Method and system for explicit characterization of products by smart coatings

Abstract

The present invention relates to the explicit characterization of handicrafts (100), such as artworks, for example by applying a substrate or coating containing a number of microtransponders (110) dispersed therein. A detection system (130) reads (220) identifiers of transponders (110) detectable at that location and measures one or more of the following parameters for each transponder: RSSI, read speed, response time of each transponder, its location, distance and / or proximity to adjacent transponders. A pattern composed of the information or based on the information is stored (230) as a reference pattern or an identification pattern of the handicraft article (100). The identification scan (240) may be performed by acquiring the same parameter on a portion of the handicraft. A pattern of such parameters in a reference scan may be compared (250, 260) to the reference scan to determine whether it is an original handicraft (280) or a copy (270).

Description

Technical Field

[0001] The present invention relates to a method and system for unambiguous product characterization through smart coatings. Background Art

[0002] A class of irreversible mathematical functions that map digital data of arbitrary length into a string of defined length is known, called hash functions or hash functions. There are many algorithms that perform the function with specific properties that depend on the application. In cryptographic applications, hash functions must have the following properties: (a) Preimage resistance: it is computationally infeasible to find an input string that provides the same hash as a given hash; (b) Second preimage resistance: it is computationally infeasible to find an input string that provides the same hash as a given string; (c) Collision resistance: it should be computationally infeasible to find a pair of input strings that provide the same hash. A hash algorithm satisfies the following requirements: (a) The output consists of numbers and letters and is called a message digest (fingerprint of a message) generated based on a bit stream of any size; (b) The algorithm is irreversible, that is, the original data cannot be reconstructed from the output, that is, it is a one-way function. Therefore, there is no two-way correspondence between the hash and the starting data. Considering that there are more possible strings for finite-dimensional data than hashes, due to the "pigeon hole principle", each possible string corresponds to at least one hash. When two strings produce the same hash, we talk about a collision, and the quality of a hash function is measured by the difficulty of identifying two strings that produce a collision. A cryptographically secure hash should not allow finding a string that can produce it in a time comparable to the time it takes to use the hash itself. The length of a hash value varies depending on the algorithm used. The most commonly used value is 128 bits, which provides good reliability in a relatively small space, given the computing power of today's computers. For example, SHA (Secure Hash Algorithm) indicates the family of functions to which the different variants belong: SHA-1, SHA-224, SHA-256, SHA-384, and SHA-512. The last four variants are often indicated as SHA-2 to distinguish them from the first. The first method produces a message digest of only 160 bits, while the others produce a digest with a bit length equal to the number indicated in their abbreviation (i.e., SHA-256 produces a digest of 256 bits). Hash functions play a crucial role in cryptography: they can be used to verify the integrity of a specific string of data, since executing the algorithm on a string that has been modified even slightly provides a completely different digest message, revealing the attempted modification.

[0003] The shared and "immutable" data structure known as blockchain is known and is defined as a digital register in which items are grouped together in chronological order in the form of "blocks" connected together and whose integrity is ensured using cryptography. Its content, once written through a standardized process, can no longer be modified or deleted, otherwise the entire process would be invalid. Thus, with the help of blockchain, digital resources can be made explicit.

[0004] Blockchain is part of the larger family of distributed ledger technologies or DLTs, i.e. systems based on distributed ledgers that can be read and modified by individual nodes of the network. In order to verify modifications made to the ledger, the nodes must obtain consent without a central authority. The method of obtaining consent and the structure of the ledger are some of the features that characterize different DLTs.

[0005] Tokens on the blockchain consist of digital information items recorded on a distributed ledger, are unambiguously associated with only one specific user of the system, and represent any form of rights: ownership of an asset (e.g., access to a service, receiving a payment). Different types of tokens are known according to their legal status: (a) Utility tokens provide exclusive access to the characteristics of a digital service in a decentralized network (e.g., Ether and Stellar). (b) Security tokens represent ownership of an asset and give the owner rights similar to shares (e.g., voting rights, dividends, profit share). In terms of economic function, such tokens are security assets, stocks (equity), debts (bonds), and liabilities. They grant all or some of the declared rights. Security tokens derive their value from the underlying asset, but the key difference is that crypto tokens represent a programmable nature, providing assets with more features, more liquidity and easier market access, speed of creation, fewer intermediaries, lower issuance costs, transparency, and integrated automation of security-related processes. (c) Payment tokens: They are synonymous with cryptocurrencies and do not have any further functionality or connection with other developments (e.g., Bitcoin, Monero, Tether). These types of tokens are identified in a report on initial coin offerings and crypto assets drafted by the European Securities and Markets Authority (ESMA), as are guidelines issued by Switzerland’s federal financial market regulator FINMA, one of the first in the world to establish a relevant regulatory body.

[0006] Many crypto tokens in circulation are hybrids and can have different categories of properties, as they have utility properties and provide some property rights, particularly of an economic nature.

[0007] As we all know, smart contracts on blockchain platforms are called non-fungible tokens, or NFTs. A non-fungible token is a special type of cryptographic token that represents something unique. Unlike cryptocurrencies, NFTs are not interchangeable with each other: they can be exchanged for the same number of NFTs of the same type, precisely because they are unique, can be rare (scarce), and each has different characteristics and properties. In the real world, an example could be an object that cannot be replaced by another similar object, such as a work of art. If someone borrows the work, he / she must return the exact same work. One of the main differences between fungible tokens (e.g., cryptocurrencies) and non-fungible tokens is that the former can be divided into small parts, while the latter are absolutely indivisible.

