CN113190653A - Traffic data monitoring system based on block chain - Google Patents
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Abstract
The invention discloses a traffic data monitoring system based on a block chain, which relates to the technical field of traffic data monitoring and solves the technical problem that the accuracy of traffic data is reduced because the speed analysis of a real-time running vehicle cannot be carried out in the prior art; the speed of the running vehicles on the running road is analyzed, so that the traffic condition is judged, the traffic data is uploaded, and the accuracy of the traffic data is improved.
Description
Technical Field
The invention relates to the technical field of traffic data monitoring, in particular to a traffic data monitoring system based on a block chain.
Background
Along with the rapid development of national economy, the number of vehicles on roads is rapidly increased, the traffic pressure is multiplied, how to realize the safe and efficient traffic of road traffic becomes a problem which is urgently needed to be solved, in the construction process of an intelligent traffic system, the realization of the real-time collection and judgment of traffic information is a key step, the traffic information is important basic information of urban traffic planning and traffic management, the development situation of the urban roads can be mastered by acquiring comprehensive, rich and real-time traffic information, the future development can be predicted, and a scientific basis is provided for the correct decision of the urban traffic planning and traffic management department;
however, in the prior art, the speed of a vehicle running in real time cannot be analyzed, which results in the reduction of the accuracy of traffic data.
Disclosure of Invention
The invention aims to provide a traffic data monitoring system based on block chains, which is characterized in that after being received by a storage unit, the storage unit is classified and stored, the storage unit is divided into a plurality of blocks, the speed of a running vehicle is set, the speed of the running vehicle is divided, then key texts are constructed for each block, virtual bookmarks are constructed in the storage unit, the virtual bookmarks comprise safe speed bookmarks, dangerous speed bookmarks and abnormal speed bookmarks, then blocks in the storage unit are divided through the virtual bookmarks, and the block chains corresponding to the blocks in each virtual bookmark are subjected to data blocking, namely the block chains between the blocks are set to be data zero communication; the data classification is carried out on the blocks, the data storage load of the blocks is reduced, data communication among the blocks is blocked, the risk of data disorder in the storage unit is reduced, and the storage quality of traffic data is improved.
The purpose of the invention can be realized by the following technical scheme:
a traffic data monitoring system based on a block chain comprises a data analysis unit, a traffic monitoring platform, a query terminal, a data calling unit, a storage unit and a plurality of blocks;
the data analysis unit is used for analyzing road vehicles so as to monitor road traffic conditions, and the specific analysis and monitoring process is as follows:
step S1: setting a road monitoring area, dividing the road monitoring area into a plurality of sub-areas, marking the sub-areas as i, i is 1, 2, … …, m and m are positive integers, then acquiring roads in each sub-area, and marking the roads as o, o is 1, 2, … …, k and k are positive integers;
step S2: setting speed measuring points in each road in each sub-area, wherein a speed measuring equipment terminal in each speed measuring point emits rays to the outer surface of a running vehicle, the emitted rays are marked as emergent rays, then the emergent rays reach the outer surface of the vehicle and return to the speed measuring equipment terminal, the returned emergent rays are marked as return rays, then the wavelengths of the emergent rays and the return rays are compared, if the wavelengths are tight, the speed of the running vehicle is judged to be high, otherwise, the speed of the running vehicle is judged to be low;
step S3: then setting a test road section, when the driving vehicle reaches the starting point of the test road section, the speed measuring device terminal emits the emergent ray and receives the retro-reflected ray, recording the interval time and marking as t1, when the driving vehicle reaches the end point of the test road section, the speed measuring device terminal emits the emergent ray and receives the retro-reflected ray, recording the interval time and marking as t2, and processing the interval time and the retro-reflected ray according to a formulaAcquiring the distance MC of a running vehicle receiving pulse waves twice continuously, wherein 340 is expressed as sound speed, namely 340 meters per second, then acquiring the time points when the pulse waves are received at the starting point and the end point of the running vehicle, acquiring the time of receiving the pulse waves of the running vehicle through difference calculation, comparing the distance MC of receiving the pulse waves with the time of receiving the pulse waves to acquire the running speed of the vehicle, and sending the running speed of the vehicle and corresponding vehicle information to a traffic monitoring platform, and the vehicleThe vehicle information comprises vehicle type, brand and license plate number; the speed of the running vehicles on the running road is analyzed, so that the traffic condition is judged, the traffic data is uploaded, and the accuracy of the traffic data is improved.
