An intelligent management system based on massive image data

Abstract

The present invention relates to the field of data processing technology, and in particular to an intelligent management system based on massive image data, comprising: a receiver, a cloud database and a retrieval engine; the receiver obtains the monitoring image data interaction authority of the monitoring device, and after obtaining the monitoring image data interaction authority, receives the monitoring image data of the monitoring device in real time and sends it to the cloud database in real time; the cloud database obtains the monitoring image data fed back by the receiver in real time, identifies the monitoring parameters of the monitoring device from which the monitoring image data comes, and the present invention realizes the centralized reception of monitoring image data of multiple monitoring devices by obtaining the monitoring device authority, and further simplifies a large amount of monitoring image data into image data by setting and filtering logic of monitoring image data. Therefore, when the system end user has a tracking demand, based on the system, the retrieval target trend can be quickly retrieved in the massive image data according to the retrieval target uploaded by the system end user.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an intelligent management system based on massive image data. Background Art

[0002] The video and image library management requirements in safe city scenarios involve multiple aspects, including ensuring data transmission quality and stability to support the transmission of high-definition, real-time video streams; resolving compatibility issues to ensure smooth communication between multiple protocols and multiple devices; strengthening security measures to protect video and image data from leakage or tampering; and focusing on data standardization and consistency to achieve cross-platform and cross-system data sharing and exchange. In the face of massive amounts of data, efficient data storage and management mechanisms must be established. Finally, relevant laws, regulations, and privacy protection policies must be strictly adhered to to ensure the legality of technology applications and the protection of user privacy.

[0003] At present, as urban residents' awareness of anti-theft and safety has increased, most residents install surveillance equipment at their home entrances and other residential entrances to provide monitoring and protection. The images collected by these surveillance devices are likely to capture special images such as security incidents and arrest targets. These images are discovered through the speculation and tracking of investigators and are further retrieved and reviewed by investigators.

[0004] However, the process for investigators to access surveillance footage was inefficient, and the speculation and tracking stages also took a considerable amount of time;

[0005] To this end, we propose an intelligent management system based on massive image data. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides an intelligent management system based on massive image data, which solves the technical problems raised in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] An intelligent management system based on massive image data, comprising: a receiver, a cloud database and a search engine;

[0009] The receiver obtains the monitoring image data interaction permission of the monitoring device. After obtaining the monitoring image data interaction permission, it receives the monitoring image data of the monitoring device in real time and sends it to the cloud database in real time; the cloud database obtains the monitoring image data fed back by the receiver in real time, identifies the monitoring parameters of the monitoring device from which the monitoring image data comes, sets the monitoring image data screening logic based on the monitoring parameters of the monitoring device, applies the monitoring image data screening logic to perform picture frame screening on the monitoring image data, further stores the screened picture frames, and marks the picture frames in an identifiable manner; the search engine uploads the search target and search target attribute parameters in real time, confirms the search target group in the cloud database based on the search target attribute parameters, and further performs search of the search target in the search target group.

[0010] Furthermore, the receiver includes a protocol unit, a receiving module, and a forwarding module:

[0011] The protocol unit is used to access the monitoring device user terminal and request the monitoring device monitoring image data interaction permission. The receiving module is used to obtain the monitoring device monitoring image data interaction permission request result in the protocol unit and perform real-time monitoring image data reception operations on the authorized monitoring device. The forwarding module is used to forward the monitoring image data received in the receiving module to the cloud database;

[0012] Among them, the operation of accessing the monitoring device user terminal in the protocol unit and requesting the monitoring device monitoring image data interaction permission is to contact the monitoring device user terminal with a communication device and request the monitoring device monitoring image data interaction permission, or during the monitoring device installation stage, the monitoring device network access protocol includes the monitoring device monitoring image data interaction permission and is confirmed by the monitoring device user terminal.

[0013] Furthermore, after the protocol unit confirms the receiver and the monitoring device's authority to interact with monitoring image data, the monitoring device is deployed based on a fiber optic network, and receives the monitoring image data through a receiving module and transmits it to the receiver. When receiving the monitoring image data, the receiving module synchronously obtains the time and location information of the source monitoring device of the monitoring image data.

[0014] Furthermore, when forwarding the surveillance image data held in the receiver, the forwarding module synchronously sets a surveillance image data segmentation time domain, performs segmentation processing on the surveillance image data held in the receiver based on the set surveillance image data segmentation data, and further forwards the surveillance image data belonging to each time domain to the cloud database in sequence based on the time sequence;

[0015] Among them, the surveillance image data segmentation time domain set in the forwarding module is not less than five seconds and not more than fifteen seconds.