[0008] NFTs are used to create verifiable digital scarcity, digital property and / or the possibility of interoperability of resources on various platforms. NFTs therefore represent the evolution of the physical properties of a certain asset. They are unique digital assets that allow their users to become their true owners. They can be exchanged on the right market, creating a tokenization process from real to digital.

[0009] NFT is therefore a digital content that represents real-world objects such as art, music, games and any type of collectibles. Anyone who buys an NFT is not buying the work itself, but the possibility of proving the rights to the work through a smart contract.

[0010] Everything starts with a digital version of the artwork. Usually, a digital photograph or a document of the shooting of a digital photograph is saved in a digital format (i.e., in the form of a long binary sequence), whose hash is calculated by the irreversible hashing process described previously. Usually, the next step is to create a file containing metadata, including the hash of the artwork and the associated timestamp, and save the metadata and the digital version of the work in a distributed file system (such as the Interplanetary File System or IPFS), a protocol and peer-to-peer network for decentralized data storage and sharing. NFT tracks the sale of the hash, making it possible to trace the change of hands of the hash to its creator and thus prove its ownership. Thus, this mechanism provides proof of the authenticity and ownership of the work. Based on the content of the NFT, the owner of the hash can prove his / her rights without contacting intermediaries and without time constraints. Therefore, NFTs in the field of art can become the best solution not only for the "notarization" of works, but also promote the automation of existing copyright management of works and their economic exploitation. On the other hand, in terms of authenticity, technologies that can be used to guarantee the identity of the subject claiming to be the author of the work have not yet been developed. However, in the case of "paper" authentication, the author's signature can be investigated handwriting, which cannot be done with smart contracts.

[0011] From an IT perspective, an NFT consists of three elements: (a) a token identifier or ID, a digital representation associated with the NFT and its owner that distinguishes it from other elements; (b) the token owner, i.e., the address associated with the owner’s wallet; and (c) metadata associated with the token, i.e., a JSON-type data structure containing a description, links to digital media (e.g., images in gif or jpeg format), and characteristics (e.g., traits, properties).

[0012] When an NFT is associated with a physical work of art (such as a painting), there is a uniqueness problem with the association between the work and the NFT itself. As described above, according to the prior art, an NFT hash can be generated from a digitized version of a work of art (e.g., a digitized image of a painting), however, the process has the problem of converting essentially analog data into its digital equivalent, where the characteristics of the work (e.g., color, shape) are approximate. It is well known that the process of digitizing an image varies due to the type of light used, the acquisition sensor, its sensitivity and resolution. In addition, over time, the work undergoes physical changes, such as color changes due to oxidation processes, or pigment degradation due to exposure to sunlight. When it is necessary to prove that the physical work actually corresponds to a certain NFT, the work needs to be newly digitized, from which a hash value that must be the same as the hash value stored in the NFT is derived. Since, as described in the prior art, the hash process produces completely different hash strings even in the case of minimal differences in the starting data, it is easy to understand how this process cannot be effectively used to clearly guarantee the identity of the work over time.

[0013] RFID (Radio Frequency Identification) systems are known for identifying objects using tags. In an RFID system, a reader sends an interrogation signal to a nearby tag, which in turn responds via backscatter. The reader analyzes the response and reports the tag data as well as the received signal strength indicator (RSSI) of the signal. RSSI is a measure of the power received from the signal returned by the RFID tag when interrogated by the reader.

[0014] When a reader reports a tag's RSSI value, it is actually reporting the tag's backscattered response signal power level as it relates to the reader's initial broadcast signal power level. This power level is typically reported in decibels per milliwatt, or dBm. A decibel is a unit of measurement that relates two physical properties on a logarithmic scale. In the case of RFID, the property being measured is a change in power, measured with reference to a single milliwatt. To provide an idea of ​​the extent to which this power level varies, a typical fixed RFID reader is capable of outputting a 1-watt, or 30-dBm, signal, while a typical tag's RSSI value can vary from -30 to -85 dBm. This effectively means that only a fraction (about one millionth) of the original power is returned to the reader.

[0015] Other measurable parameters when reading transponders are the reading speed and the response time, i.e. the number of times per second the tag is read and the time it takes for the tag to respond for the first time.

[0016] Many uses of RFID systems are known. The most common is to perform unambiguous product characterization by reading information from a unique RFID tag applied to a product by various methods. Even if the application method has tamper-proof aspects, tampering is still possible, and characterization is insufficient to prove unique, rare, high-value or complex products, such as works of art.

[0017] Patent document US2016009930A1 describes an ink in which RFIDs smaller than 0.75 mm are dispersed, which uniquely characterizes a color or product by using the ink in combination with a resin. Characterization is performed using information contained in the memory of each RFID (e.g., the same information contained in the product barcode, and in any case, the same information in each label). This allows multiple products to be read simultaneously, which is not possible with a barcode. The solution has the same characterization reliability as a single label.

[0018] Patent document US20180087369 A1 describes the use of RFID to verify the effective degradation of degradable or soluble tools, such as those used in underground operations such as temporary isolation areas or diversions. The purpose is to ensure that the instrument is fully degraded and no longer blocks or impedes groundwater flow. The micro RFID is dispersed in or above the instrument, and therefore its degradation will cause the signal to decrease over time until it is essentially zero.