Further, after receiving the vehicle running speed and the corresponding vehicle information, the traffic monitoring platform sends the vehicle running speed and the corresponding vehicle information to the storage unit, and the storage unit performs classified storage on the vehicle running speed and the corresponding vehicle information after receiving the vehicle information, wherein the specific classified storage process is as follows:
step SS 1: dividing the memory cells into a number of blocks and marking the blocks as Q, and then constructing a block set { Q1, Q2, … …, Qn };
step SS 2: then, vehicle speed thresholds L1 and L2 are set, the speed of a running vehicle is set, if the vehicle speed is more than 0 and less than L1, the vehicle is judged to be a congestion vehicle speed, if the vehicle speed is less than or equal to L1 and less than or equal to L2, the vehicle speed is judged to be a normal vehicle speed, if the vehicle speed is more than L2, the vehicle speed is judged to be a dangerous vehicle speed, and if the vehicle speed is 0, the vehicle speed is judged to be an accident vehicle speed;
step SS 3: dividing the speed of a running vehicle, storing the divided speed of the running vehicle and corresponding vehicle information into blocks, then constructing a keyword text for each block, extracting keywords from the speed of the running vehicle and the corresponding vehicle information of the block, marking the keywords as W, and then constructing a block keyword set { WQ1, WQ2, … … and WQ3}, wherein WQ2 is represented as the keyword text of a second block;
step SS 4: constructing virtual bookmarks in a storage unit, wherein the virtual bookmarks comprise safe speed bookmarks, dangerous speed bookmarks and abnormal speed bookmarks, then dividing blocks in the storage unit through the virtual bookmarks, and blocking block chains corresponding to the blocks in each virtual bookmark, namely setting the block chains between the blocks as data zero communication; the data classification is carried out on the blocks, the data storage load of the blocks is reduced, data communication among the blocks is blocked, the risk of data disorder in the storage unit is reduced, and the storage quality of traffic data is improved.
Further, the data retrieving unit is configured to retrieve data in the storage unit, and a specific retrieving process is as follows:
step TT 1: the method comprises the steps that a user sends an inquiry signal to an inquiry terminal through a mobile phone terminal, the inquiry terminal obtains an inquiry text of the user after receiving the inquiry signal and sends the inquiry signal and the inquiry text to a traffic monitoring platform, the traffic monitoring platform generates a data calling signal after receiving the inquiry signal and sends the data calling signal to a data calling unit, and the inquiry text is an information text provided when the user inquires vehicle data;
step TT 2: acquiring a query text, carrying out word segment division on the query text according to semantics, then acquiring the occurrence frequency and frequency of words, marking the occurrence frequency and frequency as CS and PL, and acquiring a word key coefficient DF in the query text by a formula DF ═ alpha (CS × a1+ PL × a2), wherein a1 and a2 are both proportionality coefficients, a1 is more than a2 and more than 0, alpha is an error correction factor and is 1.23 in value, and the word segment division is expressed by dividing words and words in the text under a semantic currency condition;
step TT 3: then, the keyword corresponding to the word key coefficient with the highest value in the query text is marked as an extraction keyword, the extraction keyword is compared with the keyword text of each block in the storage unit, if the extraction keyword is consistent with the keyword text of the block, the corresponding block is judged to be a preselected block, otherwise, the corresponding block is judged to be an excluded block;
step TT 4: and then obtaining the vehicle provided by the user and comparing the vehicle with the vehicle information in the preselected block, if the information is consistent, marking the corresponding preselected block as a selected block, setting a mobile phone terminal network of the corresponding user as a white list of the selected block, simultaneously setting query interval duration, and if the information is inconsistent, generating a re-extraction signal and re-extracting the data.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, road vehicles are analyzed through a data analysis unit, so that road traffic conditions are monitored, a road monitoring area is set, the road monitoring area is divided into a plurality of sub-areas, roads in each sub-area are obtained, a speed measuring point is set in each road in each sub-area, the wavelengths of an outgoing ray and a return ray are compared, if the wavelengths are tight, the speed of a running vehicle is judged to be fast, otherwise, the speed of the running vehicle is judged to be slow; then setting a test road section, obtaining the distance MC of the running vehicle receiving the pulse wave twice continuously through a formula, and obtaining the running speed of the vehicle by comparing the distance MC of the received pulse wave with the time of receiving the pulse; the speed of the running vehicles on the running road is analyzed, so that the traffic condition is judged, and the traffic data is uploaded, so that the accuracy of the traffic data is improved;
