CN117991686A

CN117991686A - Data acquisition method and system based on Internet of things platform

Info

Publication number: CN117991686A
Application number: CN202311860277.7A
Authority: CN
Inventors: 方超; 杨冰; 刘晓宏; 张国栋
Original assignee: Baweitong Technology Co ltd
Current assignee: Baweitong Technology Co ltd
Priority date: 2023-12-29
Filing date: 2023-12-29
Publication date: 2024-05-07

Abstract

The embodiment of the application discloses a data acquisition method and a system based on an internet of things platform, which are applied to a self-research internet of things platform, wherein the method comprises the following steps: creating an acquisition channel and configuring an acquisition point of the acquisition channel; the acquisition point positions and the corresponding Internet of things equipment attributes are stored in a local database in an associated mode; responding to the trigger of the acquisition task, and acquiring corresponding equipment data through a target acquisition point position; and analyzing the equipment data according to the configuration information of the target acquisition point to obtain corresponding target equipment data, and updating the equipment data corresponding to the local database according to the target equipment data. The embodiment of the application realizes the data acquisition of the internet of things platform, improves the value and the efficiency of the data acquisition, and provides rapid and effective data support for the management of internet of things equipment and the operation of a rail transit system.

Description

Data acquisition method and system based on Internet of things platform

Technical Field

The application relates to the technical field of the Internet of things, in particular to a data acquisition method and system based on an Internet of things platform.

Background

In recent years, the urban process is accelerated, the urban population scale is continuously enlarged, and increasing traffic demands put forward higher requirements on urban rail transit systems, so that digital transformation of rail transit is put forward, the Internet of things of the rail transit is built, and the interconnection and intercommunication of stations, trains, signals and other equipment are realized; at present, the internet of things platform has wide application in aspects of intelligent transportation, operation management, station passenger information service and the like, such as track traffic vehicles and equipment monitoring, fault early warning processing and the like through collecting, processing and transmitting field data; however, at present, when data are acquired, each acquisition device directly feeds back the data to the internet of things platform after acquiring the data, and the internet of things platform carries out subsequent application after carrying out data understanding.

Disclosure of Invention

In order to solve the technical problems, the embodiment of the application provides a data acquisition method and system based on an internet of things platform, electronic equipment, a computer readable storage medium and a computer program product, which realize the data acquisition of the internet of things platform, improve the value and efficiency of the data acquisition and provide rapid and effective data support for the management of the internet of things equipment and the operation of a rail transit system.

According to an aspect of the embodiment of the application, a data acquisition method based on an internet of things platform is provided, and the method is applied to a self-grinding internet of things platform and comprises the following steps: creating an acquisition channel and configuring an acquisition point position of the acquisition channel; storing the acquisition point positions and the corresponding Internet of things equipment attributes in a local database in an associated manner; responding to the trigger of the acquisition task, and acquiring corresponding equipment data through a target acquisition point position; and analyzing the equipment data according to the configuration information of the target acquisition point to obtain corresponding target equipment data, and updating the equipment data corresponding to the local database according to the target equipment data.

According to an aspect of an embodiment of the present application, the number of the acquisition channels and the acquisition points each include a plurality of; the responding to the triggering of the acquisition task, the corresponding equipment data is acquired through the target acquisition point position, and the method comprises the following steps: triggering an acquisition task according to the last acquisition time; responding to the trigger of the acquisition task, traversing the acquisition channel to determine a target acquisition channel; traversing the acquisition point positions of the target acquisition channel, selecting part of acquisition point positions from a plurality of acquisition point positions to obtain the target acquisition point positions, and controlling the target acquisition point positions to acquire corresponding equipment data according to the preset point position acquisition time.

According to an aspect of the embodiment of the present application, the method further includes: the configuration information comprises a data type and a data factor; the analyzing the device data according to the configuration information of the target acquisition point to obtain corresponding target device data includes: converting the data format of the equipment data according to the data type to obtain intermediate equipment data; and scaling the intermediate equipment data according to the data factor to obtain the target equipment data.

According to an aspect of the embodiment of the present application, after the updating of the device data corresponding to the local database according to the target device data, the method further includes: if the attribute change of the Internet of things equipment associated with the acquisition point is detected according to the target equipment data, updating the attribute of the Internet of things equipment; reporting the updated internet of things device attribute to an open source internet of things platform so as to monitor the internet of things device through the open source internet of things platform according to the updated internet of things device attribute.

According to an aspect of the embodiment of the present application, the method further includes: accessing a video access platform, and carrying out binding processing of the video channel and the camera equipment after the video channel is locally configured; receiving a video channel list pushed by the video access platform, and comparing the video channel list with a video channel of a local database; and updating the video channel of the local database according to the comparison result, updating the binding relation between the video channel and the camera equipment based on the updated video channel, and storing the binding relation into the local database so as to access video data based on the camera equipment.

According to an aspect of the embodiment of the present application, the updating the video channel of the local database according to the comparison result, updating the binding relationship between the video channel and the image capturing device based on the updated video channel, and storing the binding relationship in the local database includes: if the local database comprises a first target video channel which does not exist in the video channel list, deleting the first target video channel, and unbinding the image pickup equipment bound with the first target video channel; and if the video channel list comprises a second target video channel which does not exist in the local database, binding the second target video channel with unbinding camera equipment and storing the second target video channel and the unbinding camera equipment into the local database.

According to an aspect of the embodiment of the present application, after the binding relationship between the video channel and the image capturing device is updated based on the updated video channel and stored in the local database, the method further includes: responding to an open source internet of things platform to send a call instruction for target camera equipment, and calling the target camera equipment according to a video channel corresponding to the target camera equipment; the call instruction is generated based on an image pickup apparatus selection instruction of the management party; and pulling video data which is collected by the target camera equipment and runs aiming at the target Internet of things equipment.

According to an aspect of the embodiment of the present application, the invoking the target image capturing apparatus according to the video channel corresponding to the target image capturing apparatus includes: acquiring an access mode of the target camera equipment according to a video channel corresponding to the target camera equipment, and acquiring a video access platform parameter and a video channel parameter corresponding to the target camera equipment according to the access mode of the target camera equipment; pulling video data collected by the target camera device and operated aiming at the target internet of things device, wherein the video data comprises: requesting to pull a video from the video access platform according to the video access platform parameters and the video channel parameters corresponding to the target camera equipment; and receiving a video stream address sent by the video access platform, acquiring the video data according to the video stream address, and storing the video data into a local database.