[0019] This solution does not allow characterization of the product, only verification of its effective solubility.

[0020] Document US2006 / 180647A1 describes a method for identifying objects using RFID. Information about the product or the person to be identified can be stored in the RFID. No information about the RFID itself is stored or utilized. This does not make identification secure, for example in the art field where the authenticity of the work needs to be guaranteed, because the RFID is still susceptible to tampering.

[0021] Document CN103065109 instead deals with the protection of works of art, specifically paintings, but uses calligraphy and microtexture detection of the painting surface, which generates information to be stored in the RFID. Subsequent scans of the surface microtexture are then compared with the stored scans to prove the originality of the work. The core of the invention therefore lies in the optical detection of the microtexture of the painting, which requires important and expensive optical equipment and digital algorithms, and does not guarantee the robustness of the method, for example in the case of degradation of the microtexture of the painting over time.

[0022] There remains a need for unique product characterization by means of RFID systems or generally transponders which are counterfeit-resistant and which can therefore be used for purposes such as generating NFTs, or in any case for identifying and / or tracking high-value objects. Summary of the invention

[0023] The object of the present invention is to provide a method and system for unambiguous characterization and author identification of products, which fully or partially solve the problems of the prior art and overcome its disadvantages.

[0024] Specifically, the invention aims to associate a native digital uniqueness with a physical work, which is physically immutable over time, clearly linked to the identity of the author (understood as the artist or AI or producer of the artifact, and therefore a natural person and / or legal person and / or digital agent), easily detectable, and inseparable from the work itself. This unit character should be defined as the digital fingerprint of the work. Specifically, this digital fingerprint is such that it can be detected by a radio frequency signal without physical contact with the work. The long string of numbers that constitutes the digital fingerprint (for example, a sequence of the ID of a transponder) can then be processed to obtain a unique hash used within the NFT associated with the work itself.

[0025] A method and a system according to the appended claims are subject matter of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The invention will now be described by way of non-limiting illustration and in particular with reference to the accompanying drawings, in which:

[0027] - Figure 1 shows a process of applying smart paint to a work of art according to the present invention;

[0028] - Figure 2 The process of detecting RSSI parameters as a function of relative orientation between a detection antenna having different tilt angles and an RFID according to aspects of the present invention is shown;

[0029] - Figure 3 A high-level flow chart illustrating a clear identification process according to an embodiment of the present invention is shown;

[0030] - Figure 4 A schematic diagram showing a first method of locating the position of a transponder according to an embodiment of the present invention;

[0031] - Figure 5 A schematic diagram showing a second method of locating the position of a transponder according to an embodiment of the present invention; and

[0032] - Figure 6 Shows Figure 5A summary of the methods in

[0033] - Figure 7 A product scanning system according to aspects of the present invention is shown;

[0034] - Figure 8 A flowchart showing a scanning process according to an embodiment of the present invention; and

[0035] - Fig. 9 A flow chart for determining the actual position of a tag after scanning is shown according to an embodiment of the present invention.

[0036] It is specified herein that by respecting the technical concept of the present invention, elements of different embodiments may be combined together to provide further embodiments without limitation, as a person of ordinary skill in the art will readily understand from the description.

[0037] Furthermore, the present description also refers to the prior art to implement detailed features not described therein, such as minor elements that are commonly used in solutions of the same type in the prior art.

[0038] When an element is introduced, it is always understood that there may be "at least one" or "one or more".

[0039] When a list of elements or features is given in the present specification, it should be understood that the inventive concept "comprises" or, alternatively, "consists of" such elements.

[0040] When features are listed in the same sentence or bullet list, one or more individual features may be included in the present invention without being linked to other features in the list.

[0041] According to the present invention, two or more components (elements, devices, systems) described above may be freely associated and considered as a kit of parts. DETAILED DESCRIPTION

[0042] According to one aspect of the present invention, and with reference to Figure 1 By applying a substrate (such as an epoxy resin in which the transponders 110 are dispersed) containing a certain number of transponders 110 (e.g., micro RFIDs in the UHF band), the handicraft 100 (e.g., artwork) can be clearly identified. Once the resin is cured, the micro transponders are randomly dispersed and maintained in position inside the substrate ( Figure 3 210 in the flowchart in FIG.

[0043] The substrate may be obtained by applying a paint (or other spreadable material) containing a dispersion of the transponders. Alternatively, the transponders may be dispersed in a liquid material which is held in a fixed position by solidification, for example the molten plastic material which solidifies in a mould to form the product (the fixed position does not change unless the product geometry changes, for example if it is elastic, the mutual position may vary and then return to the initial position; in any case the mutual position (proximity) remains constant and we will therefore talk about a "stable" application of the dispersion). The transponders may also be applied randomly to the fabric during the production process. More generally, the substrate may consist of any product in which a dispersion of micro transponders is incorporated, regardless of the production process in which it is obtained.

[0044] In general, a dispersion of transponders can be obtained by randomly mixing a plurality of transponders 110 with a binding substance, which consists, for example, of an aqueous emulsion (tempera paint), a drying oil, a vegetable base or a synthetic resin, including acrylics, epoxies, phenolics, polyesters, vinyl esters, thermoplastics, thermosetting resins, elastomers or colloids, so that after a drying step, the position of the transponders is stable over time.

[0045] The dispersion may even be a simple powder without any binding substance, which is used only during application to the product.

[0046] In any case, the dispersion can first be applied to the label and then applied to the product. Everything described herein is also valid in the case of labels.

