CN112422892B - Working method for image processing through mass building data of Internet of things - Google Patents
Working method for image processing through mass building data of Internet of things Download PDFInfo
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- CN112422892B CN112422892B CN202011097720.6A CN202011097720A CN112422892B CN 112422892 B CN112422892 B CN 112422892B CN 202011097720 A CN202011097720 A CN 202011097720A CN 112422892 B CN112422892 B CN 112422892B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y10/00—Economic sectors
- G16Y10/30—Construction
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
- H04L9/3236—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
- H04L9/3239—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
Abstract
The invention provides a working method for processing images through mass building data of the Internet of things, which comprises the following steps that a 5G data receiving and transmitting end of an m 5G unit is connected with a 5G data receiving and transmitting end of an m controller; the video image data output end of the mth camera module is connected with the video image data input end of the mth controller, and the data storage end of the mth controller is connected with the data storage end of the mth storage module; the video camera starting end of the mth controller is connected with the video image starting end of the mth camera module; after the M ' controller works according to the M ' camera module work command sent by the cloud server, the M ' is 1,2,3, the. The video image data stored in the m' storage module are transmitted to the cloud server for storage through the selected channel, and the video image data can be uploaded to the cloud server according to the selected channel, and are stored in the cloud server after the correctness of the video image data is verified, so that monitoring data can be conveniently searched in the future.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a working method for processing images through mass building data of the Internet of things.
Background
With the continuous progress of society, the concept of safe production is deeply concentrated, and the requirement of people on safe production is higher and higher. The building industry is an industry with a lot of safety accidents, and especially how to ensure the personal safety of constructors when equipment materials are hoisted, and the safety of properties such as building materials, equipment and the like on a construction site are the first matters concerned by construction units. The video monitoring system is mainly composed of camera shooting, transmission, control, display and record registration 5. Video monitoring systems are commonly used in high-rise building construction. Patent application No. 2017201582028, entitled "video monitoring system for high-rise building construction", discloses including a camera, a starting device for opening and closing a power supply circuit of the camera and outputting a starting signal is coupled to the camera, a lightning protection triggering device for receiving the starting signal and outputting a triggering signal is coupled to the starting device, an indicating device for receiving the lightning protection triggering signal and responding to the lightning protection triggering signal to realize indication is coupled to the lightning protection triggering device, a lightning protection device for lightning protection is also coupled to the camera, and a cut-off device breaking device for protecting the camera to realize cut-off of the power supply circuit of the camera is also coupled to the camera; when the camera is in high voltage or is in lightning stroke, the cutoff device breaks a power supply loop of the camera through overheating, the lightning protection device performs discharge protection on the camera, and the indicating device is not on.
Disclosure of Invention
The invention aims to at least solve the technical problems in the prior art, and particularly creatively provides a working method for processing images through mass building data of the Internet of things.
In order to achieve the above object, the present invention provides an image processing system through internet of things mass building data, including M video cameras installed at various places on a building site, where M is a positive integer greater than or equal to 2, and is respectively a 1 st video camera, a 2 nd video camera, a 3 rd video camera, … …, and an M video camera, where the M video camera includes an M camera module, an M controller, an M wireless connection module, and an M storage module, where M is a positive integer less than or equal to M, and the M wireless connection module includes one or any combination of an M WiFi unit, an M NB-IOT unit, an M4G unit, and an M5G unit;
the WiFi data transceiving end of the mth WiFi unit is connected with the WiFi data transceiving end of the mth controller; the NB-IOT data transceiving end of the mth NB-IOT unit is connected with the NB-IOT data transceiving end of the mth controller; the 4G data transceiving end of the m 4G unit is connected with the 4G data transceiving end of the m controller; the 5G data transceiving end of the m 5G unit is connected with the 5G data transceiving end of the m controller; the video image data output end of the mth camera module is connected with the video image data input end of the mth controller, and the data storage end of the mth controller is connected with the data storage end of the mth storage module; the video camera starting end of the mth controller is connected with the video image starting end of the mth camera module;
the cloud server is further included, and after the M ' controller works according to the M ' camera module work command sent by the cloud server, M ' is 1,2, 3; and transmitting the video image data stored on the m' storage module to a cloud server for storage through a selected channel, wherein the video image stored on the cloud server comprises one or any combination of a video shooting starting time, a video shooting ending time and a position.
In a preferred embodiment of the present invention, the video camera is a 360 ° rotation video camera.
The invention also provides a working method for processing the image through the mass building data of the Internet of things, which comprises the following steps:
s1, operating the video camera device;
s2, transmitting the video image shot by the video camera device to a cloud server through a selected channel; deleting the video image data which is not uploaded again;
s3, the cloud server verifies the correctness of the video image:
if the verification fails, uploading part or all of the video image data again;
and if the verification is passed, the video image is stored on the cloud server.
In a preferred embodiment of the invention, the cloud server controls the video camera device to work according to the intelligent mobile terminal worn by the construction worker, and shoots the video image data of the construction worker.