According to an aspect of the embodiment of the present application, after the updating of the device data corresponding to the local database according to the target device data, the method further includes: and synchronizing the equipment data acquired by the Internet of things equipment and the video data acquired by the camera equipment stored in the local database to an external system, wherein the external system comprises a cloud.

According to an aspect of the embodiment of the present application, there is provided a data acquisition system based on an internet of things platform, the system including a self-grinding internet of things platform, the self-grinding internet of things platform including a configuration module, a data acquisition module, and a database, including: the configuration module is used for creating an acquisition channel and configuring acquisition points of the acquisition channel; storing the acquisition point positions and the corresponding Internet of things equipment attributes in a local database in an associated manner; the data acquisition module is used for responding to the trigger of the acquisition task and acquiring corresponding equipment data through the target acquisition point position; and analyzing the equipment data according to the configuration information of the target acquisition point to obtain corresponding target equipment data, and updating the equipment data corresponding to the local database according to the target equipment data.

According to an aspect of an embodiment of the present application, there is provided an electronic apparatus including: one or more processors; and the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the electronic equipment realizes the data acquisition method based on the Internet of things platform.

According to an aspect of an embodiment of the present application, there is provided a computer-readable storage medium having stored thereon computer-readable instructions, which when executed by a processor of a computer, cause the computer to perform the data acquisition method based on the internet of things platform as described above.

According to an aspect of the embodiments of the present application, there is also provided a computer program product comprising a computer program which, when executed by a processor, implements the steps in a data collection method based on an internet of things platform as described above.

In the technical scheme provided by the embodiment of the application, the self-research internet of things platform can create the acquisition channel, configure the acquisition point of the acquisition channel, and store the acquisition point and the corresponding internet of things equipment attribute in a local database in a correlated manner so as to facilitate the effective management of the acquisition point subsequently; in response to the triggering of the acquisition task, corresponding equipment data are acquired through the target acquisition point, and then the corresponding target equipment data are obtained by analyzing the equipment data according to the configuration information of the target acquisition point, so that the data are suitable for the data formats of various equipment, the acquired data can be accurately understood and utilized by a system, the equipment data corresponding to a local database are updated according to the target equipment data, the acquired equipment data can be instantly reflected in the local database, the data acquisition of an Internet of things platform is realized, the value and the efficiency of the data acquisition are improved, and quick and effective data support is provided for the management of the Internet of things equipment and the operation of a rail transit system.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. It is evident that the drawings in the following description are only some embodiments of the present application and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art. In the drawings:

FIG. 1 is a schematic diagram of an implementation environment for performing an Internet of things platform-based data acquisition method according to an exemplary embodiment of the present application;

FIG. 2 is a flow chart illustrating a method of data collection based on an Internet of things platform according to an exemplary embodiment of the present application;

FIG. 3 is a schematic diagram of a data acquisition system based on an Internet of things platform, according to an exemplary embodiment of the present application;

FIG. 4 is a schematic diagram of an environment in which another data acquisition method of the present application is implemented, in an exemplary embodiment;

FIG. 5 is a schematic diagram of a specific structure of a self-polishing Internet of things platform according to an exemplary embodiment of the present application;

FIG. 6 is a flow diagram of a device data collection process based on an Internet of things platform in an exemplary embodiment;

FIG. 7 is a flow chart of data acquisition shown in FIG. 6 in an exemplary embodiment;

FIG. 8 is a flow diagram of a video access process based on an Internet of things platform, shown in an exemplary embodiment;

FIG. 9 is a flowchart of video pulling shown in FIG. 8 in an exemplary embodiment;

FIG. 10 is a flow chart of video channel updates shown in FIG. 8 in an exemplary embodiment;

FIG. 11 is a block diagram of a data acquisition system based on an Internet of things platform, as shown in an exemplary embodiment of the application;

Fig. 12 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.

Detailed Description

Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.

The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.

In the present application, the term "plurality" means two or more. "and/or" describes an association relationship of an association object, meaning that there may be three relationships, e.g., a and/or B may represent: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.

Fig. 1 is a schematic diagram of an implementation environment of data collection based on an internet of things platform according to an exemplary embodiment of the present application. The implementation environment comprises a manager 10 and a self-research internet of things platform 20.

The self-grinding internet of things platform 20 is used for creating an acquisition channel and configuring an acquisition point of the acquisition channel; the acquisition point positions and the corresponding Internet of things equipment attributes are stored in a local database in an associated mode; responding to the trigger of the acquisition task, and acquiring corresponding equipment data through a target acquisition point position; and analyzing the equipment data according to the configuration information of the target acquisition point to obtain corresponding target equipment data, and updating the equipment data corresponding to the local database according to the target equipment data.

The self-research internet of things platform can be an operation instruction of a manager to create an acquisition channel and configure an acquisition point.

The self-research internet of things platform is an internet of things platform developed in the applicant, related functions of the open source internet of things platform are multiplexed, and further expansion, improvement/optimization and the like are performed on the basis of the open source internet of things platform; the open source internet of things platform refers to an open source software framework which is the most basic framework for realizing the internet of things function, provides various tools and technologies, and can help developers to quickly build the internet of things application.

For example, the open source internet of things platform may be jetlinks, and the JetLinks is developed based on Java8, spring Boot 2.X, webflux, netty, ver. X, reactor, and the like, and is an enterprise-level internet of things base platform.

In an example, the self-research internet of things platform is an internet of things platform based on track traffic, and the internet of things device is a track traffic related device, such as a gate, a sliding door, a shielding door, an AFC (automatic fare collection), an air conditioning unit, and the like.

Referring to fig. 2, fig. 2 is a flowchart illustrating a data collection method based on an internet of things platform according to an exemplary embodiment of the present application. The method may be applied to the implementation environment shown in fig. 1 and specifically executed by the self-research internet of things platform in the implementation environment, and it should be understood that the method may also be applicable to other exemplary implementation environments and specifically executed by devices in other implementation environments, and the implementation environment to which the method is applicable is not limited by the embodiment.