2. the method comprises the steps of receiving and classifying storage through a storage unit, dividing the storage unit into a plurality of blocks, setting the speed of a running vehicle, dividing the speed of the running vehicle, constructing a key text for each block, constructing a virtual bookmark in the storage unit, wherein the virtual bookmark comprises a safe speed bookmark, a dangerous speed bookmark and an abnormal speed bookmark, then dividing the blocks in the storage unit through the virtual bookmark, and blocking data of block chains corresponding to the blocks in each virtual bookmark, namely setting the block chains among the blocks as data zero communication; the data classification is carried out on the blocks, the data storage load of the blocks is reduced, data communication among the blocks is blocked, the risk of data disorder in the storage unit is reduced, and the storage quality of traffic data is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a traffic data monitoring system based on a block chain includes a data analysis unit, a traffic monitoring platform, a query terminal, a data retrieval unit, a storage unit, and a plurality of blocks;
the data analysis unit is used for analyzing road vehicles so as to monitor road traffic conditions, and the specific analysis and monitoring process is as follows:
step S1: setting a road monitoring area, dividing the road monitoring area into a plurality of sub-areas, marking the sub-areas as i, i is 1, 2, … …, m and m are positive integers, then acquiring roads in each sub-area, and marking the roads as o, o is 1, 2, … …, k and k are positive integers;
step S2: setting speed measuring points in each road in each sub-area, wherein a speed measuring equipment terminal in each speed measuring point emits rays to the outer surface of a running vehicle, the emitted rays are marked as emergent rays, then the emergent rays reach the outer surface of the vehicle and return to the speed measuring equipment terminal, the returned emergent rays are marked as return rays, then the wavelengths of the emergent rays and the return rays are compared, if the wavelengths are tight, the speed of the running vehicle is judged to be high, otherwise, the speed of the running vehicle is judged to be low;
step S3: then setting a test road section, when the driving vehicle reaches the starting point of the test road section, the speed measuring device terminal emits the emergent ray and receives the retro-reflected ray, recording the interval time and marking as t1, when the driving vehicle reaches the end point of the test road section, the speed measuring device terminal emits the emergent ray and receives the retro-reflected ray, recording the interval time and marking as t2, and processing the interval time and the retro-reflected ray according to a formulaAcquiring the distance MC of the running vehicle receiving the pulse wave twice continuously, wherein 340 is expressed as the sound velocity, namely 340 meters per second, and then acquiring the starting point and the final point of the running vehicleThe method comprises the steps that a point receives a pulse wave time point, the time of receiving the pulse wave of a running vehicle is obtained through difference calculation, the running speed of the vehicle is obtained through comparison between the distance MC of receiving the pulse wave and the time of receiving the pulse wave, the running speed of the vehicle and corresponding vehicle information are sent to a traffic monitoring platform, and the vehicle information comprises the type, the brand and the license plate number of the vehicle;
after receiving the vehicle running speed and the corresponding vehicle information, the traffic monitoring platform sends the vehicle running speed and the corresponding vehicle information to the storage unit, and the storage unit carries out classified storage on the vehicle running speed and the corresponding vehicle information after receiving the vehicle information, wherein the specific classified storage process is as follows:
step SS 1: dividing the memory cells into a number of blocks and marking the blocks as Q, and then constructing a block set { Q1, Q2, … …, Qn };
step SS 2: then, vehicle speed thresholds L1 and L2 are set, the speed of a running vehicle is set, if the vehicle speed is more than 0 and less than L1, the vehicle is judged to be a congestion vehicle speed, if the vehicle speed is less than or equal to L1 and less than or equal to L2, the vehicle speed is judged to be a normal vehicle speed, if the vehicle speed is more than L2, the vehicle speed is judged to be a dangerous vehicle speed, and if the vehicle speed is 0, the vehicle speed is judged to be an accident vehicle speed;
step SS 3: dividing the speed of a running vehicle, storing the divided speed of the running vehicle and corresponding vehicle information into blocks, then constructing a keyword text for each block, extracting keywords from the speed of the running vehicle and the corresponding vehicle information of the block, marking the keywords as W, and then constructing a block keyword set { WQ1, WQ2, … … and WQ3}, wherein WQ2 is represented as the keyword text of a second block;
step SS 4: constructing virtual bookmarks in a storage unit, wherein the virtual bookmarks comprise safe speed bookmarks, dangerous speed bookmarks and abnormal speed bookmarks, then dividing blocks in the storage unit through the virtual bookmarks, and blocking block chains corresponding to the blocks in each virtual bookmark, namely setting the block chains between the blocks as data zero communication;
the data calling unit is used for calling the data in the storage unit, and the specific calling process is as follows:
step TT 1: the method comprises the steps that a user sends an inquiry signal to an inquiry terminal through a mobile phone terminal, the inquiry terminal obtains an inquiry text of the user after receiving the inquiry signal and sends the inquiry signal and the inquiry text to a traffic monitoring platform, the traffic monitoring platform generates a data calling signal after receiving the inquiry signal and sends the data calling signal to a data calling unit, and the inquiry text is an information text provided when the user inquires vehicle data;
