CN113825139A - Internet of things equipment position fingerprint positioning method and system based on block chain - Google Patents
Internet of things equipment position fingerprint positioning method and system based on block chain Download PDFInfo
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Abstract
The application discloses a method and a system for positioning the position fingerprint of an Internet of things device based on a block chain, wherein the method comprises the steps of establishing a position fingerprint database on the chain based on the block chain; uploading corresponding electromagnetic fingerprints by the Internet of things equipment with the positioned actual position in the area, recording the electromagnetic fingerprints in a position fingerprint database, training a positioning model by a solving node under an intelligent contract distribution chain, and generating an electromagnetic fingerprint positioning algorithm model after the solving node reads the position fingerprint database; and receiving positioning requests of other nodes, generating a positioning result on the chain by using the electromagnetic fingerprint positioning algorithm model according to the positioning requests, and returning the positioning result to the other nodes sending the positioning requests. The method solves the problems that the Internet of things equipment lacks positioning capability and positioning is falsified and forged, and can be used for improving the positioning safety of the Internet of things equipment and providing positioning service for part of Internet of things equipment without positioning capability.
Description
Technical Field
The application relates to the technical field of information security, in particular to a method and a system for positioning a position fingerprint of an internet of things device based on a block chain.
Background
The internet of things is a network of sensor and actuator nodes called "things". "thing" refers to a device or sensor that senses and records a physical world signal in digital form. Location Based Services (LBS) are used in various fields including military, electronic medical care, environmental monitoring, weather forecasting, early warning and rescue, etc., and location information plays an important role in various wireless sensor network applications. A Global Positioning System (GPS) and a beidou positioning system can be used as solutions for LBS, but not all internet of things devices have GPS or beidou positioning capabilities, and a single GPS positioning is vulnerable to forgery and tampering, so that a single positioning technology is not suitable for all applications. As the assistance of big dipper and GPS location, electromagnetic fingerprint location technique utilizes the electromagnetic environment as the fingerprint, compares the electromagnetic fingerprint of equipment with the fingerprint storehouse of gathering the formation earlier stage to confirm the position of equipment, can effectively solve thing networking device and lack the problem that orientation module and locating information easily received the manipulation.
In recent years, more and more internet of things (IoT) devices are deployed, including cell phones, computers, various sensors, and the like. Location Based Services (LBS) utilize location data to provide appropriate information to a user, such as nearby businesses, nearby traffic conditions, and the like. LBS is widely applied to car networking, electronic medical treatment, environmental monitoring, home office automation and the like. Location information plays an important role in various wireless sensor network applications. A Global Positioning System (GPS) may be used as a solution for location-based services. However, manufacturers of the internet of things often do not take security as a priority factor, which brings some security risks to the location service in the internet of things. In addition, some internet of things devices do not have the capability of actively locating themselves, such as cameras, sensors, etc., and they do not have a location module.
The blockchain is a decentralized infrastructure which is gradually raised along with the increasing popularization of digital encryption currencies such as bitcoin and the like, and the unique work mechanism of the whole network authentication enables the blockchain to have the characteristics of fraud prevention, double payment prevention and the like in a distributed system and a peer-to-peer (P2P) network. Through development and improvement of a few years, a block chain gradually breaks away from bitcoin, becomes a novel distributed and decentralized technical scheme, independently becomes a hotspot of network technology innovation, creates a brand-new data distributed storage technology, and has received more and more attention in application. As a novel calculation paradigm and a cooperation mode for establishing trust at low cost, a blockchain changes application scenes and operation rules of various industries by virtue of a unique trust establishment mechanism of the blockchain, and is one of indispensable technologies for establishing a novel trust system in the future.
The application of the block chain technology provides a new idea for solving the problems of complex offline data collection, privacy protection of centralized calculation and storage, difficulty in sharing positioning information and the like in the electromagnetic fingerprint positioning process, and combines an intelligent contract to realize a fingerprint positioning scheme combining on-chain calculation and off-chain calculation to form an online updated distributed positioning scheme. In conclusion, the research on the positioning technology of the internet of things equipment based on the block chain has important significance.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, an object of the present application is to provide a location fingerprint positioning method for internet of things devices based on a block chain, which can be used to improve the security of positioning the internet of things devices and provide positioning services for some internet of things devices without positioning capability.