As shown in fig. 2, in an exemplary embodiment, the data collection method based on the internet of things platform at least includes steps S210 to S240, which are described in detail as follows:

s210, creating an acquisition channel and configuring an acquisition point of the acquisition channel.

In the embodiment of the application, an acquisition channel is created for the Internet of things equipment, the acquisition channel comprises a communication channel of the Internet of things equipment and a self-research Internet of things platform, configuration information of the acquisition channel comprises a communication protocol, a communication rate, a communication port and the like, wherein the communication protocol comprises a Modbus protocol, and the Modbus protocol comprises TCP, RTU, ASCII; such as modbus_tcp host IP, host port, slave IP.

It will be appreciated that the number of the collection channels may include one or more, and in order to distinguish between the collection channels, a unique channel ID needs to be assigned to each collection channel, and in addition, a corresponding collection point needs to be configured for each collection channel to determine a specific location or point location on the channel, where the collection point location includes a location of an internet of things device, or a location of a sensor on the internet of things device, and the number of collection points of each collection channel may also include one or more.

In an example, when the collection point is configured, configuration information of the collection point can be configured, where the configuration information includes a data format, a coding and decoding mode, a collection data mode (collection and collection when changing), a collection frequency, and the like, that is, for different types of device data, diversified analysis and processing modes are provided, so that the self-research internet of things platform can correctly manage the data collected by the internet of things device, and in addition, the configuration information can also include a custom analysis rule to adapt to data formats of various devices, so as to ensure that the collected data can be accurately understood and utilized by the system.

In an example, the self-research internet of things platform may create an acquisition channel based on the operation instructions of the manager, and may configure an acquisition point based on the operation instructions of the manager.

S220, the acquisition point positions and the corresponding Internet of things equipment attributes are stored in a local database in an associated mode.

In the embodiment of the application, in order to determine that the acquired data can be normally mapped to the equipment, the acquisition point position is required to be associated with the corresponding equipment attribute of the internet of things, and the associated information is stored in the database of the self-research internet of things platform so as to facilitate subsequent inquiry and management, wherein the equipment attribute of the internet of things comprises, but is not limited to, the equipment ID of the internet of things, the equipment type, the maximum value of the data and the like.

In an example, an acquisition point is associated with an attribute of an internet of things device, and a correspondence between the acquisition point and the internet of things device may be determined in advance according to an operation of a manager or may be determined randomly.

S230, responding to the trigger of the acquisition task, and acquiring corresponding equipment data through the target acquisition point position.

In the embodiment of the application, when the acquisition task is triggered, the self-research internet of things equipment controls the target acquisition point to acquire corresponding equipment data, wherein the target acquisition point can be any one acquisition point, can be a designated part of acquisition points or can be all the acquisition points, and the equipment data are acquired by the internet of things equipment or a sensor.

In one example, the acquisition task may be triggered manually or automatically timed.

Optionally, the number of the collection channels and the collection points includes a plurality of, and in response to a trigger of the collection task, corresponding device data is collected through the target collection point, including:

triggering the acquisition task according to the last acquisition time;

responding to the trigger of the acquisition task, traversing the acquisition channel to determine a target acquisition channel;

traversing the acquisition points of the target acquisition channel, selecting part of the acquisition points from the plurality of acquisition points to obtain the target acquisition points, and controlling the target acquisition points to acquire corresponding equipment data according to the preset point acquisition time.

In the embodiment of the application, the acquisition task is triggered at fixed time, and can be automatically triggered after a preset time interval on the basis of the last acquisition time; or based on the total collection times before the current time and the last collection time, the collection tasks can be automatically triggered after the preset time interval is dynamically adjusted, for example, the first collection time is 10:00, the second collection time is carried out after the interval of 30 seconds, the third collection time is carried out after the interval of 1 minute, and the like, and the interval time is increased along with the increase of the collection times. The interval time can be determined based on the last acquisition time and the change condition of the acquired content of the previous two times, if the data acquired for the first time is a, the second acquisition time is carried out after the interval of 30 seconds, the acquired data is still a, and the acquisition can be carried out again at the interval of 1 minute in the third acquisition; if the data acquired for the second time is b, acquiring again at intervals of 30s in the third time, and triggering the task for the third time at intervals of 30s and the second time.

When the acquisition task is triggered, traversing the acquisition channels to determine target acquisition channels, wherein the target acquisition channels can be any one acquisition channel or can be designated partial acquisition channels, for example, the acquisition channels are ordered according to channel IDs, when the acquisition channels are determined for the first time, the first n acquisition channels are used as target acquisition channels based on the ordering, and when the acquisition channels are determined for the second time, the first n acquisition channels are continuously selected as target acquisition channels according to the ID ordering on the basis of the last determined acquisition channels.

Because the target acquisition channel comprises a plurality of acquisition points, the acquisition points of the target acquisition channel can be traversed, and then part of the acquisition points are selected from the plurality of acquisition points to serve as target acquisition points, namely, the partial point acquisition of the channel is realized; the partial acquisition points may be selected randomly from a plurality of acquisition points, or may be sequentially selected according to the ID of the acquisition point, which is not limited herein.

In the embodiment of the application, after the target acquisition point position is determined, the target acquisition point position can be controlled to acquire corresponding equipment data based on the preset point position acquisition time, namely corresponding internet of things equipment reads data from a sensor or a register of the equipment according to the acquisition time; the corresponding point position acquisition time can be the same or different for different acquisition point positions, and the point position acquisition time can be configured when the acquisition point positions are configured or flexibly adjusted based on specific acquisition tasks.

According to the embodiment of the application, the acquisition task is triggered by the last acquisition time, so that the target acquisition channel is determined, part of the acquisition points are selected to obtain the target acquisition points, and the corresponding equipment data are acquired by controlling the target acquisition points according to the preset point acquisition time, thereby ensuring the data acquisition order and avoiding the influence relationship among the acquisition points.

S240, analyzing the device data according to the configuration information of the target acquisition point to obtain corresponding target device data, and updating the device data corresponding to the local database according to the target device data.

It can be understood that, because the internet of things devices are different in data type of the collected device data, in order to facilitate the self-research of the internet of things devices to rapidly manage various device data, the device data needs to be interpreted according to the configuration information of the target collection point so as to convert the original data into the target device data in a uniform format which can be understood, and then the analyzed target device data is updated to the database for subsequent use and analysis; the method comprises the steps of establishing a proper data storage structure on a self-research internet of things platform, wherein the proper data storage structure comprises a traditional relational database, a NoSQL database and the like, so that high-efficiency storage and quick retrieval of mass data are ensured.