step TT 2: acquiring a query text, carrying out word segment division on the query text according to semantics, then acquiring the occurrence frequency and frequency of words, marking the occurrence frequency and frequency as CS and PL, and acquiring a word key coefficient DF in the query text by a formula DF ═ alpha (CS × a1+ PL × a2), wherein a1 and a2 are both proportionality coefficients, a1 is more than a2 and more than 0, alpha is an error correction factor and is 1.23 in value, and the word segment division is expressed by dividing words and words in the text under a semantic currency condition;
step TT 3: then, the keyword corresponding to the word key coefficient with the highest value in the query text is marked as an extraction keyword, the extraction keyword is compared with the keyword text of each block in the storage unit, if the extraction keyword is consistent with the keyword text of the block, the corresponding block is judged to be a preselected block, otherwise, the corresponding block is judged to be an excluded block;
step TT 4: and then obtaining the vehicle provided by the user and comparing the vehicle with the vehicle information in the preselected block, if the information is consistent, marking the corresponding preselected block as a selected block, setting a mobile phone terminal network of the corresponding user as a white list of the selected block, simultaneously setting query interval duration, and if the information is inconsistent, generating a re-extraction signal and re-extracting the data.
The working principle of the invention is as follows:
a traffic data monitoring system based on a block chain is characterized in that when the system works, road vehicles are analyzed through a data analysis unit, so that road traffic conditions are monitored, a road monitoring area is set, the road monitoring area is divided into a plurality of sub-areas, then roads in the sub-areas are obtained, speed measuring points are set in the roads in the sub-areas, speed measuring equipment terminals in the speed measuring points emit rays to the outer surface of a running vehicle, the emitted rays are marked as emergent rays, the emergent rays reach the outer surface of the vehicle and then return to the speed measuring equipment terminals, the returned emergent rays are marked as return rays, then the wavelengths of the emergent rays and the return rays are compared, if the wavelengths are tight, the speed of the running vehicle is judged to be fast, otherwise, the speed of the running vehicle is judged to be slow; and then setting a test road section, acquiring the distance MC of the running vehicle continuously receiving the pulse waves twice through a formula, acquiring the time points of the running vehicle when the starting point and the terminal point receive the pulse waves, acquiring the time of the running vehicle for receiving the pulse waves through difference calculation, comparing the distance MC of the received pulse waves with the time of the received pulse waves to acquire the running speed of the vehicle, and sending the running speed of the vehicle and corresponding vehicle information to a traffic monitoring platform.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (3)
1. A traffic data monitoring system based on a block chain is characterized by comprising a data analysis unit, a traffic monitoring platform, a query terminal, a data calling unit, a storage unit and a plurality of blocks;
the data analysis unit is used for analyzing road vehicles so as to monitor road traffic conditions, and the specific analysis and monitoring process is as follows:
step S1: setting a road monitoring area, dividing the road monitoring area into a plurality of sub-areas, marking the sub-areas as i, i is 1, 2, … …, m and m are positive integers, then acquiring roads in each sub-area, and marking the roads as o, o is 1, 2, … …, k and k are positive integers;
step S2: setting speed measuring points in each road in each sub-area, wherein a speed measuring equipment terminal in each speed measuring point emits rays to the outer surface of a running vehicle, the emitted rays are marked as emergent rays, then the emergent rays reach the outer surface of the vehicle and return to the speed measuring equipment terminal, the returned emergent rays are marked as return rays, then the wavelengths of the emergent rays and the return rays are compared, if the wavelengths are tight, the speed of the running vehicle is judged to be high, otherwise, the speed of the running vehicle is judged to be low;
step S3: then setting a test road section, when the driving vehicle reaches the starting point of the test road section, the speed measuring device terminal emits the emergent ray and receives the retro-reflected ray, recording the interval time and marking as t1, when the driving vehicle reaches the end point of the test road section, the speed measuring device terminal emits the emergent ray and receives the retro-reflected ray, recording the interval time and marking as t2, and processing the interval time and the retro-reflected ray according to a formulaThe method comprises the steps of acquiring the distance MC of a running vehicle receiving pulse waves twice continuously, wherein 340 is expressed as sound speed, namely 340 meters per second, then acquiring the time points when the pulse waves are received at the starting point and the end point of the running vehicle, acquiring the time of the running vehicle for receiving the pulse waves through difference calculation, comparing the distance MC of the received pulse waves with the time of the received pulse waves to acquire the running speed of the vehicle, and sending the running speed of the vehicle and corresponding vehicle information to a traffic monitoring platform, wherein the vehicle information comprises the type, the brand and the license plate number of the vehicle.