Another objective of the present application is to provide a location fingerprint positioning system for an internet of things device based on a block chain.
In order to achieve the above object, an embodiment of the application provides a location fingerprint positioning method for an internet of things device based on a block chain, which includes the following steps: establishing a block chain-based on-chain position fingerprint database; uploading corresponding electromagnetic fingerprints by the Internet of things equipment with a positioned actual position in the area, recording the electromagnetic fingerprints in the position fingerprint database, training a positioning model by a solving node under an intelligent contract distribution chain, and generating an electromagnetic fingerprint positioning algorithm model after the solving node reads the position fingerprint database; and receiving positioning requests of other nodes, generating a positioning result on the chain by using the electromagnetic fingerprint positioning algorithm model according to the positioning requests, and returning the positioning result to other nodes sending the positioning requests.
In order to achieve the above object, an embodiment of another aspect of the present application provides a location fingerprint positioning system for an internet of things device based on a block chain, including: the database establishing module is used for establishing a block chain-based on-chain position fingerprint database; the model establishing module is used for uploading corresponding electromagnetic fingerprints by the Internet of things equipment with the positioned actual position in the area, recording the electromagnetic fingerprints in the position fingerprint database, training a positioning model by a solving node under an intelligent contract distribution chain, and generating an electromagnetic fingerprint positioning algorithm model after the solving node reads the position fingerprint database; and the positioning module is used for receiving positioning requests of other nodes, generating a positioning result on the chain by using the electromagnetic fingerprint positioning algorithm model according to the positioning requests, and returning the positioning result to the other nodes sending the positioning requests.
The method and the system for locating the position fingerprint of the equipment in the internet of things based on the block chain can be used for improving the locating safety of the equipment in the internet of things and providing locating service for part of equipment in the internet of things without locating capability, and have the following beneficial effects:
1) a position fingerprint solution is introduced to supplement a GPS, so that positioning service is provided for equipment which cannot be positioned, the authenticity of a position is verified, and the cost of position counterfeiting and tampering is increased;
2) by using a block chain technology, the reliability and the safety of the system are enhanced by establishing a position fingerprint database on a chain, and the complexity of offline fingerprint acquisition is reduced;
3) by combining the intelligent contract and the down-link calculation, the positioning safety can be ensured while the calculation time and the resource consumption are saved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is an overall framework of a block chain based internet of things device location fingerprint positioning system according to an embodiment of the present application;
fig. 2 is a flowchart of a location fingerprint positioning method for an internet of things device based on a block chain according to an embodiment of the present application;
FIG. 3 is a diagram illustrating a scheme for location calculation of uplink and downlink bonding in a chain according to an embodiment of the present application;
FIG. 4 is a flowchart of a computing task validation process according to one embodiment of the present application;
fig. 5 is a schematic structural diagram of a location fingerprint positioning system for devices of the internet of things based on a block chain according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The method mainly solves the problems that the Internet of things equipment lacks positioning capacity, positioning tampering and counterfeiting, auxiliary positioning information is acquired by adopting a position electromagnetic fingerprint algorithm to be used as supplement and verification of positioning signals, and the characteristics that block chain data cannot be tampered, can be traced and the like are utilized.
In view of the explosion of the 5G in the future, 5G base stations will be constructed on a large scale and can be used to generate a location fingerprint database. Each mobile device receives signals from one or more APs and uploads to the location fingerprint database by the identified mobile device as a reference for the remaining mobile device location credentials, using the RSS of the mobile device as a location fingerprint. Location fingerprints typically have two phases: an offline phase and an online phase. In the off-line phase, in order to collect fingerprints and build a database at various locations, cumbersome surveys in designated areas are required. The designated area is divided into squares and the RSS is measured at the grid points, referred to as the training set. In the online phase, the specific location of the mobile device is unknown, and is unlikely even to be on a grid point. Assuming that the mobile device has measured the RSS of each AP, determining the location of the mobile device is finding a fingerprint in the fingerprint database that best matches the RSS measured by the mobile device. Once the best match is found, the location of the mobile device is estimated as the corresponding location of the best matching fingerprint. Although the location fingerprint algorithm can effectively solve the problem of location of the internet of things equipment which cannot be located, the establishment of the location fingerprint database requires a large amount of tedious acquisition work. In the face of the problem of establishing the position fingerprint database, the nodes in the block chain upload fingerprints by themselves, so that the position fingerprint database can be established quickly and conveniently. The location fingerprint uploaded by the node is stored in the block chain, and the location of a certain point can be acquired through the location fingerprint database and the RSS of the point.