[0016] Furthermore, the cloud database includes an identification module, a screening module, and a storage module:

[0017] The identification module is used to receive the monitoring image data forwarded by the forwarding module and identify the monitoring parameters of the monitoring device from which the monitoring image data originates. The screening module is used to obtain the monitoring parameters of the monitoring device identified in the identification module, set the monitoring image data screening logic based on the monitoring parameters of the monitoring device, and perform frame screening on the monitoring image data of the monitoring device through the monitoring image data screening logic. The storage module is used to receive the remaining monitoring image data screened by the screening module and store the monitoring image data.

[0018] The monitoring image data identified in the identification module comes from the monitoring parameters of the health device, that is, the monitoring range of the monitoring device. The monitoring image data screening logic set in the screening module is:

[0019]

[0020] Where: S(α) is the estimated monitoring range of the monitoring device; d is the vertical distance from the monitoring device to the monitoring plane; f is the focal length of the monitoring device; p v 、p h S is the horizontal pixel span and vertical pixel span of any static object in the monitoring image data of the monitoring device; h 、S v P is the horizontal size and vertical size of the image sensor of the monitoring equipment; h 、P v is the number of horizontal and vertical pixels of the monitoring screen of the monitoring device; t is the time interval for picking up the frames in the monitoring image data; t0 is the base number of the picking time interval; λ is a constant;

[0021] After obtaining the frame picking time interval t in the surveillance image data, the surveillance image data is segmented based on t to obtain several groups of sub-surveillance image data, and the last group of frames in each sub-surveillance image data is selected as the screening result of the screening module.

[0022] Furthermore, the constant λ≥1, and the picking time interval base t0 is manually set by the system end user;

[0023] After the screening module runs and filters the picture frames, it synchronously performs dynamic target recognition in continuous frames, and the picture frames of the recognized dynamic targets are used as the final picture frame screening results of the screening module;

[0024] Among them, when the screening module identifies dynamic targets in continuous frames, it applies a background subtraction algorithm or a feature point tracking algorithm to identify dynamic targets.

[0025] Furthermore, the storage module is internally provided with submodules, including:

[0026] a marking unit for traversing the image frames stored in the storage module, obtaining the location information and time stamp of the monitoring device from which each image frame originated, marking each corresponding image frame based on the obtained location information and time stamp of the monitoring device from which the image frame originated, and controlling the storage module to perform differentiated storage on the internally stored image frames once based on the location information of the monitoring device and once based on the time period corresponding to the source time stamp;

[0027] The time period corresponding to the timestamp is in hours.

[0028] Furthermore, the search engine includes an upload module and a search unit:

[0029] The upload module is used to upload the search target and the search target attribute parameters, and use the search target attribute parameters to confirm the search target group in the cloud database. The search unit is used to obtain the search target group confirmed in the upload module and search for a picture frame containing a dynamic target similar to the search target in the search target group.

[0030] Among them, one or several groups of retrieval targets uploaded in the upload module contain image data of people, and the retrieval target attribute parameters include: retrieval target source location, retrieval target source timestamp, and the retrieval unit retrieves the picture frames containing dynamic targets similar to the retrieval targets and determines that the similarity is not less than 85%.

[0031] Furthermore, the search target group is composed of storage intervals divided into several groups of storage modules;

[0032] When the retrieval target group is determined, the retrieval target source position and the retrieval target source timestamp corresponding time period in the retrieval target attribute parameters are used to obtain a differentiated storage interval in the storage module that is the same as the retrieval target source position and the same as the retrieval target source timestamp corresponding time period, so as to differentiate each picture frame in the storage interval as an object for similarity comparison with the retrieval target, and further perform the retrieval operation.

[0033] Furthermore, the receiver, cloud database and search engine are interactively connected via a wireless network;

[0034] The receiver is internally connected to a protocol unit via a wireless network, and the receiver is interactively connected to a receiving module and a forwarding module via a wireless network;

[0035] The cloud database is interactively connected to the identification module, the screening module and the storage module via a wireless network, and the storage module is internally interactively connected to the marking unit via a wireless network;

[0036] The search engine is interactively connected with an upload module and a search unit via a wireless network.