In an example, the configuration information includes a data type and a data factor, where the data factor is a scaling factor of data, and resolving the device data according to the configuration information of the target acquisition point to obtain corresponding target device data includes:

Converting the data format of the equipment data according to the data type to obtain intermediate equipment data; and scaling the intermediate equipment data according to the data factors to obtain target equipment data.

Converting the data format of the collected device data into the data format indicated by the data type to obtain target intermediate data, wherein the data type of the device data comprises a text type and a numerical type, and converting the text type device data into a character string; the numeric device data is converted into integer int.

After the data format conversion, the intermediate equipment data can be scaled according to the data factors, wherein the scaling processing comprises the steps of converting the intermediate equipment data according to a certain proportion, and placing the data in a small specific interval, such as 0-1 or-1, so as to eliminate the difference of characteristic attributes such as characteristics, orders of magnitude and the like among different samples, convert the characteristic attributes into a dimensionless relative value, and enable the characteristic quantity values of all samples to be in the same order of magnitude, thereby realizing the correction of the intermediate equipment data and obtaining target equipment data; for example, the data factor is 0.1, the intermediate device data is scaled by a factor of 0.1.

In an example, scaling is performed on numeric type intermediate device data, after scaling, decimal point post-retention bit number can be performed, and data storage resources are saved while accuracy of the device data is ensured.

In the embodiment of the application, the device data is analyzed through the data type and the data factor to obtain the target device data, so that the reliability and the authenticity of the target device data are ensured.

In the embodiment of the application, after updating the device data corresponding to the local database according to the target device data, the method further comprises the following steps:

if the attribute change of the Internet of things equipment associated with the acquisition point is detected according to the target equipment data, the attribute of the Internet of things equipment is updated;

Reporting the updated internet of things device attribute to an open source internet of things platform so as to monitor the internet of things device according to the updated internet of things device attribute through the open source internet of things platform.

In the embodiment of the application, according to the previous configuration, the related information of the acquisition point position and the equipment attribute of the internet of things is acquired, if the acquired data influences the equipment attribute, for example, a temperature sensor acquires a new temperature value, the corresponding equipment attribute needs to be updated, namely, the self-research internet of things platform updates the data snapshot of the equipment according to the target equipment data, namely, the latest state of the equipment.

In order to monitor and manage the internet of things equipment, the self-research internet of things platform can report updated equipment attributes to the open source internet of things platform so as to monitor and manage in real time, and the open source internet of things platform monitors the internet of things equipment according to the updated internet of things equipment attributes so as to monitor and control in real time.

It is worth noting that, the data acquisition method in the embodiment of the application can acquire equipment data through point positions, and can access videos and pull data at the same time, so that the data acquisition of the internet of things platform is realized. As shown in fig. 3, on the basis of the data shown in fig. 2, the data acquisition method further includes:

S310, accessing a video access platform, and performing binding processing of the video channel and the camera equipment after configuring the video channel.

In the embodiment of the application, the camera equipment is not the internet of things equipment, so that the camera equipment needs to be connected with a video access platform, and meanwhile, a video channel is configured locally, wherein the video channel comprises a channel between the camera equipment and the self-research internet of things platform, the configuration information of the video channel comprises a video access mode, and the video access mode comprises fixed address access, video national standard access and video API access; if the video is accessed by the national standard, the video also comprises an SIP server IP, a port, an access password and the like.

In order to determine that the collected video data can be correctly mapped to the image capturing device, an association binding process needs to be performed between the video channel and the image capturing device, which may be that the video channel is associated and bound with the ID of the image capturing device.

S320, receiving a video channel list pushed by the video access platform, and comparing the video channel list with a video channel of a local database.

S330, updating the video channel of the local database according to the comparison result, updating the binding relation between the video channel and the image pickup device based on the updated video channel, and storing the binding relation in the local database so as to access video data based on the image pickup device.

In the embodiment of the application, the video access platform is used for managing the camera equipment, such as manufacturers of the camera equipment, and the video access platform can push the usable video channel list to the self-grinding internet of things platform, so that the self-grinding internet of things platform needs to compare the pushed video channel list with the video channel of the local database to determine whether to update the local video channel.

After updating the video channel, the binding relationship between the video channel and the camera device in step S310 needs to be updated, and the updated binding relationship is stored in a local database, and the camera device collects video data, so that the self-research internet of things device can access the video data.

In the embodiment of the application, the video channel and the camera equipment are bound, so that the access of video data is performed based on the camera equipment, and the comprehensiveness of the data acquisition of the self-research internet of things platform is improved.

In one example, updating the video channel and updating the binding relationship includes:

if the local database comprises a first target video channel which does not exist in the video channel list, deleting the first target video channel, and unbinding the first target video channel to the image pickup equipment bound with the first target video channel;

if the video channel list comprises a second target video channel which does not exist in the local database, binding the second target video channel with unbinding camera equipment and storing the second target video channel and unbinding camera equipment into the local database.

The method comprises the steps that a first target video channel is a video channel needing to be deleted, a second target video channel is a newly added video channel, and after the first target video channel is deleted, the binding relation between the first target video channel and corresponding camera equipment is required to be unbinding; at this time, if there is a newly added second target video channel, binding the second target video channel with the unbinding camera equipment is needed, and the binding relation is stored in a local database; if there is a second target video channel without unbound image capturing device, the second target video channel may be omitted, or an image capturing device may be added and then bound.

In the embodiment of the application, after updating the binding relationship, the method further comprises the following steps:

Responding to an open source internet of things platform to send a call instruction for target camera equipment, and calling the target camera equipment according to a video channel corresponding to the target camera equipment; the call instruction is generated based on the image capturing apparatus selection instruction of the management party;

and pulling video data which is collected by the target camera equipment and runs aiming at the target Internet of things equipment.