The existing block chain technology has bottlenecks in capacity, computing performance and expandability under a common chain and single-chain structure. The data storage mode of chain local storage is difficult to perform parallel expansion of services; the consensus model of the synchronous state machine is difficult to process the calculation with low delay requirement; the performance, capacity and delay requirements in the scene of the internet of things cannot be met due to the limitation of the performance of the nodes in the network. The Internet of things equipment positioning has the characteristics of large positioning data quantity, more nodes, small calculation and storage capacity and high positioning real-time requirement. In order to solve the problems, the application provides a location fingerprint positioning scheme based on a block chain and suitable for the scene of the Internet of things.
The overall system architecture provided by the application is shown in fig. 1, and in order to adapt to the conditions of a large number of nodes of the internet of things and limited power of a single node, a alliance link structure is adopted. The full node is served by an internet of things node with powerful computing and storage capabilities, such as a computer or server. They store all the information of the block chain, participate in the consensus of the block chain, and share the calculation task under the chain. The resource-constrained node acts as a light node mainly related to uploading and positioning of location fingerprints. Furthermore, in a positioning scenario, nodes are divided into positioning-enabled and non-positioning-enabled capabilities. The Internet of things equipment with the positioning function uploads the position fingerprints of the equipment, and an online position fingerprint database is formed on the chain and is used for positioning equipment without active positioning capacity. The system adopts a main chain and sub chain combined mode in consideration of large position data volume and high calculation delay requirement of the Internet of things. Nodes of the internet of things in the range form a sub-chain, and position fingerprints and a positioning algorithm model of the area are recorded. The sub-chains are recorded on the main chain in a Hash mode, so that the storage and calculation pressure of the main chain is reduced, and the positioning efficiency is improved.
As an initial node of the block chain, the location fingerprints of all APs are always stored in the location fingerprint database without being updated. The mobile device joins the block chain after being verified by the existing node in the block chain, and broadcasts the position fingerprint of the mobile device periodically. The node collects the received position fingerprint broadcast, packs to generate a new block, and adds the new block to the chain under the action of a consensus mechanism. The node judges whether a block is legal or not according to the following rules: blocks must be generated by legitimate nodes; verifying that the location fingerprint in the block is correct, i.e. that the euclidean distance between the coordinates obtained by entering the RSS location fingerprint algorithm and the coordinates recorded in the block is acceptable; the hash value recorded in a block must be the hash value of the previous block, i.e. the hash value of the last block in the current block chain. The verified block will be added to the existing block chain. The location fingerprints recorded in all blocks of the blockchain constitute a location fingerprint database, which is authentic and non-tamperable.
The problem that Internet of things equipment lacks location ability and location is falsified, forged is solved in this application, adopt position electromagnetic fingerprint algorithm to acquire auxiliary positioning information and as the supplement and the verification of locating signal, utilize characteristics such as block chain data can't falsify, traceable, design online renewal's distributed location scheme under block chain frame, the Internet of things equipment that has the location ability uploads oneself location and electromagnetic fingerprint on line, form the electromagnetic fingerprint storehouse of on-chain storage, supply the equipment that does not have the location ability to carry out the electromagnetic fingerprint location and verify the location result.
The method and the system for locating the location fingerprint of the internet of things device based on the block chain are described below with reference to the attached drawings.
Firstly, a location fingerprint positioning method for an internet of things device based on a block chain according to an embodiment of the present application will be described with reference to the accompanying drawings.
Fig. 2 is a flowchart of a location fingerprint positioning method for an internet of things device based on a block chain according to an embodiment of the present application.
As shown in fig. 2, the location fingerprint positioning method for the internet of things device based on the block chain includes the following steps:
in step S101, a block chain-based on-chain location fingerprint database is established.
Optionally, in an embodiment of the present application, establishing a block chain-based location fingerprint database on a chain includes: when each mobile device receives signals from one or more APs, the electromagnetic fingerprint and location information for the mobile device are uploaded into a location fingerprint database using the received signal strength vector for each mobile device as the electromagnetic fingerprint.
