A fast search method for IoT data

Abstract

The present invention discloses a method for quickly searching for Internet of Things data, relates to the technical field of data management query, and improves the retrieval efficiency of Internet of Things data. The present invention sets a plurality of device data nodes and dynamic target data nodes, connects each device data node and dynamic target data node according to the correlation between device operation data and target state data to obtain a corresponding event execution record data tree, sets an association annotation between device operation data and target state data with abnormal data annotation, and then integrates all event execution record data trees to obtain a scene data association network, retrieves a plurality of event execution record data trees from the scene data association network according to a data index request, and then prunes and integrates each event execution record data tree according to the location of the data fragment with the association annotation and the data index request.

Description

Technical Field

[0001] The present invention relates to the technical field of data management query, and in particular to a method for quickly searching for Internet of Things data. Background Art

[0002] With the rapid development of the Internet of Things, the number of connected devices has increased dramatically, generating a massive amount of sensor data. The data in the Internet of Things system is usually high-frequency, real-time and diverse, which makes it particularly important to store and query the data effectively. Traditional data processing and storage methods often cannot meet the real-time and accuracy requirements in the Internet of Things environment.

[0003] Existing IoT data technology has the following defects:

[0004] Inadequate index structure: The index structure in existing methods may not be flexible enough to efficiently support multi-dimensional queries, resulting in degraded performance when facing complex queries.

[0005] Real-time issues: Many IoT applications require real-time data processing, but existing technologies may not meet real-time requirements in terms of response time and data update, thus affecting the overall performance of the system.

[0006] Data redundancy and duplicate storage: IoT devices generate a huge amount of data, which often leads to data redundancy and duplicate storage problems, resulting in reduced query efficiency and waste of storage resources.

[0007] Therefore, how to improve the retrieval efficiency of IoT data while performing IoT data retrieval scheduling based on time dimension scheduling is a difficulty in the prior art. For this purpose, a method for quickly searching IoT data is provided. Summary of the invention

[0008] In order to solve the above technical problems, the purpose of the present invention is to provide a method for quickly searching Internet of Things data.

[0009] In order to achieve the above object, the present invention provides the following technical solutions:

[0010] A method for quickly searching for IoT data comprises the following steps:

[0011] Step S1: Set multiple sensors for each functional device and target execution object in the application scenario, and set several scenario operation events and corresponding event execution instructions, and then collect the device operation data and target state data of the functional device and target execution object during the execution process of each event execution instruction, and integrate all the device operation data and target state data to generate an event execution record data set of the corresponding event execution instruction;

[0012] Step S2: obtaining the normal device operation data or normal target state data interval of each functional device and target execution object under each scenario operation event according to the event execution record data set, and then setting abnormal data annotation for the data in the event execution record data set according to each normal operation data interval of the functional device;

[0013] Step S3, setting a number of device data nodes and dynamic target data nodes, connecting each device data node and dynamic target data node to obtain a corresponding event execution record data tree according to the correlation between the device operation data and the target state data in the event execution record data set, and setting a correlation annotation between the device operation data with abnormal data annotation and the target state data, and then integrating all event execution record data trees to obtain a scene data association network;

[0014] Step S4: The user uploads a data index request, and according to the data index request, several event execution record data trees are retrieved from the scene data association network. Then, according to the location of the data fragments with associated annotations and the data index request, each event execution record data tree is pruned and integrated, and the pruned and integrated event execution record data tree is sent to the user.

[0015] Furthermore, the event execution instruction includes the scene running event name, the target execution object, and the type name and quantity of the execution function device.