[0047] The product 100 may consist of a support on which the artwork is created. The support may be provided with a natural or synthetic substrate on which the author can create his / her artwork, including paper, canvas, fabric, ceramic, wood, glass, metal, stone, masonry, plastic. The transponder 110 may be applied during the step of creating the support or later during the creation of the artwork.

[0048] exist Figure 1 In the right-hand enlargement of , the distribution of the transponders 110 relative to the drawing lines of the artwork can be observed. The application of the dispersion of microtransponders is not necessarily applied to the entire surface of the artwork, but only to a part of it, for example, to the side opposite its pigment, or to an inner layer of a artwork (not necessarily a painting). In this context, the term "surface" shall hereinafter be used in a broader sense, i.e. an inner or outer surface connected or not connected to the rest of the handicraft.

[0049] The detection system of the dispersion of micro transponders 110 consists of at least one antenna (RFID) 130 and a data processing unit (not shown), which in turn can be connected to a server for storing or processing the detected information.

[0050] According to an aspect of the invention, the detection system may include one or more RF amplification systems and / or RF resonators, one or more television cameras, and one or more detection systems (not shown) of the antenna position.

[0051] The detection system (and therefore the antenna 130) is moved towards the artwork 100 at any position, for example, placed on its surface ( Figure 3 120 in the flowchart of FIG. 1 ). A plurality of miniature RFID transponders present in the substrate of the work (a subset of the transponders present) fall within the reading range of the identification system, for example around the face line 120. The transponders are preferably equipped with an anti-collision protocol so that all visible transponders (i.e., transponders visible to the antenna according to the power of the backscattered signal) can be read by the same antenna.

[0052] The detection system reads one or more of the following characterizing information items for each transponder: EPC (Electronic Product Code), TID (Tag Identification) memory, user memory, received signal strength indication (RSSI), reading speed, response time, location, distance to neighboring transponders. Proximity is used to indicate the mutual or topological location of the transponders, as shown below.

[0053] The preferred minimum set of information is the tag ID and its location. Optionally, it is advantageous to include RSSI and the RGB color of the object that may be detected in the scan point or area. Other parameters are useful and advantageous, but to a lesser extent. For example, when there is not enough user memory, the EPC memory is used to write information in the tag. The distance to the adjacent transponder can be calculated based on the location. The response speed and / or the read time can be used to verify the correct reading of the RFID.

[0054] Reading can be achieved for the entire surface on which the dispersion of transponders is located or for a portion thereof, whether it is completely connected or consists of (also) remote parts.

[0055] Such information is processed in a local data processing unit (not shown) or sent to a server (not shown). A pattern composed of or based on this information is stored as a reference pattern or a characterizing pattern or an identification pattern ( Figure 3 230 in the flowchart in FIG. 1 ). This pattern clearly characterizes how the antennas detect the transponder according to their relative positions. Figure 2As shown, such a mutual position may vary depending on the mutual inclination between the antenna 130 and the transponder 110. In fact, the signal component 112 in the direction of the antenna 130 will therefore be maximum when the two antennas (reader and transponder) are parallel, and will be minimum in the case of perpendicular antennas, when component 113 appears. The component 111 perpendicular to the antenna will be reduced with respect to the mutual indication of the antennas.

[0056] The transponders 110 are stuck in positions that are fixed and unchangeable (or "stable") over time within the artefact 100 (see above), which means that their mutual positions cannot change over time. Therefore, antennas placed at different times at the same point (and with the same inclination and distance from the artefact) will detect the same set of transponders with essentially the same detection information. Therefore, this can be regarded as a real unambiguous digital fingerprint (hereinafter also referred to as "unambiguous identification pattern" or "characterizing pattern") of the artefact.

[0057] According to a preferred embodiment of the invention, for each transponder at least data contained in one or more of the following transponder memory areas are recorded: EPC (Electronic Product Code) memory, TID (Tag Identification) memory, user memory for better characterization of the product.

[0058] This result can be achieved with a system that positions the antennas at the same location, or by performing a reference scan to acquire various patterns, since the tilt and / or distance of the antennas is different at each detection position, the characterizing pattern being a combination of the information acquired for each predetermined scan position and each tilt.

[0059] However, acquisition with different inclinations or with fixed inclination is not an essential feature of the invention, since pattern recognition can be performed within a certain error tolerance and the proximity of the transponder can also be detected, which is essentially independent of the inclination, as shown below.

[0060] In general, the ID can be detected and a hash of the transponder's ID pattern can be calculated and then stored in the blockchain. The RFID information pattern obtained in the characterization step can be encrypted, for example using the hash as an encryption key and stored, making the system more robust to fraud attempts.

[0061] The information detected by the RFID fingerprint can also be associated with the data detected at each predetermined scanning position (or by acquiring an overall image and extracting the corresponding parts) using a camera on the surface of the handicraft, which can be part of the reading system. This provides an RFID / RGB fingerprint (RFID, and possibly RGB). The information detected by the RFID fingerprint can also be associated with the data detected by a 3D sensor (RGBD image, color+depth) or a sensor sensitive to other parts of the electromagnetic spectrum (e.g., a thermal imaging camera).

[0062] The RFID / RGB fingerprint shall constitute the electronic or unambiguous DNA or unambiguous digital fingerprint of the artifact 100. The electronic DNA may be encoded in an RFID or matrix code, which will constitute a certificate of authenticity for the work. It may also be recorded in a blockchain such as an NFT, so that the electronic identity cannot be forged. Specifically, the hash code of the RFID / RGB fingerprint may be stored in the blockchain.