In a preferred embodiment of the invention, the cloud server controls the video camera device to work according to the intelligent mobile terminal worn by the construction worker, and shoots the video image data of the construction worker.
In a preferred embodiment of the present invention, step S2 includes the following steps:
s21, dividing the storage video stored on the mth storage module into K storage sub-videos according to the time sequence of the storage video, wherein K is a positive integer greater than or equal to 2 and is respectively a 1 st storage sub-video, a 2 nd storage sub-video, a 3 rd storage sub-video, … … and a Kth storage sub-video;
s22, carrying out hash function operation on the stored video, the 1 st sub-image of the video, the 2 nd sub-image of the video, the 3 rd sub-image of the video, … … and the Kth sub-image of the video in the step S21 in sequence to respectively obtain a video hash value, a 1 st value of the video hash, a 2 nd value of the video hash, a 3 rd value of the video hash, … … and a Kth value of the video hash in sequence;
S s ＝H<s>，
wherein H < > represents a hash function using one of MD5, SHA-1, SHA-384, SHA-512;
s∈S，S＝{s 0 ,s 1 ,s 2 ,s 3 ,...,s K }，s 0 representing stored video, s k Represents the kth sub-picture of the video, K being 1,2, 3.
S represents a video to be processed, and S represents a video set to be processed;
S s representing a hash value obtained after the video to be processed is subjected to hash function operation; wherein
A video hash value;
s23, the video hash value obtained in the step S22
Video hash 1 st value
Video hash 2 nd value
Video hash 3 rd value
… … video Hash Kth value
And video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
Corresponding video sub-image No. 1, video sub-image No. 2, video sub-image No. 3, … …, viewAnd uploading the Kth sub-image to a cloud server.
In a preferred embodiment of the present invention, the method for uploading the data in step S23 to the cloud server and selecting the channel thereof includes the following steps:
s231, acquiring the communication quality of network channels, wherein the network channels comprise a network 1 st channel, a network 2 nd channel, a network 3 rd channel and a network C th channel; c is the total number of channels for communication between the cloud server and the video camera device;
communication quality ComQ of c channel of network c The calculation method comprises the following steps:
wherein, ComQ c Means for indicating a network c channel communication quality value; c is 1,2,3,. cndot.c;
PLR c representing the packet loss rate of the c channel of the network;
lg represents the base 10 logarithm;
e represents a natural base number;
s232, sequentially arranging the communication quality value of the 1 st channel, the communication quality value of the 2 nd channel, the communication quality value of the 3 rd channel, … … and the communication quality value of the C th channel in sequence; and selecting the channel corresponding to the first channel in the sequence as the selected channel.
In a preferred embodiment of the present invention, step S3 includes the following steps:
s31, the video images received by the cloud server are respectively the 1 st video image, the 2 nd video image, the 3 rd video image, the … … and the Kth video image; k is a positive integer greater than or equal to 2;
with the 1 st video image corresponding to the 1 st value of the video hash
2 nd video image corresponds to video hash 2 nd value
3 rd video image corresponds to video hash 3 rd value
… …, Kth video image corresponds to video hash Kth value
S32, carrying out hash function operation on the 1 st video image, the 2 nd video image, the 3 rd video image, … … and the Kth video image in the step S31 in sequence, wherein the hash function operation comprises a hash function of one of MD5, SHA-1, SHA-384 and SHA-512, and respectively obtaining a cloud hash 1 st value, a cloud hash 2 nd value, a cloud hash 3 rd value, … … and a cloud hash Kth value in sequence;
judging k value of cloud hash and k value of video hash
Whether or not they are the same:
if the k value of the cloud hash and the k value of the video hash
If the values are the same, the cloud server sends the k value of the deleted video hash to the video camera device of the cloud server
The controller hashes the kth value of its video with the corresponding kth store sub-video command
Deleting the corresponding kth storage sub-video, and reducing the storage space occupation of a storage module on the video camera device; when the cloud hash value 1 and the video hash value 1 are used
Likewise, cloud hash 2 nd value and video hash 2 nd value
Similarly, cloud hash value 3 and video hash value 3
Similarly, … …, cloud hash Kth value and video hash Kth value
The same; executing the next step;
if the k value of the cloud hash and the k value of the video hash
If not, the cloud server requests the video camera device to send the k value of the video hash
The corresponding kth sub-image of the video; re-verifying;
s33, splicing the 1 st video image, the 2 nd video image, the 3 rd video image, the … … th video image and the Kth video image together according to the time sequence to obtain a cloud video image;
performing hash function operation on the cloud video image to obtain a cloud hash value;
s34, determining whether the cloud hash value is consistent with the video hash value received:
if the cloud hash value is consistent with the video hash value received by the cloud server, storing the obtained cloud video image in a cloud server;
and if the cloud hash value is not consistent with the video hash value received by the cloud hash value, splicing again.
In a preferred embodiment of the present invention, the method further includes step S4, where the video image stored on the cloud server includes one or any combination of a video capture start time, a video capture end time, and a location; the video shooting starting time or/and the video shooting ending time comprise one or any combination of year, month, day, time, minute and second; data query is facilitated.