[0037] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0038] The present invention provides an intelligent management system based on massive image data. During operation, the system obtains the authority of the monitoring equipment to realize the centralized reception of monitoring image data of multiple monitoring devices, and further condenses a large amount of monitoring image data into image data through the setting and screening processing of the monitoring image data screening logic. Therefore, when the system end user has a tracking demand, based on the system, the search target trend can be quickly retrieved from the massive image data according to the search target uploaded by the system end user, thereby improving the search target tracking efficiency of the system end user and bringing convenience to the tracking work of the system end user. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0040] Figure 1 It is a structural diagram of an intelligent management system based on massive image data;

[0041] Figure 2 This is an example diagram of an application example of the system in the present invention;

[0042] Figure 3 This is a diagram of an example application scenario and test environment of the system in the present invention. DETAILED DESCRIPTION

[0043] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0044] The present invention will be further described below with reference to the embodiments.

[0045] Example 1:

[0046] This embodiment is an intelligent management system based on massive image data, such as Figure 1 As shown, it includes: a receiver, a cloud database and a search engine;

[0047] The receiver obtains the monitoring image data interaction permission of the monitoring device. After obtaining the monitoring image data interaction permission, it receives the monitoring image data of the monitoring device in real time and sends it to the cloud database in real time;

[0048] The receiver includes a protocol unit, a receiving module, and a forwarding module:

[0049] The protocol unit is used to access the monitoring device user terminal and request the monitoring device monitoring image data interaction permission. The receiving module is used to obtain the monitoring device monitoring image data interaction permission request result in the protocol unit and perform real-time monitoring image data reception operations on the authorized monitoring device. The forwarding module is used to forward the monitoring image data received in the receiving module to the cloud database;

[0050] The operation of accessing the monitoring device user terminal and requesting the monitoring device monitoring image data interaction permission in the protocol unit is to contact the monitoring device user terminal with a communication device and request the monitoring device monitoring image data interaction permission, or during the monitoring device installation phase, the monitoring device network access agreement includes the monitoring device monitoring image data interaction permission and is confirmed by the monitoring device user terminal;

[0051] The cloud database obtains the monitoring image data fed back by the receiver in real time, identifies the monitoring parameters of the monitoring equipment from which the monitoring image data originates, sets the monitoring image data screening logic based on the monitoring parameters of the monitoring equipment, applies the monitoring image data screening logic to perform frame screening on the monitoring image data, further stores the screened frames, and marks the frames with identifiable marks;

[0052] The cloud database includes recognition module, screening module, and storage module:

[0053] The identification module is used to receive the monitoring image data forwarded by the forwarding module and identify the monitoring parameters of the monitoring device from which the monitoring image data originates. The screening module is used to obtain the monitoring parameters of the monitoring device identified in the identification module, set the monitoring image data screening logic based on the monitoring parameters of the monitoring device, and perform frame screening on the monitoring image data of the monitoring device through the monitoring image data screening logic. The storage module is used to receive the remaining monitoring image data screened by the screening module and store the monitoring image data.

[0054] The monitoring image data identified in the identification module comes from the monitoring parameters of the health device, that is, the monitoring range of the monitoring device. The monitoring image data screening logic set in the screening module is:

[0055]

[0056] Where: S(α) is the estimated monitoring range of the monitoring device; d is the vertical distance from the monitoring device to the monitoring plane; f is the focal length of the monitoring device; p v 、p hS is the horizontal pixel span and vertical pixel span of any static object in the monitoring image data of the monitoring device; h 、S v P is the horizontal size and vertical size of the image sensor of the monitoring equipment; h 、P v is the number of horizontal and vertical pixels of the monitoring screen of the monitoring device; t is the time interval for picking up the frames in the monitoring image data; t0 is the base number of the picking time interval; λ is a constant;

[0057] After obtaining the frame picking time interval t in the surveillance image data, the surveillance image data is segmented based on t to obtain a plurality of sub-groups of surveillance image data, and the last group of frames in each sub-group of surveillance image data is selected as the screening result of the screening module;

[0058] The storage module is internally provided with submodules, including:

[0059] a marking unit for traversing the image frames stored in the storage module, obtaining the location information and time stamp of the monitoring device from which each image frame originated, marking each corresponding image frame based on the obtained location information and time stamp of the monitoring device from which the image frame originated, and controlling the storage module to perform differentiated storage on the internally stored image frames once based on the location information of the monitoring device and once based on the time period corresponding to the source time stamp;

[0060] The time period corresponding to the timestamp is in hours;

[0061] The search engine uploads the search target and the search target attribute parameters in real time, confirms the search target group in the cloud database based on the search target attribute parameters, and further performs the search for the search target in the search target group;

[0062] The search engine includes an upload module and a search unit:

[0063] The upload module is used to upload the search target and the search target attribute parameters, and use the search target attribute parameters to confirm the search target group in the cloud database. The search unit is used to obtain the search target group confirmed in the upload module and search for a picture frame containing a dynamic target similar to the search target in the search target group.