In the embodiment of the application, the management side can select the image pickup device to pull the video data of the selected image pickup device, the open source internet of things platform generates the call instruction of the target image pickup device based on the image pickup device selection instruction, the number of the target image pickup device, namely the image pickup device selected by the management side, can be one or a plurality of target image pickup devices, the number of the target image pickup devices can be not limited here, the open source internet of things platform sends the call instruction to the self-grinding internet of things platform, the self-grinding internet of things platform responds to the call instruction, the video channel corresponding to the target image pickup device is acquired from the local database, the target image pickup device is called based on the video channel, and then the video data which is acquired by the target image pickup device and is operated aiming at the target internet of things device is pulled, so that the management and the monitoring of the operation of the internet of things device are realized.

In an example, invoking the target image capturing apparatus according to a video channel corresponding to the target image capturing apparatus includes:

And acquiring a target camera equipment access mode according to a video channel corresponding to the target camera equipment, and acquiring video access platform parameters and video channel parameters corresponding to the target camera equipment according to the target camera equipment access mode.

As described above, the configuration information of the video channel includes an access mode of the image capturing device, so that the access mode of the target image capturing device can be obtained according to the video channel corresponding to the target image capturing device, and the corresponding video access platform parameters and the video channel parameters are different in different device access modes. For example, the equipment access mode is a national standard access mode, and the corresponding access platform parameters comprise an SIP user authentication ID and an access password; the video channel parameters include SIP server number, IP, port, streaming mode. The equipment access mode is a video API access party, the access platform parameters comprise a user name and a password, the video channel parameters comprise a video service IP and a port, a streaming transmission mode and the like.

Further, pulling video data collected by the target camera device and operated for the target internet of things device, including:

requesting to pull the video from the video access platform according to the video access platform parameters and the video channel parameters corresponding to the target camera equipment;

And receiving a video stream address sent by the video access platform, acquiring video data according to the video stream address, and storing the video data into a local database.

In the embodiment of the application, the self-grinding internet of things equipment sends a video pulling request for pulling video to the video access platform according to the video access platform parameter and the corresponding video channel parameter, the video access platform verifies the request according to the video access platform parameter and the corresponding video channel parameter, after verification, the video stream address of video data acquired by the target camera is sent to the self-grinding internet of things platform, the video data is acquired according to the video stream address, and the video data is stored in the local database.

Notably, in the embodiment of the application, the self-research internet of things device can synchronize the device data collected by the internet of things device and the video data collected by the camera device stored in the local database to an external system, and the external system comprises a cloud end and also comprises an external communication platform, so that the external communication platform informs relevant personnel of corresponding information.

In one example, the process of synchronizing device data and video data to an external system includes:

The self-research internet of things device uploads the device data and the video data to a file system of a cloud end, then the self-research internet of things device sends a synchronization request to an external system, and the external system acquires the synchronized device data and video data from a text system based on the synchronization request and stores the synchronized device data and video data synchronously.

In addition, the data of the external system can be synchronized to the self-research internet of things device, for example, the self-research internet of things device receives a synchronization request from the external system and acquires a synchronization file uploaded by the external system from the external file system according to the synchronization request; analyzing the synchronous file to obtain an external device table, and storing the external device table into a temporary table in a local database; the method comprises the steps of obtaining a local Internet of things device table, comparing the Internet of things device table with an external device table, and updating the Internet of things device table according to a comparison result so as to synchronize the external device to a self-research Internet of things platform; and after the equipment is synchronized, clearing the data in the temporary table, and sending a synchronization result to an external system.

For the safety and reliability of data synchronization, before receiving a synchronization request from an external system, authentication processing is needed to be performed on the external system, namely if the external system is detected to trigger the invocation of a synchronization interface, the authentication processing is performed on the external system according to an access identifier and a secret key which are distributed in advance for the external system by the Internet of things; after passing the authentication of the external system, a synchronization request from the external system is received. The synchronous interface is provided by a self-grinding internet of things platform, an access ID and a key which are pre-allocated by the internet of things are required to be used when an external system calls the synchronous interface, and when the access ID and the key which are used by the external system are consistent with the access ID and the key which are pre-allocated by the self-grinding internet of things platform, the authentication of the external system is passed, and a synchronous request is received at the moment.

Acquiring the synchronous state of the local synchronous task from a local database, determining whether an ongoing synchronous task exists at present, and acquiring the synchronous state of the local synchronous task again after a preset time period is spaced if the ongoing synchronous task exists; if the synchronous task in progress does not exist, acquiring the synchronous file uploaded by the external device from the external file system according to the synchronous request, configuring the synchronous state as a synchronous progress state, and locking the external system.

When the synchronization status indicates that there is a currently ongoing synchronization task, it is further necessary to detect a synchronization time of the task in synchronization, and further including: acquiring the synchronization time of a currently-in-progress synchronization task; if the synchronization time exceeds the preset time threshold, setting the synchronization state of the synchronization request as a synchronization acceptance failure state, and sending a result indicating the synchronization acceptance failure to an external system.

The synchronization time of the currently ongoing synchronization task may refer to a time interval from the synchronization task start time to the current time, where the synchronization task start time is a time when the synchronization file is acquired from the external file system; the synchronization time may also refer to a time interval from a time when the synchronization state of the local synchronization task is first acquired to the present.

If the synchronization time exceeds the preset time threshold, the synchronization abnormality of the currently-in-progress synchronization task is indicated, and a new synchronization request is not continuously executed, so that the synchronization state of the synchronization request of the external system is set to be a synchronization acceptance failure state, and a result indicating the synchronization acceptance failure is sent to the external system; the preset time threshold can be flexibly adjusted according to time, for example, the larger the file is, the larger the preset time threshold is, for example, the preset time threshold is 1 hour.

In addition, the synchronization process needs a certain time and resource to be executed, and the result is changed, and during the synchronous execution of the equipment, the synchronization request of the same platform is refused, so that the synchronization request initiated by the external system also carries a request parameter, the request parameter comprises a request identifier, namely a request ID, and the request ID of each synchronization request needs to be ensured to be unique; the file path indicates the synchronization file storage.

And the local database also buffers the request data of the last synchronous request of the external system, compares the synchronous request with the last synchronous request according to at least one of the request identifier and the file path, and if the synchronous request and the last synchronous request belong to the same request ID or the same group of file paths, the synchronous request which indicates that the local synchronous request is not repeated is not processed, and when the synchronous request is determined to be the non-repeated request, the synchronous state of the local synchronous task is acquired according to the local database.

