corresponding to points of interest visible from the user's real point of view. The method then provides for generating by means of 25 artificial intelligence, and / or derive from the map geolocalized digital, digital data of reference points interest, including at least one visual model three-dimensional and / or other multimedia digital content relating to at least one of the aforementioned points of interest 5 associated with the user's digital point of view. Such digital point of interest data are dynamically variable depending on movement of the user. The method finally includes the phase of organizing and 10 provide the user, through an interface of digital display of a mobile device of the user, the aforementioned digital data of points of interest, dynamically variable, generated and / or derived, associated from the user's digital point of view. 15 In accordance with one embodiment of the method, the aforementioned phase of preparing or accessing a map geolocalized digital includes preparing or accessing to an immersive geolocalized digital map and / or to a virtual geolocalized digital map corresponding to 20 a “digital twin” of what is in an area geographic area represented by the “digital twin”. According to one embodiment of the method, the the aforementioned phase of obtaining or determining data geolocation of a user includes obtaining or 25 determine geolocation data including a user position, a direction of movement of the user and a speed of the user. According to an implementation option of this form of realization, the aforementioned phase of determining a point 5 of the user's digital view includes determining the digital point of view of the user in a dynamic way variable, based on user position, direction of the user's movement and speed. In accordance with one embodiment of the method, 10 the aforementioned phase of generating and / or extracting digital data of points of interest includes obtaining digital data of points of interest from the digital map geolocalized. In accordance with one embodiment of the method, 15 the aforementioned phase of generating and / or extracting digital data of points of interest includes generating digital data, through a trained intelligence model artificial. In accordance with one embodiment of the method, 20 the aforementioned phase of organizing and providing the user with data digital points of interest includes generating and / or organize and / or manage and / or distribute content digital devices optimized for movement / mobility of the user, providing data based on the point of view 25 dynamically variable digital corresponding to the point from the user's actual view. According to an implementation option of this form of realization, the aforementioned phase of generating and / or organize and / or manage and / or distribute content 5 digital devices optimized for movement / mobility of the user is carried out using an algorithm of definition of “moving content”, which establishes content production and distribution criteria optimized for mobility and personalized to the user. 10 According to an implementation option of this form of realization, the method includes the further phase of produce and disseminate digital content in relation to user position, direction, speed. Further exemplifying the above option 15 implementation, text generation is governed from the aforementioned "algorithm for the definition of content “moving” in relation to the user's speed. If you cross a city or a valley by car or by bicycle, and therefore the presence of a point of interest 20 to the user's sight and attention is relatively more short, texts can be generated so that they can be much shorter than those produced for a user who is walking on the same path, walking along it so more slowly. 25 If the speed is high, the method will provide, appropriately, only texts related to the scale of higher importance, for example the generic description of the landscape, of the city or of the valley, with short any references to the square. 5 Instead, if the speed is low, the method delivers appropriately delivers content even for more detailed information specific ones corresponding to a higher scale of importance low, for example the buildings present. In case the speed becomes zero, with the user 10 stop, the method requires that we proceed with higher levels in-depth and therefore long and detailed texts. According to another implementation option of this form of realization, the method includes the further phase of produce and distribute digital content for the purpose of 15 interests indicated by the user, using a template trained in artificial intelligence. According to some possible implementation options of this form of embodiment, the organization of the content generated by Artificial Intelligence is 20 hierarchical, and / or the organization of the generated content from Artificial Intelligence takes into account a scale default of geographical importance and / or in which the organization of content generated by Intelligence Artificial is multilingual and / or the organization of the 25 contents generated by Artificial Intelligence is such that adapt to different narrative registers or registers of presentation, user-dependent. For example, the method provides information in a dependent on age and / or cultural level and / or 5 user's cultural tradition. According to an implementation example, the model is trained to describe a church differently if the user is Western and of Christian tradition, compared to the cases of a Middle Eastern user of 10 Islamic tradition. In the first case, they can be given as discounted the functions of the parts of a church, in secondly it is appropriate to distinguish and describe, for example, the function of a bell tower versus a minaret, and similarly it will not be necessary to detail what it is 15 a saint or patron - who gives the church its name - for the Western users, while it is appropriate not to give it away discounted for Islamic users. How easily intuitive, a conceptually similar but "dual" approach compared to the previous one it is applied for the description 20 of a mosque. According to an implementation example, the model is trained to illustrate a point of interest with a different narrative register if the user is a child compared to the narrative register used for an adult. 