[0064] wherein one or more groups of search targets uploaded in the upload module contain image data of people, the search target attribute parameters include: the search target source location, the search target source timestamp, and the search unit retrieves the picture frames containing dynamic objects similar to the search target and determines that the similarity is not less than 85%;

[0065] The receiver, cloud database and search engine are interactively connected via a wireless network;

[0066] The receiver is internally connected to a protocol unit via a wireless network, and the receiver is interactively connected to a receiving module and a forwarding module via a wireless network;

[0067] The cloud database is interactively connected to the identification module, the screening module and the storage module via a wireless network, and the storage module is interactively connected to the marking unit via a wireless network;

[0068] The search engine is interactively connected with the upload module and the search unit via a wireless network.

[0069] In this embodiment, the protocol unit runs to access the user terminal of the monitoring device and requests the monitoring device for monitoring image data interaction permission. The receiving module synchronously obtains the monitoring device monitoring image data interaction permission request result in the protocol unit and performs real-time monitoring image data receiving operation on the authorized monitoring device. The forwarding module is post-operated to forward the monitoring image data received in the receiving module to the cloud database. The identification module then receives the monitoring image data forwarded by the forwarding module and identifies the monitoring parameters of the monitoring device from which the monitoring image data comes. The screening module further obtains the monitoring parameters of the monitoring device identified in the identification module, sets the monitoring image data screening logic based on the monitoring device monitoring parameters, and screens the monitoring image data of the monitoring device through the monitoring image data screening logic. The storage module receives the screening module in real time. The remaining monitoring image data is filtered in the block and stored. During the operation phase of the storage module, the marking unit synchronously traverses the picture frames stored in the storage module, obtains the location information and timestamp of the monitoring device from which each picture frame comes, and marks each corresponding picture frame based on the obtained location information and timestamp of the monitoring device from which the picture frame comes. The storage module is controlled to perform a differentiated storage on the internally stored picture frames by the location information of the monitoring device and a differentiated storage by the time period corresponding to the source timestamp. Finally, the retrieval target and the retrieval target attribute parameters are uploaded through the upload module. The retrieval target attribute parameters are applied to confirm the retrieval target group in the cloud database. The retrieval unit obtains the retrieval target group confirmed in the upload module, and searches for picture frames containing dynamic targets similar to the retrieval target in the retrieval target group.

[0070] Through the operation of the system in the above embodiment, an intelligent, fast and convenient target tracking technology is provided to the system end user;

[0071] See also Figure 2 As shown:

[0072] Figure 2 A brief description:

[0073] GA / T1400 is the standard for public security video image information application systems. Tianyi Vision's snapshot and push service is based on the public security GA / T1400 protocol standard. It will install 1400 cameras in public places, road checkpoints, and key monitoring areas to capture faces, vehicle size images, and structured data and push them to the public security platform to meet the public security's requirements for social video image resource management.

[0074] The Tianyi Video 1400 protocol is one of the most important interface protocols in video surveillance systems. It defines how information is exchanged between all levels of the system, including key aspects such as device registration, keepalives, subscriptions, and feature attribute push. By following the Tianyi Video 1400 protocol, seamless integration with the public security 1400 view library is achieved. Using the standard 1400 protocol, the system connects to the higher-level public security platform, implementing processes such as registration, keepalives, subscription distribution, and image push.

[0075] Use the following steps to implement the snapshot and push function:

[0076] 1. Device registration and keep-alive: ensure normal communication between the lower-level platform and the upper-level platform.

[0077] 2. Subscription management: The lower-level platform configures the corresponding feature attribute push service based on the subscription request of the upper-level platform.

[0078] Feature attribute collection and push: The lower-level platform collects key target feature attributes in the video in real time, and pushes the feature attribute information to the upper-level platform according to the subscription information.

[0079] Example 2:

[0080] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The intelligent management system based on massive image data in Example 1 is further described in detail:

[0081] After the protocol unit confirms the receiver's permission to interact with the monitoring device's surveillance image data, the monitoring device, deployed over an optical fiber network, receives the surveillance image data through the receiving module and transmits it to the receiver. When receiving the surveillance image data, the receiving module simultaneously obtains the time and location information of the source surveillance device of the surveillance image data.