In the embodiment of the application, the synchronous file is analyzed, such as extracting the device ID from the table 1, and the device information (such as the device name, the creation time, the update time and the like) of each device, an external device report is generated based on the device ID and the device information, and the external device report is stored in a temporary table in a local database, wherein the temporary table is used for temporary storage, and can automatically clear the data in the table after a certain time so as to reduce the storage resources.

In one example, the device information in the temporary table may also be purged prior to storing the external device table in the temporary table to prevent the abnormal condition from being cleared.

In the process of analyzing the synchronous file, an abnormality may exist, and in order to ensure the self-security of the self-research internet of things, the synchronous process needs to be terminated.

Before obtaining the local internet of things equipment table, the method further comprises: the method comprises the steps that equipment information of target internet of things equipment is obtained from an open source internet of things platform of a self-research internet of things platform to generate an internet of things equipment table, the internet of things equipment table is stored in a local database, if the open source internet of things platform is jetlinks, equipment information of deployed internet of things equipment can be obtained in jetlinks, the self-research internet of things equipment obtains part of the internet of things equipment, such as equipment information of gates and shielding doors, from jetlinks to generate the internet of things equipment table, and the internet of things equipment table is stored in the local database.

After the equipment is synchronized, the data in the temporary table can be cleared so as to save storage resources and make no preparation for next synchronization, and simultaneously, a synchronization result is sent to an external system, wherein the sending of the synchronization result to the external system comprises the following steps: a callback address is obtained from the synchronous request, and a synchronous result is sent to an external system according to the callback address; if the transmission of the synchronization result aiming at the synchronization request fails and the failure times are smaller than a preset time threshold, continuing to update the failure times; and repeatedly executing the step of sending the synchronization result to the external system according to the callback address until the failure times are greater than a preset time threshold.

The synchronization request further comprises a callback address, the callback address is provided by the external system and used for indicating a return address of the synchronization result, and the synchronization result can be directly sent to the external system through the callback address without being sent through a unified gateway; if the synchronous request has no callback address, the synchronous result is not required to be sent to an external system.

In an example, there is a case that the sending of the synchronization result fails, such as an external system crashes and services are disconnected, the number of times of sending failure of the synchronization result needs to be recorded, if the external system receives the synchronization result, a confirmation message is fed back to the self-research internet of things platform, and if the confirmation message is not received within a preset time, the sending failure of the synchronization result is indicated; if the failure times are smaller than the preset times threshold, continuing to update the failure times, namely the failure times are +1; the continuous failure times are smaller than the preset times threshold, the failure times can be continuously updated, or the total failure times are smaller than the preset times threshold, the failure times can be continuously updated, at the moment, the sending process of the synchronous result is repeatedly executed until the failure times are larger than the preset times threshold, and the synchronous result does not need to be sent to an external system.

In order to facilitate understanding, a data collection method based on an internet of things platform provided by the embodiment of the application is described in detail, as shown in fig. 4, the data collection system based on the internet of things platform comprises a self-grinding internet of things platform and a management platform, the management platform can perform equipment management, access management, point location management, attribute monitoring, function calling and alarm recording on the self-grinding internet of things platform, the self-grinding internet of things platform can realize video access so as to collect video data, and can also realize modbus access so as to collect equipment data. As shown in fig. 5, the self-grinding internet of things platform includes a configuration module, a device monitoring module, a data acquisition module and a video access module, and jetlinks is used as an open source internet of things platform, device attributes can be pushed to device monitoring, device attributes are pulled from the data acquisition module, video streams are pulled from the video access module, the device monitoring can call the functions of a camera, and the data acquisition module can report the device attributes to jetlinks.

Based on the fig. 4 and fig. 5, as shown in fig. 6, the point location data acquisition based on the internet of things platform includes:

S610, configuring equipment. S620, data acquisition. S630, reporting the attribute.

The administrator creates an acquisition channel through the equipment configuration module, configures channel points, binds the points with equipment attributes to complete configuration of the points, and the equipment configuration module stores the point configuration in a database of the self-research internet of things platform.

The data acquisition module starts an acquisition task at fixed time, acquires point location data (namely the equipment data) based on an acquisition point location of an acquisition channel, acquires channel configuration configured by the equipment configuration module, wherein the channel configuration comprises point location configuration and equipment point location binding information, analyzes the acquired data based on the channel configuration, and updates the analyzed point location data to a database.

And then, the data acquisition module acquires point location binding equipment attribute information from the equipment configuration module, updates equipment attributes based on the analyzed point location data, reports the updated equipment attributes to jetlinks, and pushes the equipment attributes to the equipment monitoring module jetlinks.

As shown in fig. 7, the data acquisition of S620 includes:

The data acquisition module is used for triggering an acquisition task at fixed time, acquiring channel information and point location information from the equipment configuration module, traversing the acquisition process, comparing with the last acquisition time, and when the acquisition channel is determined to be triggered, acquiring all the point locations under the acquisition channel and acquiring partial point locations under the acquisition channel, after the acquisition is completed, acquiring point location data configuration which comprises data types and data factors, further analyzing and updating the point location data based on the point location data configuration, and updating the acquisition time, such as the channel acquisition time and the point location acquisition time under the channel. In the reporting of the attribute in S630, the reporting of the attribute may be performed after the attribute number, or may be performed directly and entirely.

As shown in fig. 8, video access based on the internet of things platform includes:

s810, configuring a camera; s820, updating a video channel; s830, binding a video channel with a camera; s840, video pulling.

The administrator accesses the self-grinding internet of things platform to the video access platform through the equipment configuration module, and uses a camera access mode as an example of a fixed address to describe that a video channel needs to be configured, and the video channel also needs to be bound with a camera to complete the configuration of the video, and the equipment configuration module stores the video configuration in a database of the self-grinding internet of things platform.

The video access module is accessed into a video channel list pushed by the video access platform and is compared with the video channels in the local database so as to update the video channels of the local database and bind the updated video channels with cameras.

An administrator can select a camera through the equipment monitoring module to acquire video, and the equipment monitoring module invokes a camera video pulling function through jetlinks to realize video pulling.