25 With reference to the above organisation of the content dependent on a predefined scale of importance, it consists, in an implementation example, in a hierarchy management, in terms of code of “scale of importance”, of the points of interest detected 5 in context (for example, according to a hierarchy / scale of geographical importance: city-square-palace-portal). In accordance with one embodiment of the method, the above digital point of interest data includes descriptive data of the present appearance of one or more points 10 of interest, or of all visible points of interest from the user's point of view. In accordance with one embodiment of the method, the above digital point of interest data includes descriptive data of the past appearance of one or more points 15 of interest, or of all visible points of interest from the user's point of view, at a given time, on the computer graphics image reconstruction base geolocalized and referring to the aforementioned era. In accordance with one embodiment of the method, 20 the above mentioned digital data of points of interest include descriptive data of the future appearance of one or more points of interest, or of all visible points of interest from the user's point of view, based on rendering or digital reconstructions associated with a project 25 referring to an area surrounding the viewpoint of the user. In accordance with one embodiment, the method provides a two-way interaction between a device user's mobile and the aforementioned at least one digital map 5 geolocalized. In this case, the method includes the further stages of: - transmit to electronic processing means, in which the aforementioned at least one digital map is implemented geolocalized, by the user's mobile device, 10 the above information relating to position, direction and user speed; - get at least one digital map geolocalized a visual recognition, for example using Computer Vision, of images and points of interest 15 present in the user's digital point of view, by of electronic processing means; - obtain from at least one digital map geolocalized information relating to the elements recognized as present in the digital point of view 20 of the user; - create descriptive content, based on the the aforementioned information obtained by the said means of electronic processing using techniques of artificial intelligence; 25 - transmit to the user's mobile device the aforementioned descriptive contents created, in one or more multimedia modes: audio commentary, text card, images, videos, 3D formats. Please note that the above embodiment 5 allows you to make the most of the optional presence of a computer vision device available to the user, it being understood that the method of this invention, in its most general definition and in other embodiments, can be done in the absence 10 and regardless of “computer vision” functions (for example for example, it can also be used by a user who keeps the smartphone in your pocket, without using a camera, and with transmission of information to the user via audio). In the embodiment considered herein, wherein 15 the user wears for example a “smart glass” device or use a device with a camera and connected to a Computer Vision AI model, you can advantageously acquire information also from the direct recognition of monuments or places. 20 Even in this case, it remains valid and appropriate the use of the above mentioned algorithm for the provision of mobile content, which presides over for example the processing the length of texts and audio vocals in relation to the user's speed, but also 25 in relation to the aforementioned management of the hierarchy of points of interest (e.g. city-square-palace- portal) and the generation of the related texts descriptive. Furthermore, even if the current monuments 5 are recognized directly by vision artificial, the method, according to an option implementation, is distinguished by the correlation and description with reconstructions of the past or future of the environment, obviously not visible from the camera 10 that frames the present, but only from a virtual environment parallel. In the case of reconstructions of the past and the future, the method involves transmitting to the user not not only the textual descriptions but also the images of the reconstructions. 15 Thus, in the above embodiment, the “computer vision” from a camera in the real environment constitutes an alternative and / or additional source of data relating to the surrounding environment, compared to the presence detection from a digital map or 20 virtual, in particular thanks to the recognition of buildings or other elements present. Even in this case the algorithm for defining the content in movement maintains its role in the generation and content organization with respect to speed, 25 scale of importance and other criteria described. According to one embodiment, the method provides the delivery of content in simulations of paths with gym equipment. The algorithm that manages the delivery of content in 5 movement, in fact, can be applied not only in the physical movement of people in reality but also in movement simulation performed with gymnastic equipment, (e.g. treadmills, exercise bikes and rowing machines, synchronized with virtual worlds), as foreseen in 10 this embodiment. In these cases normally the direction and sense of march are constrained (you always move forward along a linear path) but the content can be generated, organized and delivered taking into account other elements: 15 of the position, of the distances, of the points of view, of the speed and pauses, but also the type of locomotion. In cases of virtual simulation the representation visual (video, 360 video, 3D, virtual tour) is detached and desynchronized from the description (written 20 or vocal) to manage speed changes and pauses. for example, a user can walk or run on a treadmill treadmill or pedaling on an exercise bike, at different speeds. Thanks to a monitor or a virtual reality viewer and to a sensor, its physical movement activates the 25 visualization of a path, natural or urban. Yes also activates a contextual description, such as a audio guide, which applies the rules of the algorithm content delivery on the go. The descriptions therefore concern the position and the 5 point of view in the virtual world represented, but yes change in relation to the speed with which the gymnastic instrument. Walking, running, breaks determine the length of texts and audio descriptions. Pauses, for example for example, they activate longer in-depth analyses, not 10 compatible with the speed of the race. Training the Intelligence Model Artificial intelligence for content generation on the move will have to take into account the different motor experiences corresponding to gymnastic instruments: locomotion 15 pedestrian (treadmill), cycling (exercise bike), canoeing (rower). The descriptive figure will also take into account the point of view, different for example on a cycle path with respect to a navigable body of water. A method for the following is illustrated: 20 development of contextual multimedia guides, including in the present invention. This method first involves carrying out a method for producing, organizing and distributing content georeferenced digital data on the move, according to a 25 any of the embodiments above illustrated, to obtain digital data of a plurality of points of interest, associated with a plurality of points of the user's digital views, dynamically variable in function of the user's movement. 