In summary, due to the adoption of the technical scheme, the video images can be uploaded to the cloud server in times according to the selected channel, and the video images are stored in the cloud server after the correctness of the video images is verified, so that the monitoring data can be conveniently searched in the future.
Additional aspects and advantages of the invention 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 invention.
Drawings
The above and/or additional aspects and advantages of the present invention 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 a schematic block diagram of the connection of the present invention.
FIG. 2 is a block diagram illustrating the flow of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, 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 accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
The invention provides an image processing system through mass building data of the Internet of things, which comprises M video cameras arranged at each position on a building site, wherein the video cameras are 360-degree rotary video cameras, and the M video cameras are connected with a video processing system through a network; the M is a positive integer greater than or equal to 2 and is respectively a 1 st video camera device, a 2 nd video camera device, a 3 rd video camera device, … … and an Mth video camera device, the Mth video camera device comprises an Mth camera module, an Mth controller, an Mth wireless connection module and an Mth storage module, the M is a positive integer less than or equal to M, and the Mth wireless connection module comprises one or any combination of an Mth WiFi unit, an Mth NB-IOT unit, an Mth 4G unit and an Mth 5G unit;
the WiFi data receiving and transmitting end of the mth WiFi unit is connected with the WiFi data receiving and transmitting end of the mth controller; the NB-IOT data transceiving end of the mth NB-IOT unit is connected with the NB-IOT data transceiving end of the mth controller; the 4G data transceiving end of the m 4G unit is connected with the 4G data transceiving end of the m controller; the 5G data transceiving end of the m 5G unit is connected with the 5G data transceiving end of the m controller; the video image data output end of the mth camera module is connected with the video image data input end of the mth controller, and the data storage end of the mth controller is connected with the data storage end of the mth storage module; the video camera starting end of the mth controller is connected with the video image starting end of the mth camera module;
the cloud server is further included, and after the M ' controller works according to the M ' camera module work command sent by the cloud server, M ' is 1,2, 3; and transmitting the video image data stored on the m' storage module to a cloud server for storage through a selected channel, wherein the video image stored on the cloud server comprises one or any combination of a video shooting starting time, a video shooting ending time and a position. In this embodiment, the data storage device further comprises an mth compression module, wherein a compressed data input end of the mth compression module is connected with a compressed data output end of the mth storage module; and compressing the video image data stored on the mth storage module by the mth compression module, and then sending the video image data to the cloud server for storage through the mth wireless connection module.
The invention also provides a working method for processing images through the mass building data of the Internet of things, which comprises the following steps as shown in FIG. 2:
s1, controlling the video camera device to work according to the intelligent mobile terminal worn by the construction worker;
s2, transmitting the video image shot by the video camera device to a cloud server through a selected channel;
s3, the cloud server verifies the correctness of the video image:
if the verification fails, uploading part or all of the video image data again; deleting video image data which are not uploaded again;
and if the verification is passed, the video image is stored on the cloud server.
In a preferred embodiment of the present invention, the method further includes step S4, where the video image stored on the cloud server includes one or any combination of the video shooting start time, the video shooting end time, and the location; the video shooting starting time or/and the video shooting ending time comprise one or any combination of year, month, day, time, minute and second; data query is facilitated. The format of the video shooting starting time (video shooting ending time) is ABCD.EF.GH.IJ.KL.MN, wherein the ABCD is 2020-9999, the EF is 01-12, the GH is 01-31, the IJ is 00-23, the KL is 00-59, and the MN is 00-59. Such as the video photographing start time 2020.01.01.01.01.01 and the video photographing end time 2020.01.02.02.02.02.
In a preferred embodiment of the invention, the cloud server controls the video camera device to work according to the intelligent mobile terminal worn by the construction worker, and shoots the video image data of the construction worker.