[0082] When forwarding the surveillance image data stored in the receiver, the forwarding module synchronously sets the surveillance image data segmentation time domain, and based on the set surveillance image data segmentation data, performs segmentation processing on the surveillance image data stored in the receiver, and further forwards the surveillance image data belonging to each time domain to the cloud database in sequence based on the time sequence;

[0083] Among them, the surveillance image data segmentation time domain set in the forwarding module is not less than five seconds and not more than fifteen seconds.

[0084] like Figure 1 As shown, the constant λ ≥ 1, and the picking time interval base t0 is manually set by the system end user;

[0085] After the screening module runs and filters the picture frames, it synchronously performs dynamic target recognition in continuous frames, and the picture frames of the recognized dynamic targets are used as the final picture frame screening results of the screening module;

[0086] Among them, when the screening module identifies dynamic targets in continuous frames, it applies a background subtraction algorithm or a feature point tracking algorithm to identify dynamic targets;

[0087] The search target group is composed of storage intervals distinguished in several groups of storage modules;

[0088] When the retrieval target group is determined, the retrieval target source position and the retrieval target source timestamp corresponding time period in the retrieval target attribute parameters are used to obtain a differentiated storage interval in the storage module that is the same as the retrieval target source position and the same as the retrieval target source timestamp corresponding time period, so as to differentiate each picture frame in the storage interval as the object for similarity comparison with the retrieval target, and further perform the retrieval operation.

[0089] In this embodiment, the above-mentioned settings provide further operation logic support for the system in Example 1, ensuring stable operation of the system in Example 1 and providing image retrieval services for system users.

[0090] In summary, during the operation of the system in the above embodiment, by obtaining the permissions of the monitoring devices, the system realizes the centralized reception of monitoring image data from multiple monitoring devices, and further condenses a large amount of monitoring image data into image data through the setting and screening processing of the monitoring image data screening logic. Therefore, when the system-side user has tracking needs, based on the system, it can autonomously retrieve the search target trends in the massive image data based on the search target uploaded by the system-side user, thereby improving the system-side user's search target tracking efficiency and bringing convenience to the tracking work of the system-side user.

[0091] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An intelligent management system based on massive image data, characterized in that: include: Receiver, cloud database and search engine; The receiver obtains the monitoring image data interaction permission of the monitoring device. After obtaining the monitoring image data interaction permission, it receives the monitoring image data of the monitoring device in real time and sends it to the cloud database in real time; The cloud database obtains the monitoring image data fed back by the receiver in real time, identifies the monitoring parameters of the monitoring equipment from which the monitoring image data originates, sets the monitoring image data screening logic based on the monitoring parameters of the monitoring equipment, applies the monitoring image data screening logic to perform frame screening on the monitoring image data, further stores the screened frames, and marks the frames with identifiable marks; The cloud database includes an identification module, a screening module, and a storage module: The identification module is used to receive the monitoring image data forwarded by the forwarding module and identify the monitoring parameters of the monitoring device from which the monitoring image data originates. The screening module is used to obtain the monitoring parameters of the monitoring device identified in the identification module, set the monitoring image data screening logic based on the monitoring parameters of the monitoring device, and perform frame screening on the monitoring image data of the monitoring device through the monitoring image data screening logic. The storage module is used to receive the remaining monitoring image data screened by the screening module and store the monitoring image data. The monitoring image data identified in the identification module comes from the monitoring parameters of the health device, that is, the monitoring range of the monitoring device. The monitoring image data screening logic set in the screening module is: Where: S(α) is the estimated monitoring range of the monitoring device; d is the vertical distance from the monitoring device to the monitoring plane; f is the focal length of the monitoring device; p v 、p h S is the horizontal pixel span and vertical pixel span of any static object in the monitoring image data of the monitoring device; h 、S v P is the horizontal size and vertical size of the image sensor of the monitoring equipment; h 、P v is the number of horizontal and vertical pixels of the monitoring screen of the monitoring device; t is the time interval for picking up the frames in the monitoring image data; t0 is the base number of the picking time interval; λ is a constant; After obtaining the frame picking time interval t in the surveillance image data, the surveillance image data is segmented based on t to obtain a plurality of sub-groups of surveillance image data, and the last group of frames in each sub-group of surveillance image data is selected as the screening result of the screening module; The constant λ≥1, and the picking time interval base t0 is manually set by the system end user; After the screening module runs and filters the picture frames, it synchronously performs dynamic target recognition in continuous frames, and the picture frames of the recognized dynamic targets are used as the final picture frame screening results of the screening module; Among them, when the screening module identifies dynamic targets in continuous frames, it applies a background subtraction algorithm or a feature point tracking algorithm to identify dynamic targets; The search engine uploads the search target and the search target attribute parameters in real time, confirms the search target group in the cloud database based on the search target attribute parameters, and further performs the search of the search target in the search target group.