5 The method then provides for generating by means of artificial intelligence the above multimedia guides contextual, based on position and direction parameters and user speed and element recognition visual and informative features present in immersive digital maps 10 and / or geolocalized virtual ones. A system is described below for produce, organize and distribute digital content georeferenced on the move, according to this invention. 15 This system comprises a mobile user device equipped with geolocation sensors and means of electronic processing, operationally connected to the user's mobile device. The above-mentioned means of electronic processing 20 include: - at least one virtual reality software application and / or immersive map, associated with at least one map geolocalized digital, configured to provide a three-dimensional visual model, and / or including other 25 digital multimedia contents, each of which is plurality of points of interest present in an area geographic area covered by the geolocalized digital map; - a software application or program capable of implement an infomobility algorithm, configured 5 to obtain and / or determine and / or interpret data geolocation of a user, including at least one user location and information about the user movement, and to determine, based on such user geolocation data, a point of 10 digital view of the user, inside the map geolocalized digital, representative of a point of real user view in real space, dynamically variable depending on the user's movement; the aforementioned digital point of view is associated with at least 15 one of the three-dimensional models present in the map geolocalized digital, corresponding to points of interests visible from the user's real point of view; - a trained AI model, capable of generating digital data of points of interest, 20 comprising at least one three-dimensional visual model and / or other digital multimedia content relating to at least one of the points of interest associated with the viewpoint user's digital data; the aforementioned digital point data of interest are dynamically variable depending on 25 of the user's movement. The above-mentioned artificial intelligence model trained is also able to organize and provide to the user, through a visualization interface digital data of the user's mobile device, digital data 5 dynamically variable points of interest generated and / or proceeds, associated with the digital point of view of the user. According to one embodiment of the system, the the aforementioned electronic processing means include, 10 or consist of, a cloud software platform. According to one embodiment of the system, the at least one reality software application mentioned above virtual includes a geolocalized digital map immersive and / or to a geolocalized digital map 15 virtual corresponding to a “digital twin” of what is located in a geographical area represented by the “digital twin”. According to an implementation option of the system, the at least one reality software application mentioned above 20 virtual is configured to display playbacks current digital data of one or more points of interest or of the surrounding environment, in the present, and / or data descriptive of the past appearance of one or more points of interest, in a given era, based on reconstructions 25 geolocated and referenced computer graphics images at that time, and / or descriptive data of the future appearance of one or more points of interest, based on rendering or digital reconstructions associated with a project referring to an area surrounding the viewpoint 5 of the user. In accordance with one embodiment of the system, the user's mobile device is also equipped with sensors of direction and / or speed and / or movement. According to one embodiment of the system, the 10 user's mobile device is also equipped with at least a visual recognition camera, and it is configured to transmit to processing media electronic information relating to position, direction and user speed. 15 In this embodiment, the means of electronic processing are also configured for perform the following actions: - carry out visual recognition, by means of Computer Vision, of images and points of interest present 20 in the user's digital point of view; - obtain from at least one digital map geolocalized information relating to the elements recognized as present in the digital point of view of the user; 25 - create descriptive content, based on said information obtained through intelligence techniques artificial; - transmit to the user's mobile device the above descriptive contents created. 5 According to one embodiment of the system, the trained artificial intelligence model is able to generate and disseminate digital content in time real, based on data entry by of the user or from relevant sources, depending on 10 interests indicated by the user, and / or with organization hierarchical, and / or taking into account a predefined scale of geographical importance, and / or through organization multilingual content and / or through different narrative registers or presentation registers, 15 user dependents. In accordance with several possible forms of realization, the system configured to perform a method according to any of the embodiments of the method previously described. 20 They are described below, by way of example exemplary and not limiting, further examples detailed application of the method according to the invention, referring to figures 1-2. As already illustrated above, the method provides 25 the introduction of a new cartographic concept and ergonomic, the “Point of view”, which is different from the “Point of interest” which traditionally corresponds to a element placed exactly in the coordinates geographic where a physical entity is located. 