[0063] According to an aspect of the present invention, the explicit digital fingerprint information may be stored in a memory unit (not shown).

[0064] According to an aspect of the invention, the digital fingerprint information may be compressed, encrypted and stored in a user memory of each of the transponders 110. Optionally, a digitized biometric sample proving the identity of the author of the product 100 may be stored in the memory unit and / or the blockchain and / or the user memory of the transponder. This digitized biometric sample proving the identity of the author of the product 100 may conveniently consist of at least a portion of the digitized genetic code of the author of the product, a compressed and encrypted version thereof or a hash code of at least a portion of the genetic code.

[0065] refer to Figure 3 Once the unambiguous reference pattern is obtained in 230, the originality of the artefact 100 can be verified by first performing an identification scan 240. In this identification scan, the reading system can cover the entire work or only a portion of it. In this case, it is positioned at one or more positions relative to the artefact 100. No reading is required at each position where a reference scan is performed, so checking originality will be simpler and faster than with a characterization scan.

[0066] The measurement of the same parameters / information as the reference scan (possibly even for different inclinations and / or distances) will provide a shorter identification pattern that will correspond to a portion of the electronic DNA of the work. By repeating the measurement several times at different predetermined scanning positions, several fragments of the electronic DNA can be compared, further increasing the probability of a correct identification.

[0067] The comparison in block 250 may be performed using a suitable pattern search algorithm in 260, or may be performed with reference to a predetermined deviation tolerance defined in many known ways. When the reference scan has been performed for various tilts of the antenna 130, all tilts of the reference scan will be compared. In the case of identifying the pattern of the identification scan within the unambiguous pattern of the reference scan (even within a predetermined error), there will be a unique identification of the artefact 100 in 280, otherwise it will be determined in block 270 that it is a copy (corresponding digital information is generated).

[0068] According to an aspect of the invention, at least a portion of the characterizing information obtained in a first scanning step is read from a user memory of the transponder 110 and compared with at least a portion of the authentication information obtained in a subsequent scan performed for authentication purposes.

[0069] Figure 4 A method for positioning a position according to one aspect of the present invention is shown. Let us consider a detection system consisting of multiple antennas AN1, AN2, AN3 (as an example, there can be more antennas), whose mutual positions are precisely known. When the system moves towards a substrate that integrates multiple transponders in random positions (such as drawn and shown by ID1), by detecting the ID, RSSI, reading speed and number of readings of each tag of all antennas, its position can be calculated using prior art techniques, such as micro-areas, triangulation, trilateral measurement (using RSSI). Specifically, in the trilateral measurement for each reading point, the measurement or approximation of the corresponding distance creates a circular area of ​​possible positions for the tag. The basic method of trilateral measurement is to calculate the intersection of the circle to estimate the position of the tag. Once the position of a subset of tags relative to each antenna of the reading system is known, the processing unit is able to calculate the mutual position of each of the tags relative to other tags according to known Euclidean geometry techniques. This process is called "scene analysis" and is used to locate tags relative to a set of known antennas.

[0070] In characterizing and identifying patterns, the mutual position can be understood alone or in combination, with the advantage that the method is more robust to replicas. In fact, the ID can be obtained from a scan similar to the characterization step alone. The mutual position has the advantage of being applicable to surfaces whose geometry can vary, such as elastic surfaces. Figure 5 , let us now consider a simplification of the previous reading system, where there is a pair of antennas ANT1-ANT2 at a fixed distance d, used to detect tags ID1 and ID2, and their mutual distance is then determined in the approximation of the area of ​​each antenna, and the same pair of antennas can be rotated to detect tags ID3, ID4 on one side and ID5 on the other side in the same way. Thus, small antennas can be used to characterize the mutual position of tags. This concept is in Figure 6In (a), detection is performed with dual antenna positioning and still only two neighboring tags of the tag are detected, while (b) three neighboring tags are detected. This can be verified by randomly moving antenna pairs by mapping the mutual distances in the characterization phase.

[0071] Both the scene analysis process by trilateration and the localization process by proximity can detect mutual distances between at least a subset of the transponders present in the substrate. The mutual distances are invariant with respect to the position and tilt of the reading system, since they represent an immutable physical property of the substrate. The mutual distances can be included in the characterization and recognition pattern, with the advantage of greater robustness of the method.

[0072] In the detection step of the reference scan, physical properties of the RFID substrate or a portion thereof are measured. In the verification step (identification scan), any subset of the substrate is scanned and physical properties are derived therefrom and then compared with reference properties of the same subset of transponders.

[0073] Taking into account the random distribution of transponders on the substrate of the work, it is necessary to consider the case where a group of transponders are particularly close or partially overlapping. Nearby transponders form a cluster, which can fall completely or partially within the reading field of the antenna. The cluster can be assimilated by approximation to a single identification element, so that it is easier to identify and locate by the antenna. In this case, the same position has different IDs, it is possible to establish a selection criterion in the product characterization step and a "tolerance" criterion between the detected pattern and the (part of) pattern detected in the characterization step. This distance criterion can be established by mathematical methods or by calibrating the system according to the invention.