2. The system according to claim 1, wherein the traffic monitoring platform sends the vehicle running speed and the corresponding vehicle information to the storage unit after receiving the vehicle running speed and the corresponding vehicle information, and the storage unit stores the vehicle information in a classified manner after receiving the vehicle information, and the specific classified storage process is as follows:
step SS 1: dividing the memory cells into a number of blocks and marking the blocks as Q, and then constructing a block set { Q1, Q2, … …, Qn };
step SS 2: then, vehicle speed thresholds L1 and L2 are set, the speed of a running vehicle is set, if the vehicle speed is more than 0 and less than L1, the vehicle is judged to be a congestion vehicle speed, if the vehicle speed is less than or equal to L1 and less than or equal to L2, the vehicle speed is judged to be a normal vehicle speed, if the vehicle speed is more than L2, the vehicle speed is judged to be a dangerous vehicle speed, and if the vehicle speed is 0, the vehicle speed is judged to be an accident vehicle speed;
step SS 3: dividing the speed of a running vehicle, storing the divided speed of the running vehicle and corresponding vehicle information into blocks, then constructing a keyword text for each block, extracting keywords from the speed of the running vehicle and the corresponding vehicle information of the block, marking the keywords as W, and then constructing a block keyword set { WQ1, WQ2, … … and WQ3}, wherein WQ2 is represented as the keyword text of a second block;
step SS 4: and constructing virtual bookmarks in the storage unit, wherein the virtual bookmarks comprise safe speed bookmarks, dangerous speed bookmarks and abnormal speed bookmarks, then dividing blocks in the storage unit through the virtual bookmarks, and blocking block chains corresponding to the blocks in each virtual bookmark, namely setting the block chains among the blocks as data zero communication.
3. The system according to claim 1, wherein the data retrieving unit is configured to retrieve data in the storage unit, and the retrieving process includes:
step TT 1: the method comprises the steps that a user sends an inquiry signal to an inquiry terminal through a mobile phone terminal, the inquiry terminal obtains an inquiry text of the user after receiving the inquiry signal and sends the inquiry signal and the inquiry text to a traffic monitoring platform, the traffic monitoring platform generates a data calling signal after receiving the inquiry signal and sends the data calling signal to a data calling unit, and the inquiry text is an information text provided when the user inquires vehicle data;
step TT 2: acquiring a query text, carrying out word segment division on the query text according to semantics, then acquiring the occurrence frequency and frequency of words, marking the occurrence frequency and frequency as CS and PL, and acquiring a word key coefficient DF in the query text by a formula DF ═ alpha (CS × a1+ PL × a2), wherein a1 and a2 are both proportionality coefficients, a1 is more than a2 and more than 0, alpha is an error correction factor and is 1.23 in value, and the word segment division is expressed by dividing words and words in the text under a semantic currency condition;
step TT 3: then, the keyword corresponding to the word key coefficient with the highest value in the query text is marked as an extraction keyword, the extraction keyword is compared with the keyword text of each block in the storage unit, if the extraction keyword is consistent with the keyword text of the block, the corresponding block is judged to be a preselected block, otherwise, the corresponding block is judged to be an excluded block;
step TT 4: and then obtaining the vehicle provided by the user and comparing the vehicle with the vehicle information in the preselected block, if the information is consistent, marking the corresponding preselected block as a selected block, setting a mobile phone terminal network of the corresponding user as a white list of the selected block, simultaneously setting query interval duration, and if the information is inconsistent, generating a re-extraction signal and re-extracting the data.
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