5 The “Point of view” instead indicates the position geographical, both punctual and areal, where it must be spread a specific content, in reference to what appears in front and is seen by the user in motion. For example, while the traditional “point of 10 interest” associated with a Cathedral is found exactly in the geographical position of the building, the The cathedral's “viewpoint” is located in the square in front of the building: it is in this position that the user will receive descriptive information about the cathedral 15 itself, such as an audio guide that illustrates the architecture, the facade and the characteristics of the monument. In most cases, the “Point of “view” corresponds to the optimal observation point from where you can get information about a "Point of 20 interest” that is being observed. The structured insertion of “Points of View” in a dedicated system allows you to build tourist guides digital, especially vocal but also multimedia, which offer the user on the move in an urban environment, 25 road or natural, relevant contextual information with what he is seeing, whether they are geographical, tourist or commercial. The production and organization process of the content, according to the present invention, presents the 5 following aspects of originality and innovation. The descriptive and multimedia content must be placed from the user's point of view in motion and produce contextual content, optimized to be enjoyed exactly in the "Points of view" that are 10 identified through algorithmic methodologies and systems of computer vision applied in virtual maps. content production method must be optimized for the mobile user experience in the environment. 15 Text generation, done by a model of appropriately generative Artificial Intelligence trained, according to one embodiment of the method, takes the form of an immersive script, that is, written by placing oneself in the point of view 20 of the user himself in a precise position of perception of the surrounding environment, but also in one direction and to a specific speed of movement. It should be noted that as the user moves, the points of view change, and therefore it is necessary to receive 25 information dynamically and adaptively compared to three parameters in the embodiment considered herein): position, direction, speed of movement. The multimedia guide experience changes if you for example, cross a square starting from one side 5 (looking at the facade of the cathedral), or from the side opposite (looking at the town hall); it is also different the experience of a slow pedestrian walk or a fast car crossing; again, change the perception (the Point of view) in reference to the 10 position: if you are in the center of the square, or close to the sculptural portal of the cathedral. It is therefore necessary to develop a method for prioritize and organize distribution and sequence of contents. 15 This objective involves the introduction of a further aspect, defined here as “algorithm for the moving content”. The task of the “content algorithm in movement” is to establish the criteria and order for the 20 content delivery to the user on the go. Corresponding to the “Points of view”, thanks to the user's geolocation obtained from GPS or other systems, the “algorithm for moving content” manages the individual information contents, proposing them 25 not only in the appropriate geographical location, but also distributing them in relation to the direction, to the speed, criteria and information priorities established by the system and indicated by the user (themes, expressed interests, weather, traffic, and so on), and 5 also taking into account the direction of travel. The main parameters of the “algorithm for the “moving content” are therefore the position of the user, the direction and speed of movement of the user. 10 According to embodiments of the method, they are considering aspects of hierarchy and sequence: scale of geographical and informational importance. In audio information the timeline is a relevant factor. 15 The use of an importance code (or other code specific) allows you to produce content according to a hierarchy corresponding to the geographical scale, and of establish a timeline in the message, which influences the editorial setting, for example 20 making it possible to manage: - welcome and introductory instructions of the guide, at the start; in general, beyond the specifications descriptions of a single point of interest, it is useful provide the user with a general overview of the area 25 tourist, or of the historical-artistic period-style of the monuments present in the area; in case you add also the presentation of reconstructions of the past or of the future, it is essential to start from a framework of the historical era or of the future project which is the object of the 5 reconstructions; - general messages on large areas (which in Depending on the level of importance, they can precede or follow other messages relating to more restricted areas); - incremental deepening sequences, also 10 superimposed in the same area, which interact with the user speed. If the user stops, listen, in the sequence established by the editorial staff, all messages relative to the area in which it is located. If it moves quickly, listen only to the primary information and then 15 passes to those present in the surrounding areas where you are moved. The definition of the importance scale of the content is relevant in order to educate a model of Artificial Intelligence to produce texts with 20 different levels of scale, to be distributed in relation to the user's position, speed and distance from points of interest. Training the intelligence model artificial responds then, in a form of 25 implementation of the method, to the following objectives: writing descriptive texts relating to a tourist itinerary of a users who provide general introductions to the area crossed, quick descriptions in case of crossing on a fast vehicle, descriptions 5 in-depth for slow passages or stops, narrations of details in case of close-up points of view. Artificial Intelligence, in a form of implementation, also manages the delivery time of the content, estimating the speed of in real time 10 crossing, and thus generating text fragments (audio) of the correct duration for the single stroke relevant crossed. Content generated by Artificial Intelligence they can be multilingual and adapt to various genres 15 narratives and to users with different cultural levels (such as illustrated in figure 2: PLATFORM COMPONENTS). According to some embodiments of the method, it adapts and integrates with various mapping options available. 