In a preferred embodiment of the present invention, step S1 includes the following steps:
s11, the cloud server collects the positions of construction workers according to the intelligent mobile terminals worn by the construction workers;
the calculation method of the position of the construction worker comprises the following steps:
wherein (x) 0 ,y 0 ,z 0 ) Three-dimensional coordinate values representing positions where construction workers are located;
(X 1 ,Y 1 ,Z 1 ) Representing three-dimensional position coordinates of a first transceiving tower of the signal;
(X 2 ,Y 2 ,Z 2 ) Representing the three-dimensional position coordinates of the second transceiving tower;
(X 3 ,Y 3 ,Z 3 ) Representing the three-dimensional position coordinates of the second transceiving tower;
zeta represents the error rate between the first receiving and sending tower and the intelligent mobile terminal;
zeta represents the error rate between the second receiving and sending tower and the intelligent mobile terminal;
ζ represents an error rate between the third transceiving tower and the intelligent mobile terminal;
t 0,i 、t 0,j 、t 0,p indicating the time when the intelligent mobile terminal sends the ranging;
t i ' represents the moment when the intelligent mobile terminal sends a ranging signal and a first transceiving tower receives the ranging signal; i represents the receiving times of a first transceiving tower of the signal;
t j ' represents the time when the intelligent mobile terminal sends the ranging signal to the second transceiving tower to receive the ranging; j represents the receiving times of the second transceiving tower;
t p ' represents the time when the intelligent mobile terminal sends a signal after ranging to a third transceiving tower to receive ranging; p represents the receiving times of a third transceiving tower;
lambda represents the transceiving transmission wavelength of the intelligent mobile terminal;
f represents the transceiving transmission frequency of the intelligent mobile terminal;
s12, the cloud server controls the corresponding video camera device to shoot the image data of the construction worker according to the position of the construction worker:
wherein (x) ψ ,y ψ ,z ψ ) Position coordinates representing the ψ -th video camera; ψ ═ 1,2,3,. said, M;
(x 0 ,y 0 ,z 0 ) Three-dimensional coordinate values representing positions of construction workers;
d ψ indicating the distance of the construction worker from the psi video camera;
d＝{d 1 ,d 2 ,d 3 ,...,d M d represents the distance between a construction worker and all the video camera devices;
selecting the minimum distance d min Corresponding video camera psi min Controlling the video camera psi min Video image data of construction workers are shot.
In a preferred embodiment of the present invention, step S2 includes the following steps:
s21, dividing the storage video stored on the mth storage module into K storage sub-videos according to the time sequence of the storage video, wherein K is a positive integer greater than or equal to 2 and is respectively a 1 st storage sub-video, a 2 nd storage sub-video, a 3 rd storage sub-video, … … and a Kth storage sub-video;
s22, carrying out hash function operation on the stored video, the 1 st sub-image of the video, the 2 nd sub-image of the video, the 3 rd sub-image of the video, … … and the Kth sub-image of the video in the step S21 in sequence to respectively obtain a video hash value, a 1 st value of the video hash, a 2 nd value of the video hash, a 3 rd value of the video hash, … … and a Kth value of the video hash in sequence;
S s ＝H<s>，
wherein, the invention H < > represents a hash function using SHA-1; a hash function of one of MD5, SHA-384, SHA-512 may also be employed.
s∈S，S＝{s 0 ,s 1 ,s 2 ,s 3 ,...,s K }，s 0 Representing stored video, s k Represents the kth sub-picture of the video, K being 1,2, 3.
S represents a video to be processed, and S represents a video set to be processed;
S s representing a hash value obtained after the video to be processed is subjected to hash function operation; wherein
A video hash value;
s23, the video hash value obtained in the step S22
Video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
And video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
And uploading the corresponding 1 st sub-image, 2 nd sub-image, 3 rd sub-image, … … and Kth sub-image of the video to a cloud server.
In a preferred embodiment of the present invention, the method for uploading the data in step S23 to the cloud server and selecting the channel thereof includes the following steps:
s231, acquiring the communication quality of network channels, wherein the network channels comprise a network 1 st channel, a network 2 nd channel, a network 3 rd channel and a network C th channel; c is the total number of channels for communication between the cloud server and the video camera device;
communication quality ComQ of c channel of network c The calculation method comprises the following steps:
Wherein, ComQ c Indicating network c channel communicationA quality value; c is 1,2,3,. cndot.c;
PLR c representing the packet loss rate of the c channel of the network;
χ c indicating the data flow size of the c channel of the network;
η represents the network congestion rate;
ε represents the adjustment factor;
lg represents the base 10 logarithm;
e represents a natural base number;
s232, sequentially arranging the 1 st channel communication quality value, the 2 nd channel communication quality value, the 3 rd channel communication quality value, … … and the C th channel communication quality value in sequence; and selecting the channel corresponding to the first channel in the sequence as the selected channel.
In a preferred embodiment of the present invention, step S3 includes the following steps:
s31, the video images received by the cloud server are respectively the 1 st video image, the 2 nd video image, the 3 rd video image, the … … and the Kth video image; k is a positive integer greater than or equal to 2;
with the 1 st video image corresponding to the 1 st value of the video hash
2 nd video image corresponds to video hash 2 nd value
3 rd video image corresponds to video hash 3 rd value
… …, Kth video image corresponds to video hash Kth value
S32, conducting SHA-1 hash function operation on the 1 st video image, the 2 nd video image, the 3 rd video image, … … and the Kth video image in the step S31 in sequence, or conducting a hash function operation on one of MD5, SHA-384 and SHA-512 to obtain a cloud hash 1 st value, a cloud hash 2 nd value, a cloud hash 3 rd value, … … and a cloud hash Kth value respectively in sequence;
judging k value of cloud hash and k value of video hash
Whether or not they are the same:
if the k value of the cloud hash and the k value of the video hash
If the values are the same, the cloud server sends the k value of the deleted video hash to the video camera device of the cloud server
The controller hashes the kth value of its video with the corresponding kth store sub-video command
Deleting the corresponding kth storage sub-video, and reducing the storage space occupation of a storage module on the video camera device; when the cloud hash value 1 and the video hash value 1 are used
Likewise, cloud hash 2 nd value and video hash 2 nd value
Similarly, cloud hash value 3 and video hash value 3
Similarly, … …, cloud hash Kth value and video hash Kth value
The same; executing the next step;
if the k value of the cloud hash and the k value of the video hash
If not, the cloud server requests the video camera device to send the k value of the video hash
The corresponding kth sub-image of the video; re-verifying;
s33, splicing the 1 st video image, the 2 nd video image, the 3 rd video image, the … … th video image and the Kth video image together according to the time sequence to obtain a cloud video image;
performing SHA-1 hash function operation on the cloud video image, or performing one of MD5, SHA-384 and SHA-512 hash functions to obtain a cloud hash value;
s34, determining whether the cloud hash value is consistent with the video hash value received:
if the cloud hash value is consistent with the video hash value received by the cloud server, storing the obtained cloud video image in a cloud server;
and if the cloud hash value is not consistent with the video hash value received by the cloud hash value, splicing again.