[0016] Furthermore, the process of generating the event execution record data set includes:

[0017] Setting a number for each functional device, and then judging whether the current type and quantity of functional devices of the corresponding type in the application scenario meet the conditions for executing the corresponding event execution instruction according to the type and quantity of the functional devices in the event execution instruction, and sending the event execution instruction to the corresponding functional device according to the judgment result, so that each functional device mutually confirms the event execution instruction to be jointly executed through the wireless communication device;

[0018] During the process of the functional device executing the event execution instruction, each sensor located on the functional device collects the device operation data of the functional device and the target state data of the target execution object interacting with the functional device;

[0019] During the execution of the event execution instruction, whenever the relevant functional devices interact, each sensor on the corresponding functional device generates device operation data and target state data at its current time node, and sets the functional device number for interaction;

[0020] The execution of the current event execution instruction is completed, and the device operation data and target status data generated by each sensor on the functional device related to the event execution instruction are integrated to obtain the event execution record data set, and the execution start and end time of the corresponding event execution instruction are marked on the event execution record data set.

[0021] Furthermore, the process of acquiring the normal equipment operation data or the normal target state data interval includes:

[0022] Each target state data is divided into several data segments, the data segments in the same time sequence are normally distributed to obtain the normal data segment intervals in each time sequence, and the normal data segment intervals in each time sequence are sequentially connected to obtain the normal target state data interval;

[0023] The process of generating normal target state data intervals is adopted to obtain normal device operation data intervals for each type of device operation data, and the process of obtaining normal target state data intervals and normal device operation data intervals is repeated to obtain normal device operation data intervals for various device operation data of various functional devices under various scenario operation events, as well as normal target state data intervals for various target state data of various target execution objects.

[0024] Furthermore, the process of setting abnormal data annotation for the data in the event execution record data set includes:

[0025] Then, each data in each event execution record data set is compared with the corresponding normal target state data interval or normal equipment operation data interval. If there is a fragment of the data that is not in the corresponding normal target state data interval or normal equipment operation data interval, an abnormal data annotation is set in the corresponding event execution record data set to mark the corresponding data fragment, otherwise no operation is performed.

[0026] Furthermore, the process of establishing the event execution record data tree includes:

[0027] According to the functional device numbers and target execution object types corresponding to each data in the event execution record data set, several device data nodes and one dynamic target data node are established;

[0028] The operation data of each device is stored in the corresponding device data node, and a directed connection line is set between the corresponding device data nodes according to the time node when the operation data of each device carries the number of other functional devices;

[0029] At the same time, the target state data is input into the dynamic target data node, and then according to the functional device number associated with the target execution object at each time node, a time connection line is set between the dynamic target data node and each device data node, so as to obtain the event execution record data tree corresponding to the event execution instruction.

[0030] Furthermore, the process of establishing the scene data association network includes:

[0031] Setting a time interval threshold, determining whether the time interval between a data segment with abnormal data annotation in the target status data or the equipment operation data and a data segment with abnormal data annotation in the equipment operation data or the target status data is less than or equal to the time interval threshold, and setting an associated annotation between the corresponding data segments with abnormal data annotation according to the determination result;

[0032] Setting up a scene data association network, mapping each device data node to the scene data association network according to the actual position distribution of each functional device in the application scene at different time nodes, and setting a scene time axis in the scene data association network so that the distribution of each device data node in the scene data association network changes with the time change on the scene time axis;

[0033] According to the distribution status of device data nodes in the scene data association network, each event execution record data tree is mapped in the scene data management network.

[0034] Furthermore, the process of retrieving a plurality of event execution record data trees from the scene data association network according to the data index request includes:

[0035] Extract the corresponding event execution record data tree from the scene data association network according to the index subject in the data index request, and then directly remove irrelevant device data nodes or target data nodes from the event execution record data tree according to the index restriction condition, or remove irrelevant device operation data or target status data in the device data node or target data node;

[0036] At the same time, in the process of removing irrelevant data from the event execution record data tree, it is determined whether the data expected to be retained in the current event execution record data tree has a data segment with an abnormal data annotation. If there is a data segment with an abnormal data annotation, it is determined again whether the corresponding data segment has an associated annotation. If it is determined to have an associated annotation, in the subsequent process of removing irrelevant data, the data segment associated with the corresponding data segment is forcibly retained, otherwise no operation is performed;