20 Driving in extended reality, thanks to algorithms dedicated, generates and delivers different types of information depending on the different types of digital cartography available. Two types of are mentioned here, distinguishing them: 25 digital maps that can be made available today as a reference "digital twin" for the creation of Extended Reality Guides: - 2D digital cartography, consisting of maps geopositioned two-dimensional vectors, and 5 - 3D digital maps made up of 360 photos and from three-dimensional models of the environment, both geolocated. 2D digital maps allow for the provision of content everywhere, as today they cover practically 10 the whole planet, and thanks to GPS they can always define the position of the point of view in relation to the point of interest. In 2D maps, however, they are not provided information system on building elevations, for example 15 For example, the facade of a church. So the information generated by artificial intelligence will not describe the detail of the vertical surfaces. Thanks to a dedicated algorithm, it will then be possible to generate with artificial intelligence information about history 20 of the building, on the builders, on the owners, on the events that have occurred, on its overall form, on the style, and so on. If, in addition to 2D cartography, it is available a map with 360° photos, or 3D models, for example 25 “street views” or three-dimensional photogrammetries, the platform thanks to artificial intelligence can recognize the vertical parts of the building, and can then describe, for example, the facade and its components, such as the portal and the rose window, thus generating 5 a guide more closely related to the point of view real. The availability of geopositioned photogrammetry It also enables the exact positioning of 3D models in the environment, e.g. reconstructions 10 virtual archaeological sites above the remains of a building ancient, or the 3D model of the renovation project of a house on the house itself. Some embodiments of the method decline several possible customization options. 15 One of the tasks of the “content algorithm in “movement” is to manage the rotation of information in custom mode for the single user. Personalization occurs thanks to additional system components, in particular the classification 20 typology of contents, synchronization with factors time and personal settings interface. The classification of contents takes place according to a taxonomy geared towards meeting interests of the user. For example, in the case of tourist users, 25 can organize content by attractions artistic, historical, natural, accommodation facilities, tourist services, events, promotional offers. The user must be able to explicitly indicate, thanks to a personal settings interface, of which 5 type of content you intend to enjoy. When visiting a art cities, for example, the user can select the artistic attractions, and the “algorithm for content in “movement” organizes the corresponding “Points of view”. But even when the user has not explicitly 10 personalized content types, the “algorithm for the moving content” can organize automatically moving content in form personalized. Also synchronization with clock and calendar 15 allows the “moving content algorithm” to prioritize personalized content based on location and user situation. For example, if the user is driving along a coastal road on a summer morning, the “proximity algorithm” can prioritize the 20 information about the beaches, while the user who walking the same street in the evening can give content on restaurants. Customizing the “algorithm for the “moving content”, applied to a tourist guide 25 to be enjoyed on the go, it also allows you to avoid a tourist who passes by the same point to continue hear the same information. Another feature present in a form of implementation of the method is the rotation of the 5 information. The rotation of information allows to example of proposing, even in the same way motorway, different information on the outward journey and back. The speed of movement is also a factor 10 managed by the “moving content algorithm”: if the user quickly switches from a local cell the information must not be interrupted on the other hand. Conversely, if the user is stationary, for example in a queue highway or in front of a museum, the information units 15 must not be repeated. According to one embodiment, it is considering the appearance of the audio channel and the “text to speech” (“push” mode and translations). The basic ergonomic assumption is the use 20 of the “moving content algorithm” during the movement, when the user is engaged in driving automotive, two-wheeled or in travel pedestrian. Moving user cannot interact 25 actively, reading texts or looking at images, it is aimed therefore to privilege the audio channel: the information they are read aloud (produced with speech synthesis “Text to Speech”). Always to avoid interfering with driving, the 5 platform delivers content in PUSH format, that is, through automatisms defined by the “proximity algorithm”. An additional parameter for the distribution of the content is the temporal one: night time, day time, projection into the past or future of the place, time of 10 lunch or dinner, opening hours of functional buildings, even weather conditions. Content production makes use of potential offered by Artificial Intelligence, in in particular machine translation and text to speech 15 with synthetic pronunciation in multiple languages. There are also situations of more widespread use interactive and less passive, for example on the part of non- driver but passengers on board a vehicle transport, or for the use of the contents before or after 20 the journey, or if the user stops and wants to enjoy additional content. In the more interactive consultation modes the The system also allows you to read texts, and provides for the transmission of images, both 2D and 3D, which can 25 be synchronized to the audio. Spatio-temporal variants of the point of view: “elevator” and “time machine”. On several occasions, it may make sense to develop of the spatial or temporal variants of the “Point of View”. 