As shown in fig. 9, the video pulling of S840 includes: the device monitoring module receives jetlinks the device function interface call sent by the device configuration module, obtains the device access mode from the device configuration module, and then the video access module calls the video pulling function based on the device access mode, at this time, the video access module needs to obtain parameters of the docking platform and parameters of the camera video from the database, video pulling is performed from the video platform (the video access platform) based on the parameters of the docking platform and the parameters of the camera video, the video platform returns the video stream address to the video access module, and then the video access module returns the video stream address to the administrator through jetlinks and the video monitoring module.

As shown in fig. 10, the video channel update includes: the video access module receives the video channel list push sent by the video platform, acquires the video channel list from the video platform at regular time, compares the video channel list with a local video channel, and then adds and modifies the video channel according to the comparison result, if the video channel is modified, the corresponding video channel in the local database needs to be deleted, and unbinding the video channel with the corresponding camera.

The embodiment of the device disclosed by the application is introduced herein, and the device can be used for executing the data acquisition method based on the Internet of things platform in the embodiment of the application. For details not disclosed in the embodiment of the apparatus of the present application, please refer to the embodiment of the data acquisition method based on the platform of the internet of things.

Fig. 11 is a block diagram of a data acquisition system based on an internet of things platform, according to an exemplary embodiment of the present application. The system may be applied to the implementation environment shown in fig. 1. The system may also be suitable for other exemplary implementation environments and may be specifically configured in other platforms, and the present embodiment is not limited to the implementation environment in which the system is suitable.

As shown in fig. 11, the data acquisition system based on the internet of things platform is an exemplary system; the system includes a self-lapping internet of things platform 1110, which includes a configuration module 1111, a data acquisition module 1112, and a database 1113, including:

The configuration module 1111 is used for creating an acquisition channel and configuring an acquisition point position of the acquisition channel; storing the acquisition point positions and the corresponding Internet of things equipment attributes in a local database in an associated manner;

a data acquisition module 1112, configured to acquire corresponding device data through the target acquisition point location in response to a trigger of the acquisition task; and analyzing the equipment data according to the configuration information of the target acquisition point to obtain corresponding target equipment data, and updating the equipment data corresponding to the local database according to the target equipment data.

In one embodiment of the present application, the number of the acquisition channels and the acquisition points each includes a plurality of acquisition channels and the number of the acquisition points; the data acquisition module is specifically used for triggering an acquisition task according to the last acquisition time; responding to the trigger of the acquisition task, traversing the acquisition channel to determine a target acquisition channel; traversing the acquisition point positions of the target acquisition channel, selecting part of acquisition point positions from a plurality of acquisition point positions to obtain the target acquisition point positions, and controlling the target acquisition point positions to acquire corresponding equipment data according to the preset point position acquisition time.

According to an aspect of an embodiment of the present application, the configuration information includes a data type and a data factor; the data acquisition module is specifically used for converting the data format of the equipment data according to the data type to obtain intermediate equipment data; and scaling the intermediate equipment data according to the data factor to obtain the target equipment data.

According to an aspect of the embodiment of the present application, the platform further includes an attribute reporting module, where the attribute reporting module is configured to update the attribute of the internet of things device if it is detected that the attribute of the internet of things device associated with the acquisition point is changed according to the target device data; reporting the updated internet of things device attribute to an open source internet of things platform so as to monitor the internet of things device through the open source internet of things platform according to the updated internet of things device attribute.

According to an aspect of the embodiment of the present application, the configuration module is further configured to access a video access platform, and perform binding processing between a video channel and a camera device after the video channel is locally configured; receiving a video channel list pushed by the video access platform, and comparing the video channel list with a video channel of a local database; and updating the video channel of the local database according to the comparison result, updating the binding relation between the video channel and the camera equipment based on the updated video channel, and storing the binding relation into the local database so as to access video data based on the camera equipment.

According to an aspect of the embodiment of the present application, the configuration module is specifically configured to delete a first target video channel that does not exist in the video channel list if the local database includes the first target video channel, and unbind an image capturing device bound to the first target video channel; and if the video channel list comprises a second target video channel which does not exist in the local database, binding the second target video channel with unbinding camera equipment and storing the second target video channel and the unbinding camera equipment into the local database.

According to one aspect of the embodiment of the application, the platform further comprises a calling module and a pulling module, wherein the calling module is used for responding to a calling instruction of the open source internet of things platform for target camera equipment and calling the target camera equipment according to a video channel corresponding to the target camera equipment; the call instruction is generated based on an image pickup device selection instruction of the management party, and the pulling module is used for pulling video data which is collected by the target image pickup device and runs aiming at the target Internet of things device.

According to an aspect of the embodiment of the present application, the invoking module is specifically configured to obtain the access mode of the target image capturing device according to the video channel corresponding to the target image capturing device, and obtain the video access platform parameter and the video channel parameter corresponding to the target image capturing device according to the access mode of the target image capturing device; the pulling module is specifically used for requesting to pull the video from the video access platform according to the video access platform parameters and the video channel parameters corresponding to the target camera equipment; and receiving a video stream address sent by the video access platform, acquiring the video data according to the video stream address, and storing the video data into a local database.

According to an aspect of the embodiment of the present application, the platform further includes a synchronization module, configured to synchronize device data collected by the internet of things device and video data collected by the image capturing device stored in the local database to an external system, where the external system includes a cloud.

It should be noted that, the data collection system based on the internet of things platform provided in the foregoing embodiment and the data collection method based on the internet of things platform provided in the foregoing embodiment belong to the same concept, where the specific manner in which each module and unit perform the operation has been described in detail in the method embodiment, and will not be described herein again.

In practical application, the data acquisition system based on the internet of things platform provided in the above embodiment may allocate the functions to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above, which is not limited herein.

The embodiment of the application also provides electronic equipment, which comprises: one or more processors; and the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the electronic equipment realizes the data acquisition method based on the Internet of things platform provided in each embodiment.

Fig. 12 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application. It should be noted that, the computer system 1200 of the electronic device shown in fig. 12 is only an example, and should not bring any limitation to the function and the application scope of the embodiment of the present application, where the electronic device may be configured in the self-research internet of things platform to implement the data collection method described above.

As shown in fig. 12, the computer system 1200 includes a central processing unit (Central Processing Unit, CPU) 1201 that can perform various appropriate actions and processes, such as performing the methods in the above-described embodiments, according to a program stored in a Read-Only Memory (ROM) 1202 or a program loaded from a storage section 1208 into a random access Memory (Random Access Memory, RAM) 1203. In the RAM 1203, various programs and data required for the system operation are also stored. The CPU 1201, ROM 1202, and RAM 1203 are connected to each other through a bus 1204. An Input/Output (I/O) interface 1205 is also connected to bus 1204.