[0037] If there is no data segment with abnormal data annotation, continue to remove irrelevant data;

[0038] After the operation of obtaining and eliminating irrelevant data from the scene data association network according to the data index request is completed, the entire event execution record data tree is sent to the corresponding user.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention sets a plurality of device data nodes and dynamic target data nodes, connects each device data node and dynamic target data node to obtain a corresponding event execution record data tree according to the correlation between device operation data and target status data in the event execution record data set, sets association annotations between device operation data and target status data with abnormal data annotations, and then integrates all event execution record data trees to obtain a scene data association network. A user uploads a data index request, and according to the data index request, a plurality of event execution record data trees are retrieved from the scene data association network, and then according to the location of the data fragment with the association annotation and the data index request, each event execution record data tree is pruned and integrated, thereby realizing the improvement of the retrieval efficiency of the Internet of Things data while performing Internet of Things data retrieval scheduling based on the time dimension scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention.

[0042] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0043] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0044] Embodiment 1: as Figure 1 As shown, a method for quickly searching for IoT data includes the following steps:

[0045] Step S1: Set multiple sensors for each functional device and target execution object in the application scenario, and set several scenario operation events and corresponding event execution instructions, and then collect the device operation data and target state data of the functional device and target execution object during the execution process of each event execution instruction, and integrate all the device operation data and target state data to generate an event execution record data set of the corresponding event execution instruction;

[0046] Step S2: obtaining the normal device operation data or normal target state data interval of each functional device and target execution object under each scenario operation event according to the event execution record data set, and then setting abnormal data annotation for the data in the event execution record data set according to each normal operation data interval of the functional device;

[0047] Step S3, setting a number of device data nodes and dynamic target data nodes, connecting each device data node and dynamic target data node to obtain a corresponding event execution record data tree according to the correlation between the device operation data and the target state data in the event execution record data set, and setting a correlation annotation between the device operation data with abnormal data annotation and the target state data, and then integrating all event execution record data trees to obtain a scene data association network;

[0048] Step S4: The user uploads a data index request, and according to the data index request, several event execution record data trees are retrieved from the scene data association network. Then, according to the location of the data fragments with associated annotations and the data index request, each event execution record data tree is pruned and integrated, and the pruned and integrated event execution record data tree is sent to the user.

[0049] Embodiment 2: This embodiment is a further limitation of Embodiment 1, and the step S1 is implemented by the following process:

[0050] Set a number for each functional device in the application scenario 1 、a 2 、a 3 ,……,a n , and set various sensors and wireless communication devices for each functional device, such as temperature sensors, pressure sensors, etc., where n is a natural number greater than 0;

[0051] It should be noted that the types of sensors set for different types of functional equipment are not exactly the same. For example, when the application scenario is a factory, the functional equipment includes product processing equipment, material handling equipment, etc., then the types of sensors set for product processing equipment include cameras, pressure sensors, temperature sensors, etc., and the types of sensors set for material handling equipment include laser sensors, pressure sensors, etc.;

[0052] Set a number of scenario operation events according to the application scenario type, including product processing, object handling, product packaging, etc.;

[0053] The user uploads an event execution instruction, which includes the name of the scenario running event, the target execution object, and the type and quantity of the execution function equipment, where the target execution object includes processed raw materials, processed products, etc.;

[0054] The event target may include the starting location of the target execution object and the execution result target, wherein the execution result target may be the execution result location or shape of the target execution object.