5 In particular, where the view at human height is hindered by visual disturbance factors, for example trees, walls, other obstacles, the system can resort to to an aerial view, raising the point of view beyond the obstacles and describing what lies beyond. 10 A further variant of the “Point of view” is temporal nature: if the current appearance of the environment is of little importance, the description can move on to illustrate reconstructions of the past or plans for the future. This, for example, may concern archaeological sites 15 without risers, difficult to interpret by non- experts, or ongoing construction sites. The description in these cases does not therefore concern the context as it appears today, but as it was in the past or how it will be in the future. 20 “Data Ingestion” and information processing geolocalized. Training the intelligence model artificial, and its feeding with data also in real time, it can happen in different ways. 25 The simplest is the use of online databases of geolocalized information (texts, images or other contents). For example, data acquisition is relevant Open Source like Wikipedia entries, in particular 5 of which are related to geolocalized points of interest. Wikipedia offers a huge number of entries relating not only to localities, but also to individual monuments and attractors. These entries include latitude and longitude, textual descriptions but also images. 10 textual descriptions, in the form of encyclopedic entries, will be treated by the Artificial Intelligence model to take the narrative form relevant to the guide and with the “algorithm for moving content”. images help to identify 15 visually what appears in front of the user. The system also includes a “Data Ingestion” which allows you to manually enter geolocalized information (texts, images, coordinates) relating to any point of interest, whether it is present 20 in the present, past, or future environment. Ad for example, it will be possible to insert descriptive cards of Points of interest of an archaeological site or a construction site, but also computer reconstructive images graphics of the past appearance (virtual archaeology) or of the 25 future project (CAD design). Computer Vision: Applied to an Immersive Map or via camera. In case of using a camera and visual recognition of monuments, the method deals with 5 however of the generation and delivery of contents in movement, in relation to the user's speed and other criteria described. In the presence of reconstructions of the past or future the camera is not able to provide any information from the images herein, 10 and therefore the method allows to integrate descriptions and images of the reconstructions themselves in coherence with the features mentioned. A further feature of the method for the production, organization and distribution of 15 georeferenced digital contents on the move, it concerns the ability to provide content to the user in movement not only based on geographical location, detected via GPS, but based on visual recognition of the surrounding environment. 20 In this case the reference technologies are the “visual recognition” and “visual search”, activated in two distinct modes: a) Access to a geolocalized immersive map that replicates the environment the user is in (e.g., 25 Google Street View, a virtual tour or a reconstruction 3D environmental data). Dynamic geolocation data (position, direction, speed) detected by the sensor device are transmitted to the immersive map, which shows the virtual images corresponding to the “point of 5 real view. Thanks to the visual recognition of the virtual images and the presence of a database of points of interest, the system generates the contents according to the criteria dictated by the "algorithm for the content in movement”. For example, if I am walking along the streets of a 10 historic center, my mobile device detects my position, direction and speed and passes them to the virtual map, which frames the same street where I am I find and allow the recognition of images and points of interest (e.g. buildings, churches, news 15 historical…) inserted in the virtual map. b) a camera that frames objects present in the external environment. In this case it is applied in a classic Visual Recognition: the system recognizes the elements that are in front of the user and pass the 20 given to the Artificial Intelligence model in charge of generate the contents, always according to the dictated criteria from the “moving content algorithm” (position, speed, direction) and also in the case where the description concerns reconstructions of the past and of the 25 present, not visible in camera footage. The scope of application concerns, in the two cases mentioned, the following devices: A. All mobile devices connected to the network and equipped with of motion sensors and microphone 5 B. all mobile devices connected to the network equipped with of digital cameras, from smartphones to tablets, to in-car cameras and smart glasses. As can be seen, the purposes of this invention, as previously indicated, are 10 fully achieved by the above method and system described, by virtue of the characteristics above illustrated in detail. In fact, the method and system described above respond to the need to solve technical problems 15 outlined at the beginning of this description and to have of effective, flexible and reliable solutions production, organization and distribution of content georeferenced digital devices on the move, and the development of contextual multimedia guides 20 In particular, the method and system described above offer a technical solution for producing, organizing and distribute georeferenced digital content, intended specifically for mobile distribution, low cost and dynamically adaptable, that is, capable of being 25 provided in ways appropriately adapted to variables what are the movement conditions and speed of user movement, or the importance scale of the points of interest present, or others. To the embodiments of the method, of the 5 device and system described above, a technician of the branch, to meet contingent needs, will be able to contribute modifications, adaptations and replacements of elements with others functionally equivalent, without leaving the scope of the following claims. Each of the features 10 described as belonging to a possible form of realization can be done independently from the other embodiments described.