[0074] According to a further embodiment of the invention, the RFID 110 is equipped with a writable user memory, preferably of the write-once-ready-multiple type, and wherein, after the characterization step and before the identification step, the characterization pattern or a subset thereof obtained based on the local parameters of the RFID is stored in the user memory of the transponder, and wherein:

[0075] - in the identification step, reading the pattern stored in the RFID; and

[0076] - In the comparison step, a pattern stored in the characterizing pattern is searched.

[0077] The system for clarifying product characterization according to the present invention may include:

[0078] - a liquid dispersion of a transponder, such as a micro RFID UHF 110, suitable for application to the surface of the product 100;

[0079] - at least one RFID antenna 130;

[0080] - At least one processing unit;

[0081] Wherein, the processing unit is configured to receive and store the characterization pattern of the product 100 as defined above, and receive and verify the presence of the identification pattern having the same type of information within the explicit reference pattern.

[0082] According to one aspect of the present invention, there is provided a camera configured to obtain an image of a surface at a set of scanning positions on the surface of a product.

[0083] According to different aspects of the present invention, the processing unit is configured to store the hash of the characterization pattern as an NFT in a blockchain.

[0084] According to different aspects of the present invention, there is one or more systems for detecting the position of the antenna 130.

[0085] Unique scanning and identification methods

[0086] Reference Figure 7 , the scanning system in which the antenna 3 is moved in the X-Y direction by the corresponding guides 4 and 5 is designed to map the positions of all RFID 2 tags scattered within the object 1 (e.g., a painting), and at the same time map the color and three-dimensional surface information of the object. Considering that the reading area of the RFID antenna is larger than the forward steps in x and y, each tag will be ready around its actual position at each successive step in both x and y. At the end of the entire scanning process, a specific algorithm allows obtaining the actual positions of all tags and averaging the detected positions (x, y, z) of each tag.

[0087] For each detected tag, store the ID, actual position (xyz, position average), RSSI (average of all measurements), and the RGB image detected around the actual position of the tag. Assume that a total of N tags are detected. An algorithm considers all possible ways of dividing the set of N tags into subgroups consisting of M elements (where, obviously, M < N), calculates the average of the distances of the M tags present in each subgroup, sorts the groups by reducing the average distance, selects the subgroup with the largest average distance, and ensures that each of the N tags appears in the M subgroups.

[0088] Finally, the scanning system repeats the scanning process again to store the codes of M - 1 tags belonging to its group in encrypted form.

[0089] The flow of the scanning process 300 using such a device is as Figure 8 shown, where a single flow chart is subdivided into successive parts (a) to (d).

[0090] At start 310, position X (and / or Y) is incremented by one step in 311. In 312, position Z of the readhead is also (optionally) adjusted to maintain a fixed distance from the surface, thereby making the reading more reliable.

[0091] A scan of each RFID is then performed in 313. At this point, if an RFID is present (314), the ID, location, and optionally RSSI are recorded in 315. Conversely, if no RFID is present, the process moves through box 316 to box 317 (which arrives at 315 in any case) for reading the color of the scanned object (e.g., a painting) optionally using an RGB sensor.

[0092] Position control is then performed. Specifically, it is verified in 321 whether X has reached the edge of the object. If this is not true, the process moves to the increment of Y in box 341, otherwise X is incremented by one step in 322, and then in 323 part Z can be optionally adjusted again, as described above. At this point, each RFID is scanned in 324. If present in box 325, the ID, position and optionally RSSI are recorded in 326, if not present in the connection box 327, box 326 is also released. In box 328, the color is read directly, optionally using the RGB sensor, as described above.

[0093] Thus, block 341 is reached where Y is incremented by one step and X is decremented by one step in 342, position Z is adjusted as described above in 343, and a scan of each RFID is performed as described above in 344. If an RFID is present in 345, the ID and position and optionally RSSI are recorded in 346, otherwise the process moves to connect block 347, and then to 348 for optional detection and storage of color as described above.

[0094] At this point, in 361, it is verified whether X has reached the opposite edge of the object, in which case X is decremented by one step in 362, Z is adjusted as described above in 363, and each RFID is scanned in 364. If an RFID is present (block 365), the ID and location are read, and RSSI is optionally read in block 366 and then in connection with block 367, even if X has not reached the opposite edge, and the color can optionally be detected in 368.

[0095] Next, in 371, Y is incremented by one step and in 372 it is verified whether Y has reached the bottom edge. If this is true, the process ends at 390. If Y has not reached the bottom edge, then in 373, X is incremented by one step, in 374, position Z is optionally adjusted, and in 375, each RFID is scanned. In the subsequent box 376, it is verified whether the RFID is present. If this is true, the ID and position and optionally RSSI are recorded (in box 377), and then moved to the connection box 378 to which the process is directed, even if there is no RFID present. At this point, the process moves to 379, where the color is optionally detected as described above, and it starts again from box 372 until Y reaches the bottom edge.

[0096] This process is effective for every 1D, 2D or 3D object by properly adjusting the axes and scanning steps.

[0097] The proposed scanning system is designed to detect and precisely map the location of RFID tags embedded in 3D objects. Such objects can be paintings or blocks of composite materials, for example. In addition to the localization of RFID tags, the system also records color information and maps the 3D surface of the object.

[0098] The scanning system is based on a series of cyclic steps: increasing / decreasing position along the X-axis, adjusting position along the Z-axis to maintain a constant distance from the object surface, detecting the presence of an RFID tag, and reading the color using an RGB sensor.