In a preferred embodiment of the present invention, step S2 is to upload the video images captured by the video camera to the cloud server after the video images are compressed in several times. The step S2 includes the following steps:
s21, dividing the storage video stored on the mth storage module into K storage sub-videos according to the time sequence of the storage video, wherein K is a positive integer greater than or equal to 2 and is respectively a 1 st storage sub-video, a 2 nd storage sub-video, a 3 rd storage sub-video, … … and a Kth storage sub-video;
s22, sequentially inputting the 1 st sub-image, the 2 nd sub-image, the 3 rd sub-image, … … and the Kth sub-image of the video in the step S21 into an m-th compression module for compression, wherein the compression mode is not limited to the video compression method based on the deep neural network in the patent application No. 2017107582416, and the 1 st compressed video, the 2 nd compressed video, the 3 rd compressed video, … … and the Kth compressed video are sequentially obtained;
s23, performing hash function operation on the stored video in the step S21 and the 1 st, 2 nd, 3 rd, … … th and Kth compressed videos in the step S22 in sequence to respectively obtain a video hash value, a video hash 1 st value, a video hash 2 nd value, a video hash 3 rd value, … … th and a video hash Kth value in sequence;
S s ＝H<s>，
wherein, the invention H < > represents a hash function using SHA-1; a hash function of one of MD5, SHA-384, SHA-512 may also be employed.
s∈S，S＝{s 0 ,s 1 ,s 2 ,s 3 ,...,s K }，s 0 Representing stored video, s k Represents the kth sub-picture of the video, K being 1,2, 3.
S represents a video to be processed, and S represents a video set to be processed;
S s representing a hash value obtained after the video to be processed is subjected to hash function operation; wherein
A video hash value;
s24, the video hash value obtained in the step S23
Video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
And video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
Uploading the corresponding 1 st compressed video, 2 nd compressed video, 3 rd compressed video, … … and Kth compressed video to a cloud server.
In a preferred embodiment of the present invention, step S3 includes the following steps:
s31, the video images received by the cloud server are respectively the 1 st video image, the 2 nd video image, the 3 rd video image, the … … and the Kth video image; k is a positive integer greater than or equal to 2;
its 1 st video image corresponds to the 1 st value of the video hash
2 nd video image corresponds to video hash 2 nd value
3 rd video image corresponds to video hash 3 rd value
… …, Kth video image corresponds to video hash Kth value
S32, SHA-1 hash function operation is sequentially carried out on the 1 st video image, the 2 nd video image, the 3 rd video image, … … and the Kth video image in the step S31, and a cloud hash 1 value, a cloud hash 2 value, a cloud hash 3 value, … … and a cloud hash Kth value can be respectively and sequentially obtained through a hash function of one of MD5, SHA-384 and SHA-512;
judging k value of cloud hash and k value of video hash
Whether or not they are the same:
if the k value of the cloud hash and the k value of the video hash
If the values are the same, the cloud server sends the k value of the deleted video hash to the video camera device of the cloud server
The controller hashes the kth value of its video with the corresponding kth store sub-video command
Deleting the corresponding kth stored sub-video, and reducing the storage space occupation of a storage module on the video camera device; when the cloud hash value 1 and the video hash value 1 are used
Likewise, cloud hash 2 nd value and video hash 2 nd value
Similarly, cloud hash value 3 and video hash value 3
Similarly, … …, cloud hash Kth value and video hash Kth value
The same; executing the next step;
if the k value of the cloud hash and the k value of the video hash
If not, the cloud server requests the video camera device to send the k value of the video hash
The corresponding kth sub-image of the video; re-verifying;
s33, decompressing the 1 st video image, the 2 nd video image, the 3 rd video image, the … … and the Kth video image to respectively obtain a 1 st decompressed video image, a 2 nd decompressed video image, a 3 rd decompressed video image, … … and a Kth decompressed video image in sequence;
s34, decompressing the 1 st video image, the 2 nd video image, the 3 rd video image, the … … th video image and the Kth video image to respectively obtain a 1 st decompressed video image, a 2 nd decompressed video image, a 3 rd decompressed video image, … … and a Kth decompressed video image which are spliced together according to the time sequence to obtain a cloud video image;
carrying out SHA-1 hash function operation on the cloud video image to obtain a cloud hash value;
s34, determining whether the cloud hash value is consistent with the video hash value received:
if the cloud hash value is consistent with the video hash value received by the cloud server, storing the obtained cloud video image in a cloud server;
and if the cloud hash value is not consistent with the video hash value received by the cloud hash value, splicing again.