[0055] Furthermore, whenever a user uploads a new event execution instruction, based on the type and quantity of the execution function devices in the event execution instruction, it is determined whether the corresponding type and quantity of the function devices of the current application scenario meet the conditions for executing the corresponding event execution instruction. If the execution conditions are not met, the corresponding event execution instruction is temporarily executed;

[0056] If the execution conditions are met, the event execution instruction is sent to the corresponding functional device, and then each functional device mutually confirms the event execution instruction to be jointly executed through the wireless communication device;

[0057] During the process of the functional device executing the event execution instruction, each sensor located on the functional device collects the device operation data of the functional device and the target state data of the target execution object interacting with the functional device. It should be noted that multiple event execution instructions can be executed in parallel in the application scenario;

[0058] During the execution of the event execution instruction, whenever the relevant functional devices interact, each sensor on the corresponding functional device generates device operation data and target state data at its current time node, and sets the functional device number for interaction;

[0059] The execution of the current event execution instruction is completed, and the device operation data and target status data generated by each sensor on the functional device related to the event execution instruction are integrated to obtain the event execution record data set, and the execution start and end time of the corresponding event execution instruction are marked on the event execution record data set.

[0060] Embodiment 3: This embodiment is a further limitation of Embodiment 1, and step S2 is implemented by the following process:

[0061] Extract all target state data from the event execution record data set corresponding to the same scenario running event, establish a multi-dimensional coordinate system, and then map the same target state data onto the multi-dimensional coordinate system;

[0062] Each target state data is divided into several data segments, and the data segments with the same time sequence are normally distributed. Then, starting from the center position of the normal distribution result, 25% of the left and right parts relative to the normal part are selected as the normal data segment interval under the corresponding time sequence;

[0063] Then, the normal data segment intervals in each time sequence are connected in sequence to obtain the normal target state data interval of the corresponding type of target state data;

[0064] The process of generating normal target state data intervals is adopted to obtain normal device operation data intervals for each type of device operation data, and the process of obtaining normal target state data intervals and normal device operation data intervals is repeated to obtain normal device operation data intervals for various device operation data of various functional devices under various scenario operation events, as well as normal target state data intervals for various target state data of various target execution objects.

[0065] Then, each data in each event execution record data set is compared with the corresponding normal target state data interval or normal equipment operation data interval. If the data has a segment that is not in the corresponding normal target state data interval or normal equipment operation data interval, an abnormal data annotation is set in the corresponding event execution record data set to annotate the corresponding data segment;

[0066] If all the data are within the corresponding normal target state data range or normal equipment operation data range, no operation is performed.

[0067] Embodiment 4: This embodiment is a further limitation of Embodiment 1, and step S3 is implemented by the following process:

[0068] Extract all equipment operation data and execution status data from the event execution record data set, and establish several equipment data nodes and a dynamic target data node according to the functional equipment number and target execution object type corresponding to each data item, and then mark each equipment data node with the corresponding functional equipment number;

[0069] The operation data of each device in the event execution record data set are stored in the corresponding device data node according to the corresponding functional device, and directed connection lines are set between the corresponding device data nodes according to the time nodes when the operation data of each device carries other functional device numbers, wherein the direction of the directed connection line indicates the direction in which the corresponding functional device performs the target execution object interaction, and the time nodes when the corresponding functional device performs the interaction are marked on the directed connection line;

[0070] It should be noted that, for any event execution record data set, there may be multiple directed connection lines set between two device data nodes;

[0071] At the same time, the target state data in the event execution record data set is input into the dynamic target data node, and then according to the functional device number associated with the target execution object at each time node, a time-effect connection line is set between the dynamic target data node and each device data node, so that the dynamic target data node is dynamically connected or disconnected with each device data node as time changes, and then the event execution record data tree corresponding to the event execution instruction is obtained;

[0072] The time-effect connection line is provided with a display time segment, wherein the display time segment is equal to the time segment of the interaction between the target execution object and the corresponding functional device;

[0073] Sort the target state data and equipment operation data in the dynamic target data node and the equipment data node in chronological order when there is a time-effect connection line, and set the time interval threshold;

[0074] Then, it is determined whether the time interval value between the data segment with abnormal data annotation in the target state data or the equipment operation data and the data segment with abnormal data annotation in the equipment operation data or the target state data is less than or equal to the time interval threshold;

[0075] If it is less than or equal to, then set the associated annotation between the corresponding data segments with abnormal data annotations; if it is greater than, then do nothing.