[0099] The scanning system moves along the X axis, scanning the surface of the object. When it comes into contact with the edge of the object, it increments its position along the Y axis and advances in the opposite direction along the X axis. This process continues until the lower edge of the object is reached along the Y axis.

[0100] During each step, the position along the Z axis is adjusted to maintain a constant distance from the object surface. This ensures that the RFID and RGB readings are constant and reliable despite possible irregularities in the object surface.

[0101] Each RFID tag detected records its position (X, Y, Z), ID, and RSSI (Received Signal Strength Indicator) value, which indicates the power of the signal received from the tag. Since the read area of ​​the RFID antenna is larger than the progressive steps in X and Y, each tag will be detected in each successive step of both X and Y around its actual position.

[0102] refer to Fig. 9, in order to determine the actual position of each tag, all the positions detected for each tag are advantageously stored in a dictionary, with the tag's ID as key. At the end of the scan, the algorithm can calculate the average of the detected positions for each ID, thus obtaining the actual position of the corresponding tag. This process reduces the error caused by the overlap of the RFID antenna reading area relative to the forward step.

[0103] In addition to location, the algorithm can also calculate the average of the RSSI and RGB images detected around the actual location of the tag. This data can be used for later analysis, such as identifying patterns in RFID data or analyzing the color of an object.

[0104] In the specific flowchart 400, the process starts in 401 and an empty dictionary for tags is created in 410. Then, scanning is performed as described above. If in 420, an RFID tag in the scan is detected, the ID and position and optionally RSSI and / or RGB are extracted in 430. If in 440 the identifier ID is already in the dictionary, the parameters as described above are updated in the dictionary in 450, while in the opposite case it is added to the dictionary in 460, and in any case the process moves to the connection block 470, from which another tag is scanned again in 420. On the contrary, if no more tags are scanned in 420, the actual position, RSSI and RGB calculations are performed for each scanned tag in 480 (using the reader as described above).

[0105] The actual position / RSSI / RGB is calculated as an average (any kind of average) for each tag.

[0106] In practice, the position and other data of each tag are updated with each scan and averaged to determine them, thereby calculating the distance between tags. To calculate these mutual distances, all groups of at least 2 tags are analyzed and the average distance between tags in each group is calculated based on the average position that has been calculated (as described above or using an equivalent algorithm).

[0107] In practice, the algorithm considers all possible ways to partition the set of detected labels into subgroups consisting of M elements (M greater than or equal to 2). For each possible subgroup, it calculates the average of the distances between the labels in the group. Then, it sorts the groups by decreasing average of the distances.

[0108] At this point, the algorithm selects (and stores in a specific dictionary) the subgroups with the largest distance average, ensuring that each detected label appears in at least M subgroups. This step is useful for identifying groups of labels that are relatively close to each other.

[0109] Finally, the scanning system repeats the scanning process, but with one addition: during each step, it stores the IDs of the M-1 other tags in its group in an encrypted manner. This is used to create a map of tag groups directly on the tags themselves, making it possible to identify groups even without a grouping algorithm.

[0110] The above solution provides an advanced object identification and anti-counterfeiting protection method based on the application of a random distribution of RFID tags inside the object. The technical effect of this solution is to increase the redundancy and security of the identification system, thereby overcoming the single point of failure (SPOF) problem. In fact, in identification systems according to the prior art, the presence of a single tag represents a potential SPOF. If a tag is damaged, removed or compromised in some way, the entire identification system may fail and all relevant information is lost. However, by applying a random distribution of redundant RFID tags according to the proposed method, the probability of such failure is greatly reduced.

[0111] Another technical effect of this solution is the increased anti-counterfeiting security relative to the prior art. The complexity caused by the random distribution of RFID tags within the object makes it extremely difficult to copy or forge the object. A potential forger should be able to copy not only the object itself, but also each tag and place all tags in a manner that is randomly distributed within the original object. The complexity and accuracy involved in this is beyond the capabilities of many forgery methods.

[0112] Furthermore, the proposed system uses a specific algorithm to map the location of each tag and group the tags based on their topology. This allows creating a unique "digital fingerprint" for each object, based not only on the ID of a single tag, but also on their distribution within the object, and possibly taking into account other information, such as RSSI and color data. This digital fingerprint is further protected by cryptography, making forgery more difficult.

[0113] Finally, the scanning system stores the encrypted IDs of the other tags in the group on each tag, creating a map of the tag group directly on the tag itself. This feature adds a higher level of security and redundancy because groups of tags can be identified even in the absence of a grouping algorithm.

[0114] In summary, the technical effect of this solution is to significantly increase the redundancy and security of the object identification system, overcome the SPOF problem, and provide strong anti-counterfeiting protection.

[0115] It is provided here that the dispersion or powder of the RFID tag does not necessarily have to be used as a coating, but can be applied to the tag in various ways, which is then applied to the object together with the tamper-proof application.

[0116] Advantages of the present invention

[0117] Among the advantages of the method and system according to the invention, the following advantages may be listed, which may be considered individually or in combination:

[0118] - clear identification of the artefact;

[0119] - The unique pattern of the handicraft is not repeatable;

[0120] - immutability over time;

[0121] - It is impossible to separate the RFID clear pattern from the handicraft;

[0122] - a clear and secure connection between the author and the work;

[0123] - Marking speed;

[0124] - Inviolability of the fingerprint (e.g. when included in a blockchain);

[0125] - Low implementation cost; and

[0126] - Non-intrusive nature of handicrafts.