In order to relieve the situation that part of Internet of things equipment cannot be positioned and reduce the risks of position tampering and counterfeiting, a position fingerprint algorithm is introduced as a supplement of a GPS. In order to enhance the safety and persuasion, a positioning network of the Internet of things equipment is simulated by using the block chain, and a position fingerprint positioning scheme based on the block chain is provided. By placing the location fingerprint repository and the computation of the location on the chain, the decentralized nature of the blockchain is exploited to better protect data security and user privacy.
Electromagnetic fingerprint positioning is first performed, each mobile device receiving signals from one or more APs and using the RSS of the mobile device as an electromagnetic fingerprint, uploaded by the identified mobile device to an electromagnetic fingerprint database as a reference for the remaining mobile device location credentials.
The electromagnetic fingerprint consists of two parts: the received signal strength vector RSS and the position information P. The vector RSS consists of the received signal strengths measured by the nodes of the surrounding APs, expressed as: RSS ═ ρ1,ρ2,…,ρn]Where ρ isiIs the average received signal strength from the ith AP. The location information is a binary with a tag P ═ x, y.
In step S102, the corresponding electromagnetic fingerprint is uploaded by the internet of things device located at the actual position in the area, and recorded in the position fingerprint database, the positioning model is trained by the solution node under the intelligent contract distribution chain, and after the solution node reads the position fingerprint database, the electromagnetic fingerprint positioning algorithm model is generated.
Optionally, in an embodiment of the present application, the verified electromagnetic fingerprint is recorded in a location fingerprint database, and the verification process further includes: respectively calculating the distance between the node to be measured and each received signal strength vector in the fingerprint database; and selecting the numerical values of K electromagnetic fingerprint calculation labels (x, y) with the nearest distance, and averaging K position coordinates of the fingerprints to obtain a positioning result. The calculation formula of the positioning result is as follows:
wherein (x)i,yi) Refers to the position of the K points where the received signal strength vector is closest in euclidean distance. And if the error between the calculated positioning result and the uploading result of the equipment is within a certain threshold value, the verification is considered to be passed.
The electromagnetic fingerprint uploaded by the node is stored in the block chain, and the position information of a certain point can be obtained through the electromagnetic fingerprint library and the RSS of the point. The electromagnetic fingerprinting method can be seen as a classification or regression problem (features are RSS vectors, labels are locations). Supervised machine learning methods may train a mapping model from data to features to labels. The node position is determined by adopting a K-nearest neighbor (KNN) classification algorithm, namely K fingerprint positions closest to the current RSS are selected to estimate the current position.
In order to measure the distance between a real-time RSS sample and a sample in the location database, assuming that the number of sampling points and APs is m, n, respectively, the euclidean distance is used as a measure of the distance between two RSS samples:
where ρ isijRefers to the RSS sampling value rho of the i reference point of the jth AP in the electromagnetic fingerprint databasejRefers to the RSS samples from the jth AP in real time.
And respectively calculating the distance between the node to be measured and each RSS vector in the fingerprint library, and selecting the nearest K electromagnetic fingerprint to carry out numerical calculation of the label (x, y). The average of the K position coordinates of the fingerprint is used as the positioning result.
Wherein (x)i,yi) Referring to the position of K points with the nearest RSS Euclidean distance, the optimal value of the parameter K is estimated by 10-fold cross validation, and the flow of the cross validation is as follows:
(1) the data set was divided into ten parts, and 9 parts of the data set were used as training data and 1 part of the data set was used as test data in turn for the experiments. Each trial will yield a corresponding accuracy (or error rate).
(2) The average of the accuracy (or error rate) of the 10 results is used as an estimate of the accuracy of the algorithm.
(3) And (3) repeating the steps (1) and (2), and then solving the average value of the steps to serve as an estimation for the accuracy of the algorithm.
The electromagnetic fingerprint positioning algorithm is as follows:
in step S103, a positioning request of another node is received, a positioning result is generated on the chain by using the electromagnetic fingerprint positioning algorithm model according to the positioning request, and the positioning result is returned to the other node that sent the positioning request.
The positioning algorithm executed by the intelligent contract mainly faces the difficult problems of large resource consumption and long time consumption, and because the operation result of the intelligent contract can be recorded on a chain only through the consensus of nodes, a lot of redundant calculation is generated. In order to improve the calculation efficiency, the training process in the electromagnetic fingerprint positioning algorithm is carried out under the chain, and the positioning calculation is carried out on the chain, so that the safety of the positioning calculation is ensured, and the resource consumption is reduced.