[0076] Furthermore, a scene data association network is set up, and according to the actual position distribution of each functional device in the application scene at different time nodes, each device data node is mapped to the scene data association network, and a scene time axis is set in the scene data association network, so that the distribution of each device data node in the scene data association network changes with the time change on the scene time axis;

[0077] According to the distribution of device data nodes in the scene data association network, the event execution record data tree of each event execution instruction is mapped to the scene data management network, and then the device data nodes and the data in the device data nodes in the scene data association network are integrated so that for any time node on the scene timeline, the corresponding time of each device data node and the data in the device data node is the same and consistent.

[0078] Embodiment 5: This embodiment is a further limitation of Embodiment 1, and step S4 is implemented by the following process:

[0079] A user uploads a data index request, which includes one or more index subjects and several index limiting conditions;

[0080] The index subject may be, for example, a scene running event name, a functional device number, a target execution object name, etc., and the index limiting conditions may be, for example, time, data type, data feature (e.g., abnormal data fragment), etc.;

[0081] Then, according to the index subject in the data index request, the corresponding event execution record data tree is extracted from the scene data association network, and then according to the index restriction condition, irrelevant device data nodes or target data nodes are directly removed from the event execution record data tree, or irrelevant device operation data or target status data in the device data nodes or target data nodes are removed;

[0082] At the same time, in the process of removing irrelevant data from the event execution record data tree, it is determined whether the data expected to be retained in the current event execution record data tree has a data segment with an abnormal data annotation. If there is a data segment with an abnormal data annotation, it is determined again whether the corresponding data segment has an associated annotation. If it is determined to have an associated annotation, in the subsequent process of removing irrelevant data, the data segment associated with the corresponding data segment is forcibly retained, otherwise no operation is performed;

[0083] If there is no data segment with abnormal data annotation, continue to remove irrelevant data;

[0084] After the operation of obtaining and eliminating irrelevant data from the scene data association network according to the data index request is completed, the entire event execution record data tree is sent to the corresponding user.

[0085] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for quickly searching for Internet of Things data, characterized in that: The following steps are involved: Step S1: Set multiple sensors for each functional device and target execution object in the application scenario, and set several scenario operation events and corresponding event execution instructions, and then collect the device operation data and target status data during the execution process of each event execution instruction, and integrate all the device operation data and target status data to generate an event execution record data set of the corresponding event execution instruction; Step S2: obtaining the normal device operation data or normal target state data interval of each functional device and target execution object under each scenario operation event according to the event execution record data set, and then setting abnormal data annotation for the data in the event execution record data set according to each normal operation data interval of the functional device; Step S3, setting a number of device data nodes and dynamic target data nodes, connecting each device data node and dynamic target data node to obtain a corresponding event execution record data tree according to the correlation between the device operation data and the target state data in the event execution record data set, and setting a correlation annotation between the device operation data with abnormal data annotation and the target state data, and then integrating all event execution record data trees to obtain a scene data association network; The process of establishing the event execution record data tree includes: According to the functional device numbers and target execution object types corresponding to each data in the event execution record data set, several device data nodes and one dynamic target data node are established; The operation data of each device is stored in the corresponding device data node, and a directed connection line is set between the corresponding device data nodes according to the time node when the operation data of each device carries the number of other functional devices; The direction of the directed connection line indicates the direction in which the corresponding functional device performs the target execution object interaction, and the time node of the corresponding functional device performing the interaction is marked on the directed connection line; At the same time, the target state data is input into the dynamic target data node, and then according to the functional device number associated with the target execution object at each time node, a time-effect connection line is set between the dynamic target data node and each device data node, so as to obtain the event execution record data tree corresponding to the event execution instruction; The time-effect connection line is provided with a display time segment, wherein the display time segment is equal to the time segment of the target execution object interacting with the corresponding functional device; The process of establishing the scene data association network includes: Setting a time interval threshold, determining whether the time interval between a data segment with abnormal data annotation in the target status data or the equipment operation data and a data segment with abnormal data annotation in the equipment operation data or the target status data is less than or equal to the time interval threshold, and setting an associated annotation between the corresponding data segments with abnormal data annotation according to the determination result; Setting up a scene data association network, mapping each device data node to the scene data association network according to the actual position distribution of each functional device in the application scene at different time nodes, and setting a scene time axis in the scene data association network so that the distribution of each device data node in the scene data association network changes with the time change on the scene time axis; According to the distribution status of device data nodes in the scene data association network, each event execution record data tree is mapped in the scene data management network; Step S4: The user uploads a data index request, and according to the data index request, several event execution record data trees are retrieved from the scene data association network. Then, according to the location of the data fragments with associated annotations and the data index request, each event execution record data tree is pruned and integrated, and the pruned and integrated event execution record data tree is sent to the user.