In a preferred embodiment of the present invention, step S2 includes the following steps:
s21, dividing the storage video stored on the mth storage module into K storage sub-videos according to the time sequence of the storage video, wherein K is a positive integer greater than or equal to 2 and is respectively a 1 st storage sub-video, a 2 nd storage sub-video, a 3 rd storage sub-video, … … and a Kth storage sub-video;
s22, carrying out hash function operation on the stored video, the 1 st sub-image of the video, the 2 nd sub-image of the video, the 3 rd sub-image of the video, … … and the Kth sub-image of the video in the step S21 in sequence to respectively obtain a video hash value, a 1 st value of the video hash, a 2 nd value of the video hash, a 3 rd value of the video hash, … … and a Kth value of the video hash in sequence;
S s ＝H<s>，
wherein, the invention H < > represents a hash function using SHA-1; a hash function of one of MD5, SHA-384, SHA-512 may also be employed.
s∈S，S＝{s 0 ,s 1 ,s 2 ,s 3 ,...,s K }，s 0 Representing stored video, s k Represents the kth sub-picture of the video, K being 1,2, 3.
S represents a video to be processed, and S represents a video set to be processed;
S s representing a hash value obtained after the video to be processed is subjected to hash function operation; wherein
A video hash value;
s23, inputting the sub-image No. 1, sub-image No. 2, sub-image No. 3, sub-image No. … … and sub-image No. K of the video in the step S21 into the m compression module for compression, and respectively obtaining the 1 st compressed video, the 2 nd compressed video, the 3 rd compressed video, the … … and the K th compressed video in sequence;
s24, conducting SHA-1 hash function operation on the 1 st compressed video, the 2 nd compressed video, the 3 rd compressed video, … … and the Kth compressed video in the step S23 in sequence, and respectively obtaining a 1 st value of the video compression hash, a 2 nd value of the video compression hash, a 3 rd value of the video compression hash, … … and a Kth value of the video compression hash in sequence; deleting the 1 st sub-image, the 2 nd sub-image, the 3 rd sub-image, … … and the Kth sub-image of the video;
s25, the video hash value obtained in the step S22
Video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
And uploading the 1 st value of the video compression hash, the 2 nd value of the video compression hash, the 3 rd value of the video compression hash, … …, the K th value of the video compression hash, and the 1 st value of the video compression hash, the 2 nd value of the video compression hash, the 3 rd value of the video compression hash, … …, the 1 st compressed video, the 2 nd compressed video, the 3 rd compressed video, … … and the K th compressed video corresponding to the K th value of the video compression hash to a cloud server.
In a preferred embodiment of the present invention, step S3 includes the following steps:
s31, the video images received by the cloud server are respectively the 1 st video image, the 2 nd video image, the 3 rd video image, the … … and the Kth video image; k is a positive integer greater than or equal to 2;
the 1 st video image corresponds to a 1 st value of a video compression hash, the 2 nd video image corresponds to a 2 nd value of the video compression hash, the 3 rd video image corresponds to a 3 rd value of the video compression hash, … …, and the Kth video image corresponds to a Kth value of the video compression hash;
s32, conducting SHA-1 hash function operation on the 1 st video image, the 2 nd video image, the 3 rd video image, … … and the Kth video image in the step S31 in sequence, and obtaining a cloud hash 1 st value, a cloud hash 2 nd value, a cloud hash 3 rd value, … … and a cloud hash Kth value in sequence respectively;
judging whether the k-th value of the cloud hash is the same as the k-th value of the video compression hash:
if the k value of the cloud hash is the same as the k value of the video compression hash, the cloud server sends a k compressed video command corresponding to the k value of the video compression hash to the video camera device of the cloud server, and the controller deletes the k compressed video corresponding to the k value of the video compression hash of the cloud server, so that the storage space occupation amount of a storage module on the video camera device is reduced; when the 1 st value of the cloud hash is the same as the 1 st value of the video compression hash, the 2 nd value of the cloud hash is the same as the 2 nd value of the video compression hash, the 3 rd value of the cloud hash is the same as the 3 rd value of the video compression hash, … …, the K th value of the cloud hash is the same as the K th value of the video compression hash; executing the next step;
if the k value of the cloud hash is different from the k value of the video compression hash, the cloud server requests the video camera device to send a k compressed video corresponding to the k value of the video compression hash; re-verifying;
s33, sequentially decompressing the 1 st video image, the 2 nd video image, the 3 rd video image, … … and the K th video image in the step S31 to respectively obtain a 1 st decompressed video image, a 2 nd decompressed video image, a 3 rd decompressed video image, … … and a K th decompressed video image in sequence;