The overall process of the positioning scheme combining uplink and downlink on the chain is shown in fig. 3, and can be divided into three stages, namely establishment of an electromagnetic fingerprint library, training of a downlink positioning model and positioning of electromagnetic fingerprints. Firstly, uploading own electromagnetic fingerprint by Internet of things equipment with positioning capability in an area, and recording the electromagnetic fingerprint subjected to authenticity verification in an electromagnetic fingerprint library on a chain; and training a positioning algorithm model by a solving node under an intelligent contract distribution chain, finishing the training of the positioning algorithm locally after the solving node reads an electromagnetic fingerprint library on the chain, and uploading the signed training model. After signature verification and model verification are carried out on the training model by the block chain, an updated electromagnetic fingerprint positioning model is recorded on the chain; and the nodes with the positioning requirements initiate positioning requests to the intelligent contract, execute positioning algorithms on the chain and return positioning results to the positioning request nodes.
The system sets LCoin as a reward for participating in the calculation on the chain, which LCoin can be used to initiate a location request in the system. The credibility of the electromagnetic fingerprints stored on the chain is guaranteed due to the traceable and non-falsifiable characteristics of the block chain, and when the electromagnetic fingerprints are uploaded by the nodes, the nodes can be successfully linked up only after verification errors are within 3 m; otherwise, the node uploading the false electromagnetic fingerprint is penalized by a fine.
In order to prevent a single node from maliciously uploading electromagnetic fingerprints in a large quantity at the same place in a short time and causing offset of system positioning, the uploading interval of each user is set, and each user is required to upload the electromagnetic fingerprints for no more than 5 times within ten minutes. Meanwhile, in order to prevent the nodes from forging a large number of identities and uploading a large number of forged electromagnetic fingerprints, a part of security deposit needs to be paid when the nodes upload the electromagnetic fingerprints each time, and if the forged electromagnetic fingerprints are uploaded, namely the authentication is not passed, the security deposit can be recovered; if the uploaded electromagnetic fingerprint is verified, the deposit is returned to the node.
Optionally, in an embodiment of the present application, after generating the electromagnetic fingerprint positioning algorithm model, the method further includes: generating a computing node by taking the hash value of the previous block as a random number, and publishing the computing node on a chain, so that the node acquires the serial number of the computing node by accessing an intelligent contract; the selected computing nodes send the ID and the time stamp to the intelligent contract to determine that the computing nodes participate in the down-link computation; and if the selected computing node does not respond within the preset time, the selected computing node is regarded as giving up the computing right, the intelligent contract waits for obtaining the hash of the previous block as a random number, a new solution node is selected, after the intelligent contract distributes the computing nodes, all nodes on the alliance chain vote to a verification node, and after the verification is passed, the solution node, the verification signature and the electromagnetic fingerprint positioning algorithm model are recorded on the block chain.
In particular, the distribution and validation of the calculation tasks under the chain is realized on the intelligent contract. In order to ensure the randomness of the selection of the computing nodes, the computing nodes are generated by taking the hash value of the previous block as a random number and published on the chain. The node obtains the serial number of the computing node by accessing the intelligent contract. The selected node sends the ID and timestamp to the intelligent contract to determine its participation in the down-link computation. If the selected node does not respond within a certain waiting time, the selected node is regarded as abandoning the calculation right, and the intelligent contract waits for acquiring the hash of the previous block as a random number and selects a new solution node. In order to ensure the reliability of the calculation result under the link, after the intelligent contract allocates the calculation nodes, all the nodes on the alliance link vote for the verification nodes. And the verification node verifies the calculation result of the solution node and returns the verification result to the intelligent contract. And collecting the verification result by the intelligent contract, and if the nodes exceeding a certain proportion are consistent, determining that the verification is passed. If the verification fails, the solution node performing this calculation will face a penalty and lose the eligibility to participate in the calculation under the chain for a period of time, while the verification node will receive the reward. The intelligent contract will then reassign the solution node for computation. If the verification is passed, the solution node, the verification signature and the fingerprint location model will be recorded together on the blockchain.
The specific flow of the program is shown in fig. 4, and mainly includes the following steps:
step 1: the compute node numbers are randomly generated and published on the contracts.
numbercom＝hashpremod numcandidate
Wherein numbercomNumbering for the calculation of sections, hashpreHash, num of the previous blockcandidateThe number of candidate nodes.