The following components are connected to the I/O interface 1205: an input section 1206 including a keyboard, a mouse, and the like; an output portion 1207 including a Cathode Ray Tube (CRT), a Liquid crystal display (Liquid CRYSTAL DISPLAY, LCD), and a speaker, etc.; a storage section 1208 including a hard disk or the like; and a communication section 1209 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 1209 performs communication processing via a network such as the internet. The drive 1210 is also connected to the I/O interface 1205 as needed. A removable medium 1211 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on the drive 1210 so that a computer program read out therefrom is installed into the storage section 1208 as needed.

In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication portion 1209, and/or installed from the removable media 1211. When executed by a Central Processing Unit (CPU) 1201, performs the various functions defined in the system of the present application.

It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), a flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.

Another aspect of the present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a data collection method based on the internet of things platform as before. The computer-readable storage medium may be included in the electronic device described in the above embodiment or may exist alone without being incorporated in the electronic device.

Another aspect of the application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the data acquisition method based on the internet of things platform provided in the above embodiments.

The foregoing is merely illustrative of the preferred embodiments of the present application and is not intended to limit the embodiments of the present application, and those skilled in the art can easily make corresponding variations or modifications according to the main concept and spirit of the present application, so that the protection scope of the present application shall be defined by the claims.

Claims

1. The data acquisition method based on the internet of things platform is characterized by being applied to the self-grinding internet of things platform, and comprises the following steps:

creating an acquisition channel and configuring an acquisition point position of the acquisition channel;

storing the acquisition point positions and the corresponding Internet of things equipment attributes in a local database in an associated manner;

responding to the trigger of the acquisition task, and acquiring corresponding equipment data through a target acquisition point position;

and analyzing the equipment data according to the configuration information of the target acquisition point to obtain corresponding target equipment data, and updating the equipment data corresponding to the local database according to the target equipment data.

2. The method of claim 1, wherein the number of acquisition channels and acquisition sites each comprise a plurality of; the responding to the triggering of the acquisition task, the corresponding equipment data is acquired through the target acquisition point position, and the method comprises the following steps:

triggering an acquisition task according to the last acquisition time;

traversing the acquisition point positions of the target acquisition channel, selecting part of acquisition point positions from a plurality of acquisition point positions to obtain the target acquisition point positions, and controlling the target acquisition point positions to acquire corresponding equipment data according to the preset point position acquisition time.

3. The method of claim 1, wherein the configuration information includes a data type and a data factor; the analyzing the device data according to the configuration information of the target acquisition point to obtain corresponding target device data includes:

Converting the data format of the equipment data according to the data type to obtain intermediate equipment data;

and scaling the intermediate equipment data according to the data factor to obtain the target equipment data.

4. The method of claim 1, wherein after updating the device data corresponding to the local database according to the target device data, the method further comprises:

If the attribute change of the Internet of things equipment associated with the acquisition point is detected according to the target equipment data, updating the attribute of the Internet of things equipment;

reporting the updated internet of things device attribute to an open source internet of things platform so as to monitor the internet of things device through the open source internet of things platform according to the updated internet of things device attribute.

5. The method according to any one of claims 1 to 4, further comprising:

Accessing a video access platform, and carrying out binding processing of the video channel and the camera equipment after the video channel is locally configured;

receiving a video channel list pushed by the video access platform, and comparing the video channel list with a video channel of a local database;

and updating the video channel of the local database according to the comparison result, updating the binding relation between the video channel and the camera equipment based on the updated video channel, and storing the binding relation into the local database so as to access video data based on the camera equipment.

6. The method according to claim 5, wherein updating the video channel of the local database according to the comparison result, updating the binding relationship between the video channel and the image capturing apparatus based on the updated video channel, and storing the updated binding relationship in the local database, comprises:

if the local database comprises a first target video channel which does not exist in the video channel list, deleting the first target video channel, and unbinding the image pickup equipment bound with the first target video channel;

And if the video channel list comprises a second target video channel which does not exist in the local database, binding the second target video channel with unbinding camera equipment and storing the second target video channel and the unbinding camera equipment into the local database.

7. The method of claim 5, wherein after the updating the binding relationship between the video channel and the image capturing device based on the updated video channel and storing the binding relationship in the local database, the method further comprises:

Responding to an open source internet of things platform to send a call instruction for target camera equipment, and calling the target camera equipment according to a video channel corresponding to the target camera equipment; the call instruction is generated based on an image pickup apparatus selection instruction of the management party;

8. The method of claim 7, wherein the invoking the target image capturing device according to the video channel corresponding to the target image capturing device comprises:

acquiring a target camera equipment access mode according to a video channel corresponding to the target camera equipment, and acquiring a video access platform parameter and a video channel parameter corresponding to the target camera equipment according to the target camera equipment access mode;

Pulling video data collected by the target camera device and operated aiming at the target internet of things device, wherein the video data comprises:

Requesting to pull a video from the video access platform according to the video access platform parameters and the video channel parameters corresponding to the target camera equipment;

And receiving a video stream address sent by the video access platform, acquiring the video data according to the video stream address, and storing the video data into a local database.

9. The method of claim 1, wherein after updating the device data corresponding to the local database according to the target device data, the method further comprises:

And synchronizing the equipment data acquired by the Internet of things equipment and the video data acquired by the camera equipment stored in the local database to an external system, wherein the external system comprises a cloud.

10. The utility model provides a data acquisition system based on thing networking platform, its characterized in that, the system includes from lapping thing networking platform, from lapping thing networking platform includes configuration module, data acquisition module to and the database, include:

The configuration module is used for creating an acquisition channel and configuring acquisition points of the acquisition channel; storing the acquisition point positions and the corresponding Internet of things equipment attributes in a local database in an associated manner;

the data acquisition module is used for responding to the trigger of the acquisition task and acquiring corresponding equipment data through the target acquisition point position; and analyzing the equipment data according to the configuration information of the target acquisition point to obtain corresponding target equipment data, and updating the equipment data corresponding to the local database according to the target equipment data.