s34, sequentially carrying out SHA-1 hash function operation on the 1 st decompressed video image, the 2 nd decompressed video image, the 3 rd decompressed video image, … … and the Kth decompressed video image obtained in the step S33, and sequentially obtaining a 1 st decompressed hash value, a 2 nd decompressed hash value, a 3 rd decompressed hash value, … … and a Kth decompressed hash value respectively;
verifying whether the kth decompressed hash value is the same as the video hash kth value:
if the kth decompression hash value is the same as the kth value of the video hash, the cloud server deletes the kth decompression video image; when the 1 st decompression hash value is the same as the 1 st value of the video hash, the 2 nd decompression hash value is the same as the 2 nd value of the video hash, and the 3 rd decompression hash value is the same as the 3 rd value of the video hash, … …, the Kth decompression hash value is the same as the Kth value of the video hash; executing the next step;
if the kth decompression hash value is different from the kth value of the video hash, the kth video image is decompressed again and then verified;
s35, splicing the 1 st decompressed video image, the 2 nd decompressed video image, the 3 rd decompressed video image, the … … th decompressed video image and the Kth decompressed video image together according to the time sequence to obtain a cloud video image;
carrying out SHA-1 hash function operation on the cloud video image to obtain a cloud hash value;
s36, determining whether the cloud hash value is consistent with the video hash value received:
if the cloud hash value is consistent with the video hash value received by the cloud server, storing the obtained cloud video image in a cloud server;
and if the cloud hash value is not consistent with the video hash value received by the cloud hash value, splicing again.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (7)
1. A system for processing images through mass building data of the Internet of things comprises M video cameras arranged at each position on a building site, wherein M is a positive integer larger than or equal to 2 and is respectively a 1 st video camera, a 2 nd video camera, a 3 rd video camera, … … th video camera and an Mth video camera, and the system is characterized in that the Mth video camera comprises an Mth camera module, an Mth controller, an Mth wireless connection module and an Mth storage module, wherein M is a positive integer smaller than or equal to M, and the Mth wireless connection module comprises one or any combination of an Mth WiFi unit, an Mth NB-IOT unit, an Mth 4G unit and an Mth 5G unit;
the WiFi data receiving and transmitting end of the mth WiFi unit is connected with the WiFi data receiving and transmitting end of the mth controller; the NB-IOT data transceiving end of the mNB-IOT unit is connected with the NB-IOT data transceiving end of the m controller; the 4G data transceiving end of the m 4G unit is connected with the 4G data transceiving end of the m controller; the 5G data transceiving end of the m 5G unit is connected with the 5G data transceiving end of the m controller; the video image data output end of the mth camera module is connected with the video image data input end of the mth controller, and the data storage end of the mth controller is connected with the data storage end of the mth storage module; the video camera starting end of the mth controller is connected with the video image starting end of the mth camera module;
the cloud server is further included, and after the M ' controller works according to the M ' camera module work command sent by the cloud server, M ' is 1,2, 3; transmitting the video image data stored on the m' storage module to a cloud server for storage through a selected channel, wherein the video image stored on the cloud server comprises one or any combination of video shooting starting time, video shooting ending time and position; the method for selecting the channel comprises the following steps:
s231, acquiring the communication quality of network channels, wherein the network channels comprise a network 1 st channel, a network 2 nd channel, a network 3 rd channel and a network C th channel; c is the total number of channels for communication between the cloud server and the video camera device;
c-th message of its networkCommunication quality ComQ of a channel c The calculation method comprises the following steps:
wherein, ComQ c Means for indicating a network c channel communication quality value; c is 1,2,3,. cndot.c;
PLR c representing the packet loss rate of the c channel of the network;
lg represents the base 10 logarithm;
e represents a natural base number;
η represents the network congestion rate;
ε represents the adjustment coefficient;
s232, sequentially arranging the communication quality value of the 1 st channel, the communication quality value of the 2 nd channel, the communication quality value of the 3 rd channel, … … and the communication quality value of the C th channel in sequence; and selecting the channel corresponding to the first channel in the sequence as the selected channel.
2. The system for processing the images through the mass building data of the internet of things according to claim 1, wherein the video camera is a 360-degree rotating video camera.