Claims

1. A method for producing, organizing, and distributing georeferenced digital content on the move, performed using computer processing, comprising: - preparing or accessing at least one geolocalized digital map, capable of providing a three-dimensional visual model and / or including other multimedia digital content, of each of a plurality of points of interest present in a geographic area covered by the geolocalized digital map; - obtaining or determining a user's geolocation data, including at least one user position and information relating to the user's movement;- determining, based on said user geolocation data, a digital viewpoint of the user within the geolocalized digital map, representative of a real-world viewpoint of the user, dynamically variable based on the user's movement, wherein said digital viewpoint is associated with at least one of said three-dimensional models present in the geolocalized digital map, corresponding to points of interest visible from the user's real-world viewpoint; - generating, using artificial intelligence, and / or extracting from the geolocalized digital map, digital point-of-interest data, including at least one three-dimensional visual model and / or other digital multimedia content relating to at least one of said points of interest associated with the user's digital viewpoint, said digital point-of-interest data being dynamically variable based on the user's movement;- organize and provide to the user, through a digital display interface of a user's mobile device, such dynamically variable, generated and / or derived digital point-of-interest data associated with the user's digital point of view.; 2. A method according to claim 1, wherein said step of preparing or accessing a geolocalized digital map comprises preparing or accessing an immersive geolocalized digital map and / or a virtual geolocalized digital map corresponding to a “digital twin” of what is located in a geographic area represented by the “digital twin”.

3. A method according to claim 1 or claim 2, wherein said step of obtaining or determining geolocation data of a user comprises obtaining or determining geolocation data comprising a location of the user, a direction of movement of the user, and a speed of the user.

4. The method of claim 3, wherein said step of determining a digital viewpoint of the user comprises determining said digital viewpoint of the user in a dynamically variable manner, based on said user position, direction of movement and speed of the user.

5. A method according to any preceding claim, wherein said step of generating and / or deriving digital point of interest data comprises deriving the digital point of interest data from the geolocated digital map.

6. A method according to any preceding claim, wherein said step of generating and / or deriving digital point-of-interest data comprises generating digital data, by means of a trained artificial intelligence model.

7. A method according to any preceding claim, wherein said step of organizing and providing the user with digital point-of-interest data comprises generating and / or organizing and / or managing and / or distributing digital content optimized based on the user's movement / mobility, delivering the data based on the dynamically varying digital point of view corresponding to the user's actual point of view.

8. Method according to claim 7, wherein said step of generating and / or organizing and / or managing and / or distributing digital content optimized based on the user's movement / mobility is carried out by means of an algorithm for defining “moving content”, which establishes criteria for the production and distribution of content optimized for mobility and personalized to the user.

9. A method according to claim 7 or claim 8, comprising the further step of producing and disseminating digital content in relation to the position, direction, speed of the user.

10. A method according to any of claims 7-9, comprising the further step of producing and disseminating digital content based on interests indicated by the user, by means of a trained artificial intelligence model.

11. A method according to claim 9 or claim 10, wherein the organization of the content generated by the Artificial Intelligence is hierarchical, and / or wherein the organization of the content generated by the Artificial Intelligence takes into account a predefined scale of geographical importance and / or wherein the organization of the content generated by the Artificial Intelligence is multilingual and / or wherein the organization of the content generated by the Artificial Intelligence is such as to adapt to different narrative registers or presentation registers, dependent on the user.

12. A method according to any preceding claim, wherein said digital point-of-interest data comprises data descriptive of the present appearance of one or more points of interest, or of all points of interest visible from the user's point of view.

13. A method according to any of the preceding claims, wherein said digital data of points of interest comprise descriptive data of the past appearance of one or more points of interest, or of all points of interest visible from the user's point of view, at a given time, based on reconstructions of geolocalised computer graphics images referring to said time.

14. A method according to any preceding claim, wherein said digital point-of-interest data comprises data descriptive of the future appearance of one or more points of interest, or of all points of interest visible from the user's point of view, based on renderings or digital reconstructions associated with a project relating to an area surrounding the user's point of view.