2. The intelligent management system based on massive image data according to claim 1, characterized in that: The receiver includes a protocol unit, a receiving module, and a forwarding module: The protocol unit is used to access the monitoring device user terminal and request the monitoring device monitoring image data interaction permission. The receiving module is used to obtain the monitoring device monitoring image data interaction permission request result in the protocol unit and perform real-time monitoring image data reception operations on the authorized monitoring device. The forwarding module is used to forward the monitoring image data received in the receiving module to the cloud database; Among them, the operation of accessing the monitoring device user terminal in the protocol unit and requesting the monitoring device monitoring image data interaction permission is to contact the monitoring device user terminal with a communication device and request the monitoring device monitoring image data interaction permission, or during the monitoring device installation stage, the monitoring device network access protocol includes the monitoring device monitoring image data interaction permission and is confirmed by the monitoring device user terminal.

3. The intelligent management system based on massive image data according to claim 2, characterized in that: After the protocol unit confirms the receiver and the monitoring device's authority to interact with monitoring image data, the monitoring device is deployed based on a fiber optic network, and receives the monitoring image data through a receiving module and transmits it to the receiver. When receiving the monitoring image data, the receiving module synchronously obtains the time and location information of the source monitoring device of the monitoring image data.

4. The intelligent management system based on massive image data according to claim 2, characterized in that: When forwarding the surveillance image data stored in the receiver, the forwarding module synchronously sets the surveillance image data segmentation time domain, performs segmentation processing on the surveillance image data stored in the receiver based on the set surveillance image data segmentation data, and further forwards the surveillance image data belonging to each time domain to the cloud database in sequence based on the time sequence; Among them, the surveillance image data segmentation time domain set in the forwarding module is not less than five seconds and not more than fifteen seconds.

5. The intelligent management system based on massive image data according to claim 1, characterized in that: The storage module is internally provided with submodules, including: a marking unit for traversing the image frames stored in the storage module, obtaining the location information and time stamp of the monitoring device from which each image frame originated, marking each corresponding image frame based on the obtained location information and time stamp of the monitoring device from which the image frame originated, and controlling the storage module to perform differentiated storage on the internally stored image frames once based on the location information of the monitoring device and once based on the time period corresponding to the source time stamp; The time period corresponding to the timestamp is in hours.

6. The intelligent management system based on massive image data according to claim 1, characterized in that: The search engine includes an upload module and a search unit: The upload module is used to upload the search target and the search target attribute parameters, and use the search target attribute parameters to confirm the search target group in the cloud database. The search unit is used to obtain the search target group confirmed in the upload module and search for a picture frame containing a dynamic target similar to the search target in the search target group. Among them, one or several groups of retrieval targets uploaded in the upload module contain image data of people, and the retrieval target attribute parameters include: retrieval target source location, retrieval target source timestamp, and the retrieval unit retrieves the picture frames containing dynamic targets similar to the retrieval targets and determines that the similarity is not less than 85%.

7. The intelligent management system based on massive image data according to claim 6, characterized in that: The search target group is composed of storage intervals divided into several groups of storage modules; When the retrieval target group is determined, the retrieval target source position and the retrieval target source timestamp corresponding time period in the retrieval target attribute parameters are used to obtain a differentiated storage interval in the storage module that is the same as the retrieval target source position and the same as the retrieval target source timestamp corresponding time period, so as to differentiate each picture frame in the storage interval as an object for similarity comparison with the retrieval target, and further perform the retrieval operation.

8. The intelligent management system based on massive image data according to claim 1, characterized in that: The receiver, cloud database and search engine are interactively connected via a wireless network; The receiver is internally connected to a protocol unit via a wireless network, and the receiver is interactively connected to a receiving module and a forwarding module via a wireless network; The cloud database is interactively connected to the identification module, the screening module and the storage module via a wireless network, and the storage module is internally interactively connected to the marking unit via a wireless network; The search engine is interactively connected with an upload module and a search unit via a wireless network.

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