3. A working method for carrying out image processing on massive building data of the Internet of things is characterized by comprising the following steps:
s1, operating the video camera device;
s2, transmitting the video image shot by the video camera device to a cloud server through a selected channel; the method for selecting the channel comprises the following steps:
s231, acquiring the communication quality of network channels, wherein the network channels comprise a network 1 st channel, a network 2 nd channel, a network 3 rd channel and a network C th channel; c is the total number of channels for communication between the cloud server and the video camera device;
communication quality ComQ of c channel of network c The calculation method comprises the following steps:
wherein, ComQ c Means for indicating a network c channel communication quality value; c is 1,2,3,. cndot.c;
PLR c representing the packet loss rate of the c channel of the network;
lg represents the base 10 logarithm;
e represents a natural base number;
η represents the network congestion rate;
ε represents the adjustment factor;
s232, sequentially arranging the communication quality value of the 1 st channel, the communication quality value of the 2 nd channel, the communication quality value of the 3 rd channel, … … and the communication quality value of the C th channel in sequence; selecting a channel corresponding to the first channel in the sequence as a selected channel;
s3, the cloud server verifies the correctness of the video image:
if the verification fails, uploading part or all of the video image data again; deleting the video image data which is not uploaded again;
and if the verification is passed, the video image is stored on the cloud server.
4. The working method for image processing through mass building data of the internet of things according to claim 3, wherein the cloud server controls the video camera device to work according to the intelligent mobile terminal worn by a construction worker, and shoots video image data of the construction worker.
5. The working method for image processing through mass building data of the internet of things according to claim 3, wherein the step S2 includes the following steps:
s21, dividing the storage video stored on the mth storage module into K storage sub-videos according to the time sequence of the storage video, wherein K is a positive integer greater than or equal to 2 and is respectively a 1 st storage sub-video, a 2 nd storage sub-video, a 3 rd storage sub-video, … … and a Kth storage sub-video;
s22, carrying out hash function operation on the stored video, the 1 st sub-image of the video, the 2 nd sub-image of the video, the 3 rd sub-image of the video, … … and the Kth sub-image of the video in the step S21 in sequence to respectively obtain a video hash value, a 1 st value of the video hash, a 2 nd value of the video hash, a 3 rd value of the video hash, … … and a Kth value of the video hash in sequence;
S s ＝H<s>，
wherein H < > represents a hash function using one of MD5, SHA-1, SHA-384, SHA-512;
s∈S，S＝{s 0 ,s 1 ,s 2 ,s 3 ,...,s K }，s 0 representing stored video, s k Represents the kth sub-picture of the video, K being 1,2, 3.
S represents a video to be processed, and S represents a video set to be processed;
S s representing a hash value obtained after the video to be processed is subjected to hash function operation; wherein
A video hash value;
s23, the video hash value obtained in the step S22
Video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
And video hash 1 st value
Video hash 2 nd value
Video hash value 3
… … video Hash Kth value
And uploading the corresponding video sub-image No. 1, video sub-image No. 2, video sub-image No. 3, … … and video sub-image No. K to a cloud server.
6. The working method for image processing through mass building data of the internet of things according to claim 3, wherein the step S3 includes the following steps:
s31, the video images received by the cloud server are respectively the 1 st video image, the 2 nd video image, the 3 rd video image, the … … and the Kth video image; k is a positive integer greater than or equal to 2;
with the 1 st video image corresponding to the 1 st value of the video hash
2 nd video image corresponds to video hash 2 nd value
3 rd video image corresponds to video hash 3 rd value
… …, Kth video image corresponds to video hash Kth value
S32, carrying out hash function operation on the 1 st video image, the 2 nd video image, the 3 rd video image, … … and the Kth video image in the step S31 in sequence, wherein the hash function operation comprises a hash function of one of MD5, SHA-1, SHA-384 and SHA-512, and respectively obtaining a cloud hash 1 st value, a cloud hash 2 nd value, a cloud hash 3 rd value, … … and a cloud hash Kth value in sequence;
judging k value of cloud hash and k value of video hash
Whether or not they are the same:
if the k value of the cloud hash and the k value of the video hash
If the values are the same, the cloud server sends the k value of the deleted video hash to the video camera device of the cloud server
The controller hashes the kth value of its video with the corresponding kth store sub-video command
Deleting the corresponding kth storage sub-video, and reducing the storage space occupation of a storage module on the video camera device; when the cloud hash value 1 and the video hash value 1 are used
Likewise, cloud hash 2 nd value and video hash 2 nd value
Similarly, cloud hash value 3 and video hash value 3
Similarly, … …, cloud hash Kth value and video hash Kth value
The same; executing the next step;
if the k value of the cloud hash and the k value of the video hash
If not, the cloud server requests the video camera device to send the k value of the video hash
The corresponding kth sub-image of the video; re-verifying;
s33, splicing the 1 st video image, the 2 nd video image, the 3 rd video image, the … … th video image and the Kth video image together according to the time sequence to obtain a cloud video image;
performing hash function operation on the cloud video image to obtain a cloud hash value;
s34, determining whether the cloud hash value is consistent with the video hash value received:
if the cloud hash value is consistent with the video hash value received by the cloud server, storing the obtained cloud video image in a cloud server;
and if the cloud hash value is not consistent with the video hash value received by the cloud hash value, splicing again.
7. The working method for image processing through mass building data of the internet of things according to claim 3, further comprising a step S4, wherein the video image stored on the cloud server includes one or any combination of a video shooting start time, a video shooting end time, and a position; the video shooting starting time or/and the video shooting ending time comprise one or any combination of year, month, day, time, minute and second; data query is facilitated.
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