15. A method according to any preceding claim, comprising a two-way interaction between a user's mobile device and said at least one geolocalized digital map, further comprising the steps of: - transmitting said information relating to the user's position, direction, and speed to electronic processing means implementing said at least one geolocalized digital map, by the user's mobile device; - obtaining in the at least one geolocalized digital map a visual recognition, for example by computer vision, of images and points of interest present in the user's digital viewpoint, by said electronic processing means; - obtaining from the at least one geolocalized digital map information relating to the elements recognized as present in the user's digital viewpoint;- create descriptive content based on the information obtained using electronic processing tools using artificial intelligence techniques; - transmit the created descriptive content to the user's mobile device in one or more multimedia formats: audio commentary, text file, images, videos, 3D formats; 16. A method for developing contextual multimedia guides, comprising: - performing a method for producing, organizing, and distributing georeferenced digital content on the move, according to any of the preceding claims, to obtain digital data of a plurality of points of interest, associated with a plurality of digital viewpoints of the user, dynamically variable as a function of the user's movement; generating said contextual multimedia guides using artificial intelligence, based on the user's position, direction, and speed parameters and the recognition of visual and informative elements present in immersive and / or virtual geolocalized digital maps.

17. A method according to any of the preceding claims, comprising the provision of content in simulations of courses with gymnastic equipment, wherein the provision of moving content is applied not with respect to the physical movement of people in reality but with respect to a simulation of movement carried out with gymnastic equipment.

18. A system for producing, organizing, and distributing georeferenced digital content on the move, comprising a user's mobile device equipped with geolocation sensors and electronic processing equipment, operationally connected to the user's mobile device, comprising: - at least one virtual reality and / or immersive map software application, associated with at least one geolocalized digital map, configured to provide a visual three-dimensional model, and / or including other multimedia digital content, of each of a plurality of points of interest present in a geographic area covered by the geolocalized digital map;- a software application or program capable of implementing an infomobility algorithm, configured to obtain and / or determine and / or interpret a user's geolocation data, including at least one user position and information relating to the user's movement, and to determine, based on said user geolocation data, a digital viewpoint of the user, within the geolocalized digital map, representative of a real viewpoint of the user in real space, dynamically variable depending on the user's movement, wherein said digital viewpoint is associated with at least one of said three-dimensional models present in the geolocalized digital map, corresponding to points of interest visible from the user's real viewpoint;- a trained artificial intelligence model, capable of generating digital point-of-interest data, comprising at least one three-dimensional visual model and / or other multimedia digital content relating to at least one of said points of interest associated with the user's digital point of view, said digital point-of-interest data being dynamically variable depending on the user's movement, said trained artificial intelligence model further capable of organizing and providing to the user, through a digital display interface of said user's mobile device, said dynamically variable digital point-of-interest data generated and / or derived, associated with the user's digital point of view.; 19. System according to claim 18, wherein said electronic processing means comprise, or consist of, a cloud software platform.

20. System according to one of claims 18 or 19, wherein said at least one virtual reality software application comprises an immersive geolocalized digital map and / or a virtual geolocalized digital map corresponding to a “digital twin” of what is located in a geographic area represented by the “digital twin”.

21. System according to claim 20, wherein said at least one virtual reality software application is configured to display current digital reproductions of the one or more points of interest or of the surrounding environment, in the present, and / or descriptive data of the past appearance of the one or more points of interest, in a given era, based on reconstructions of geolocalized computer graphics images referred to said era, and / or descriptive data of the future appearance of the one or more points of interest, based on renderings or digital reconstructions associated with a project referred to an area surrounding the user's point of view.

22. System according to any of claims 18-21 wherein the user's mobile device is further equipped with direction and / or speed and / or motion sensors.

23. A system according to any of claims 18-22, wherein the user's mobile device is further equipped with at least one camera for visual recognition, and is configured to transmit to said electronic processing means information relating to the user's position, direction, and speed; wherein the electronic processing means are further configured to: - perform visual recognition, using computer vision, of images and points of interest present in the user's digital viewpoint; - extract information from the geolocalized digital map relating to the elements recognized as present in the user's digital viewpoint; - create descriptive content, based on said information obtained, using artificial intelligence techniques; - transmit said created descriptive content to the user's mobile device.

24. A system according to any of claims 18-23, wherein the trained artificial intelligence model is capable of generating and disseminating digital content in real time, based on data input by the user or from relevant sources, based on interests indicated by the user, and / or with hierarchical organization, and / or taking into account a predefined scale of geographical importance, and / or through multilingual organization of the content and / or through different narrative registers or presentation registers, dependent on the user.

25. A system according to any of claims 18-24, configured to perform a method according to any of claims 1-17.