[0127] In the above disclosure, preferred embodiments are described and some variations of the present invention are proposed, but it should be understood that modifications and changes may be made by those skilled in the art without departing from the relevant protection scope as defined in the appended claims.

Claims

1. A method for verifying the originality of a product and optionally the identity of the author of said product, comprising the following steps: A. applying (210) a dispersion of a transponder (110) to at least one surface of a product (100), or applying a label to said surface to which the dispersion of said transponder (110) was previously applied; B. characterizing (220) the surface or the tag of the product by moving at least one antenna (130) towards at least a portion of the surface or the tag of the product to scan at least a subset of the transponders (110) to detect a set of transponder characteristics, the set of transponder characteristics comprising, for each transponder (110), at least an ID and a position relative to a predefined reference system; C. storing (230) the characterization information obtained in step B as a product characterization pattern in a memory unit; D. acquiring (240) the information of step B by scanning at least one area of ​​the surface of the product or at least one portion of the label, thereby obtaining a pattern of authentication information, wherein at least a portion of the dispersion of the transponder (110) applied in step A is present, moving the at least one antenna (130) toward the surface of the product (100); E. storing (250) the verification information related to the product obtained in step D in a verification pattern of product authenticity; F. searching (260) the verification pattern in the characterization pattern within a predefined deviation tolerance; as well as G. Depending on the positive or negative result of step F, digital information is generated (280) regarding the identity and authenticity of said product (100) and optionally regarding said identity of the author of the product.

2. The method according to claim 1, wherein: The set of transponder characteristics includes a received signal strength indication RSSI.

3. The method according to claim 1 or 2, wherein: The set of transponder characteristics includes one or more of the following: EPC electronic product code memory, TID tag identification memory, user memory, reading speed, response time.

4. The method according to one or more of claims 1 to 3, wherein: In step C and step E, the product characterization pattern and the authenticity pattern, for each transponder, include an indication of the distance between each transponder (110) and other transponders, and perform the following steps: - dividing the set of transponders into all subgroups consisting of M elements, where M is greater than or equal to 2 and less than the total number of transponders on the product or label; - for each subgroup, calculating the average value of the distances between the transponders in the group; - selecting the subgroups with the highest average distance above a predefined threshold, ensuring that each of the detected transponders is present in at least M subgroups; - the average of the distances stored in said characterizing pattern in step C and in said authenticity verification pattern in step E for each of said subgroups selected in the previous step.

5. The method according to claim 1, wherein: The position is calculated as the average of the positions detected in each antenna position for each ID.

6. The method according to claim 1, wherein: In step A, the product (100) consists of a support on which the artwork is produced.

7. The method according to claim 1, wherein: In step A, a dispersion of a plurality of transponders (110) is obtained by randomly mixing said transponders with a binding substance, such that after a drying step, said positions of said transponders are stable over time.

8. The method according to claim 1, wherein: In steps B and D, RGBD information of the color and depth of the product (100) is added to the characterization information and verification information, the RGBD information being acquired when the camera scans each scanning position of the product.

9. The method according to claim 1, wherein: In step C, at least a portion of the representation information obtained in step B is hashed and then stored in a blockchain as a non-fungible token NFT so that the metadata of the NFT contains a hash and a reference to the storage location of the representation information, preferably on a distributed file system DFS, such as the InterPlanetary File System IPFS.

10. The method according to claim 1, wherein: In step C, at least a portion of the characterization information acquired in step B is compressed, encrypted and stored in a user memory of each of the transponders (110).

11. The method according to claim 1, wherein: In step C, a digitized biometric sample proving the identity of the author of the product (100) is stored, optionally in a blockchain according to claim 9 and / or in a user memory according to claim 10.

12. The method according to claim 11, wherein: The digitized biometric sample proving the identity of the author of the product (100) comprises one of: at least a portion of a digitized genetic code of the author of the product, a compressed and encrypted version, a hash code of the at least a portion of the genetic code.

13. The method according to one of claims 1 to 12, wherein: In steps B and D, multiple antennas (AN1, AN2, AN3; ANT1, ANT2) are used, with mutual positions known in both steps, and wherein the mutual positions of the transponders (110) are obtained by proximity to the antennas or by RSSI-based trilateration, said mutual positions being included in the characterization and identification information.

14. The method according to one of claims 1 to 13, wherein: In step G, at least part of the characterization information obtained in step B is read from a user memory of the transponder (110) according to claim 10 and compared with at least part of the authentication information obtained in step D.

15. A system for specifying product characterization, comprising: - a dispersion of transponders (110) applied to the surface of a product (100) or a label applied to said product; - at least one RFID antenna (130); - at least one processing unit; It is characterized in that the processing unit is configured to receive and store the characterization information of the product (100) obtained in step B according to one or more of claims 1 to 14, and to receive and verify the existence of verification information obtained in step D having the same type of information within the characterization information.

16. The system of claim 15, wherein: A camera is included, the camera being configured to obtain images of the product at a set of scanning locations on the surface of the product (100).

17. The system according to claim 15 or 16, wherein: The processing unit is configured to calculate and store a hash of the representation information and mint an NFT in a blockchain so that the NFT contains the hash and a reference to the storage location of the representation information within the metadata of the NFT, preferably on a distributed file system DFS, such as an InterPlanetary File System IPFS.

18. System according to one or more of claims 15 to 17, wherein: One or more systems are provided for detecting the position of the antenna (130).

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