Step 2: compute node slaveThe contract obtains the issued result, sends its ID and signature to the smart contract and calculates locally. If the solving node is at a certain TimelimitIf no reply exists, the calculation right is regarded as automatically abandoning. At this point, the compute node is not penalized.
And step 3: the solution node returns the hash and signature of the result to the intelligent contract. After the intelligent contract verifies the signature, the hash value of the calculation result is stored on the chain. If a computing node times out at this step, it is also considered to automatically abandon the computation, and the node will be penalized.
And 4, step 4: and the intelligent contract organization node votes to the verification node and issues the verification node. The verification node obtains the result issued on the contract, sends its ID to the intelligent contract and calculates locally. If the verification node is at a certain TimelimitIf there is no reply, the authentication right is regarded as automatically abandoning.
And 5: the verification node returns the hash and signature of the result to the intelligent contract. The intelligent contract returns a result and a threshold value Pass according to the nodepercentageAnd judging whether the verification is passed or not. If the verification is passed, the computing node uploads the result to the intelligent contract again.
Step 6: and the intelligent contract records the result after checking. Finally, the compute node and the verification node receive the reward.
According to the location fingerprint positioning method for the Internet of things equipment based on the block chain, the location fingerprint is used as a supplement of a GPS, so that the location is provided for equipment which cannot be positioned, and the cost for location attack is increased. In addition, the system utilizes the block chain to model the positioning environment of the Internet of things equipment. The position fingerprint database on the chain protects the fingerprint safety and provides a channel for online updating and data sharing. By combining intelligent contracts and under-chain calculation, a fingerprint positioning algorithm is deployed on a block chain, and the reliability of positioning is ensured through distributed calculation.
The location fingerprint positioning system of the internet of things device based on the block chain is described next with reference to the attached drawings.
Fig. 5 is a schematic structural diagram of a location fingerprint positioning system for devices of the internet of things based on a block chain according to an embodiment of the present application.
As shown in fig. 5, the location fingerprint positioning system for devices of internet of things based on a block chain includes: database building module 100, model building module 200, and location module 300.
The database establishing module 100 is configured to establish a block chain-based on-chain position fingerprint database. The model establishing module 200 is configured to upload a corresponding electromagnetic fingerprint from an internet of things device located at an actual position in an area, record the electromagnetic fingerprint in a position fingerprint database, train a location model by a solution node under an intelligent contract distribution chain, and generate an electromagnetic fingerprint location algorithm model after the solution node reads the position fingerprint database. The positioning module 300 is configured to receive positioning requests of other nodes, generate a positioning result on the chain by using an electromagnetic fingerprint positioning algorithm model according to the positioning requests, and return the positioning result to the other nodes that send the positioning requests.
Optionally, in an embodiment of the present application, establishing a block chain-based location fingerprint database on a chain includes: when each mobile device receives signals from one or more APs, the electromagnetic fingerprint and location information for the mobile device are uploaded into a location fingerprint database using the received signal strength vector for each mobile device as the electromagnetic fingerprint.
Optionally, in an embodiment of the present application, the recording the electromagnetic fingerprint in a location fingerprint database further includes: respectively calculating the distance between the node to be measured and each received signal strength vector in the fingerprint database; and selecting the numerical values of K electromagnetic fingerprint calculation labels (x, y) with the nearest distance, and averaging K position coordinates of the fingerprints to obtain a positioning result.
Optionally, in an embodiment of the present application, a calculation formula of the positioning result is:
wherein (x)i,yi) Finger received signal strengthThe degree vector is the position of the K points with the closest euclidean distance.
It should be noted that the explanation of the embodiment of the location fingerprint positioning method for the internet of things device based on the block chain is also applicable to the location fingerprint positioning system for the internet of things device based on the block chain in this embodiment, and details are not repeated here.