2. A method for quickly searching for Internet of Things data according to claim 1, characterized in that: The event execution instruction includes the scene running event name, the target execution object, and the type name and quantity of the execution function equipment.

3. A method for quickly searching for Internet of Things data according to claim 2, characterized in that: The process of generating the event execution record data set includes: Set a number for each functional device, and then judge whether the current type and quantity of functional devices of the corresponding type in the application scenario meet the conditions for executing the corresponding event execution instruction according to the type and quantity of the execution functional devices in the event execution instruction, and send the event execution instruction to the corresponding functional device according to the judgment result; During the process of the functional device executing the event execution instruction, each sensor located on the functional device collects the device operation data of the functional device and the target state data of the target execution object interacting with the functional device; During the execution of the event execution instruction, whenever the relevant functional devices interact, each sensor on the corresponding functional device generates device operation data and target state data at its current time node, and sets the functional device number for interaction; The execution of the current event execution instruction is completed, and the device operation data and target status data generated by each sensor on the functional device related to the event execution instruction are integrated to obtain the event execution record data set, and the execution start and end time of the corresponding event execution instruction are marked on the event execution record data set.

4. A method for quickly searching for Internet of Things data according to claim 3, characterized in that: The process of obtaining the normal equipment operation data or the normal target state data interval includes: Each target state data is divided into several data segments, the data segments in the same time sequence are normally distributed to obtain the normal data segment intervals in each time sequence, and the normal data segment intervals in each time sequence are sequentially connected to obtain the normal target state data interval; By adopting the process of generating normal target state data intervals, normal device operation data intervals of various device operation data of various functional devices under various scenario operation events and normal target state data intervals of various target state data of various target execution objects are obtained.

5. A method for quickly searching for Internet of Things data according to claim 4, characterized in that: The process of setting abnormal data annotation for the data in the event execution record dataset includes: Compare each data in each event execution record data set with the corresponding normal target state data interval or normal equipment operation data interval. If there is a fragment of the data that is not in the corresponding normal target state data interval or normal equipment operation data interval, set an abnormal data annotation in the corresponding event execution record data set to annotate the corresponding data fragment, otherwise do nothing.

6. A method for quickly searching for Internet of Things data according to claim 5, characterized in that: The process of retrieving several event execution record data trees from the scene data association network according to the data index request includes: Extract the corresponding event execution record data tree from the scene data association network according to the index subject in the data index request, and then directly remove irrelevant device data nodes or target data nodes from the event execution record data tree according to the index restriction condition, or remove irrelevant device operation data or target status data in the device data node or target data node; At the same time, in the process of removing irrelevant data from the event execution record data tree, it is determined whether the data expected to be retained in the current event execution record data tree has a data segment with an abnormal data annotation. If there is a data segment with an abnormal data annotation, it is determined again whether the corresponding data segment has an associated annotation. If it is determined to have an associated annotation, in the subsequent process of removing irrelevant data, the data segment associated with the corresponding data segment is forcibly retained, otherwise no operation is performed; If there is no data segment with abnormal data annotation, the operation of eliminating irrelevant data will continue. After the operation of obtaining and eliminating irrelevant data from the scene data association network according to the data index request is completed, the data tree of all event execution records will be sent to the corresponding user.

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