According to the location fingerprint positioning system for the equipment in the Internet of things based on the block chain, the location fingerprint is used as the supplement of the GPS, so that the location is provided for equipment which cannot be positioned, and the cost for location attack is increased. In addition, the system utilizes the block chain to model the positioning environment of the Internet of things equipment. The position fingerprint database on the chain protects the fingerprint safety and provides a channel for online updating and data sharing. By combining intelligent contracts and under-chain calculation, a fingerprint positioning algorithm is deployed on a block chain, and the reliability of positioning is ensured through distributed calculation.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (8)
1. An Internet of things equipment position fingerprint positioning method based on a block chain is characterized by comprising the following steps:
establishing a block chain-based on-chain position fingerprint database;
uploading corresponding electromagnetic fingerprints by the Internet of things equipment with a positioned actual position in the area, recording the electromagnetic fingerprints in the position fingerprint database, training a positioning model by a solving node under an intelligent contract distribution chain, and generating an electromagnetic fingerprint positioning algorithm model after the solving node reads the position fingerprint database; and
and receiving positioning requests of other nodes, generating a positioning result on the chain by using the electromagnetic fingerprint positioning algorithm model according to the positioning requests, and returning the positioning result to other nodes sending the positioning requests.
2. The method of claim 1, wherein the building a block chain based on-chain location fingerprint database comprises:
when each mobile device receives signals from one or more APs, the electromagnetic fingerprint and the position information of the mobile device are uploaded to the position fingerprint database by using the received signal strength vector of each mobile device as the electromagnetic fingerprint.
3. The method of claim 1, after generating the electromagnetic fingerprint positioning algorithm model, further comprising:
generating a computing node by taking the hash value of the previous block as a random number, and publishing the computing node on a chain, so that the node acquires the serial number of the computing node by accessing an intelligent contract;
the selected computing nodes send the ID and the time stamp to the intelligent contract to determine that the computing nodes participate in the down-link computation;
and if the selected computing node does not respond within the preset time, the selected computing node is regarded as giving up the computing right, the intelligent contract waits for the hash of the previous block to be obtained as a random number, a new solution node is selected, after the intelligent contract distributes the computing nodes, all nodes in a alliance chain vote to a verification node, and after the verification is passed, the solution node, the verification signature and the electromagnetic fingerprint positioning algorithm model are recorded on a block chain.
4. The utility model provides a thing networking device location fingerprint positioning system based on block chain which characterized in that includes:
the database establishing module is used for establishing a block chain-based on-chain position fingerprint database;
the model establishing module is used for uploading corresponding electromagnetic fingerprints by the Internet of things equipment with the positioned actual position in the area, recording the electromagnetic fingerprints in the position fingerprint database, training a positioning model by a solving node under an intelligent contract distribution chain, and generating an electromagnetic fingerprint positioning algorithm model after the solving node reads the position fingerprint database; and
and the positioning module is used for receiving positioning requests of other nodes, generating a positioning result on the chain by using the electromagnetic fingerprint positioning algorithm model according to the positioning requests, and returning the positioning result to the other nodes sending the positioning requests.
5. The system of claim 4, wherein the building of the block chain based on-chain location fingerprint database comprises: when each mobile device receives signals from one or more APs, the electromagnetic fingerprint and the position information of the mobile device are uploaded to the position fingerprint database by using the received signal strength vector of each mobile device as the electromagnetic fingerprint.
6. The system of claim 5, wherein the recording the electromagnetic fingerprint in the location fingerprint database further comprises: respectively calculating the distance between the node to be measured and each received signal strength vector in the fingerprint database; and selecting the numerical values of K electromagnetic fingerprint calculation labels (x, y) with the nearest distance, and averaging K position coordinates of the fingerprints to obtain a positioning result.
7. The system of claim 6, wherein the positioning result is calculated by the formula:
wherein (x)i,yi) Refers to the position of the K points where the received signal strength vector is closest in euclidean distance.
8. The system of claim 4, further comprising: the recording module is used for generating a computing node by taking the hash value of the previous block as a random number after the electromagnetic fingerprint positioning algorithm model is generated, and publishing the computing node on a chain, so that the node can obtain the serial number of the computing node by accessing an intelligent contract; the selected computing nodes send the ID and the time stamp to the intelligent contract to determine that the computing nodes participate in the down-link computation; and if the selected computing node does not respond within the preset time, the selected computing node is regarded as giving up the computing right, the intelligent contract waits for the hash of the previous block to be obtained as a random number, a new solution node is selected, after the intelligent contract distributes the computing nodes, all nodes in a alliance chain vote to a verification node, and after the verification is passed, the solution node, the verification signature and the electromagnetic fingerprint positioning algorithm model are recorded on a block chain.
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