CN106469348B - Method and system for dynamically adjusting sensor data acquisition algorithm - Google Patents
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Abstract
The invention relates to a method and a system for dynamically adjusting a sensor data acquisition algorithm, which realize dynamic adjustment of an acquisition mode or a recognition algorithm of a sensor acquisition device based on data and a plan of a related sensor acquisition device, realize that the sensor acquisition device can be matched with external environmental conditions in real time and achieve the effect of keeping data accurate. According to the invention, the local end of the sensor acquisition device carries out pattern recognition on the acquisition mode or the recognition algorithm, the remote end carries out optimization operation with larger load, and the acquisition mode or the recognition algorithm is updated remotely on line, so that the updating efficiency is improved. And only the identification result is sent to the remote end, so that huge construction cost and difficulty in the condition of massive deployment of the sensor acquisition devices are saved. The implementation of the invention can also change the acquisition mode or the recognition algorithm of the sensor acquisition device in batches under the condition of requirement so as to meet different functional requirements on the set sensor acquisition device, and the invention is suitable for the working conditions with different requirements.
Description
Technical Field
The present invention relates to sensor algorithm updating technology, and more particularly, to a method for dynamically adjusting a sensor data acquisition algorithm and a system for dynamically adjusting a sensor data acquisition algorithm.
Background
The traditional sensor collects data by means of a unified algorithm, and under any condition, the data are collected by a fixed and unchangeable algorithm. If the installation environment and place deviate from the conditions of the generation algorithm, the acquired data and the objective real data have serious errors, the acquisition accuracy of the sensor is seriously influenced, and further the function realization of the sensor-based device system is influenced.
And whether the judgment of whether the sensor is suitable for the current environmental condition is to carry out reverse deduction on the result of the sensor-based device system so as to judge whether the original data acquired by the current sensor can accurately embody objective real data, and the process usually needs to manually carry out preliminary judgment by virtue of personal experience to determine whether a large error exists, then traces back to the sensor, and updates the acquisition mode of the sensor. The updating work is generally an off-line updating mode, so that the steps of disassembling and assembling the sensor, connecting updating optimization and the like are required, the operation is complex, and larger time cost and labor cost are required.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for dynamically adjusting a sensor data acquisition algorithm and a system for dynamically adjusting the sensor data acquisition algorithm, which can ensure that a sensor is always adapted to the current environment in real time and are convenient to optimize.
The technical scheme of the invention is as follows:
a method for dynamically adjusting a sensor data acquisition algorithm is characterized in that pattern recognition is carried out on original data acquired by a sensor acquisition device to obtain a recognition result; and comparing the recognition result with a preset plan, judging whether the recognition result has the specified defects in the plan, and if so, optimizing the acquisition mode or the recognition algorithm of the sensor acquisition device corresponding to the current recognition result according to the optimization scheme corresponding to the current defects, which is set in the plan.
Preferably, when pattern recognition is performed on raw data acquired by the sensor acquisition device, a recognition temporary value of a part of the sensor acquisition devices is obtained first, and a recognition result is obtained by comparing the recognition temporary values of the current sensor acquisition device and other sensor acquisition devices, wherein the recognition result comprises a difference value of the recognition temporary values of the current sensor acquisition device and other sensor acquisition devices.
Preferably, the optimization scheme is as follows: and optimizing the acquisition mode or the recognition algorithm of the current sensor acquisition device based on the acquired data or returned original data of the current sensor acquisition device and other sensor acquisition devices through a machine learning algorithm, and updating the acquisition mode of the current sensor acquisition device into the optimized acquisition mode or recognition algorithm.
Preferably, the identification result is sent to the remote end, and after the acquisition mode or the identification algorithm is optimized at the remote end, the optimized acquisition mode or the optimized identification algorithm is used for updating the sensor acquisition device on line.
Preferably, when the rule of the plan requires the optimization of the acquisition mode or the recognition algorithm according to the original data, the original data acquired by the sensor acquisition device is sent to the remote end, and after the remote end carries out the mode recognition and the acquisition mode or the recognition algorithm optimization, the optimized acquisition mode or the recognition algorithm is used for updating the sensor acquisition device on line.
Preferably, the method for storing the plan of cooperative work of the sensor acquisition device comprises the following manual mode or semi-automatic mode:
manual mode: manually setting a plan and taking effect after approval;
semi-automatic mode: and automatically deducing to obtain an optimized plan according to the existing plan and the current recognition result, and taking effect after manual approval.
A system for dynamically adjusting a sensor data acquisition algorithm, implementing the method for dynamically adjusting a sensor data acquisition algorithm of claim; the sensor acquisition device is connected with the original data storage device and stores the acquired original data in the original data storage device; the sensor acquisition device is connected with the pattern recognition algorithm storage device and stores the pattern recognition algorithm; the original data storage device and the pattern recognition algorithm storage device are respectively connected with the pattern recognition device, the pattern recognition device calls a pattern recognition algorithm, and pattern recognition is carried out on original data stored in the original data storage device to obtain a recognition result; the pattern recognition device sends the recognition result to the data storage device through the data transceiver, and the data storage device is connected with the plan management module and judges whether the recognition result has the specified defects in the plan; the data storage device is connected with the learning deduction module, the plan management module is connected with the learning deduction module, and the acquisition mode of the sensor acquisition device corresponding to the current identification result is optimized according to an optimization scheme corresponding to the current defects and set in the plan; the learning deduction module is connected with the data transceiver, and the optimized acquisition mode or the optimized recognition algorithm is updated to the sensor acquisition device through the data transceiver.
Preferably, the identification results of the plurality of sensor acquisition devices are sent to the same data storage device.
Preferably, when algorithm or acquisition mode optimization is needed, according to a rule of a plan, raw data acquired by one or more specific sensor acquisition devices is sent to a data storage device, an acquisition mode is optimized through a learning deduction module, and the optimized acquisition mode or identification algorithm is sent to a mode identification algorithm storage device connected with the current sensor acquisition device.
Preferably, in the rule of the plan, the acquisition mode or the recognition algorithm of the current sensor acquisition device is optimized according to the current sensor acquisition device and the original data acquired by the plurality of sensor acquisition devices before and after the current sensor acquisition device is related to the current sensor acquisition device.
Preferably, the learning deduction module optimizes the current acquisition mode or recognition algorithm of the sensor acquisition device through a machine learning algorithm or a manual modeling method, and correspondingly, the learning deduction module is a machine learning module or a model uploading module for manual modeling.
Preferably, the raw data storage device is further connected with a data transceiver, and the raw data collected by the sensor collection device is sent to the data storage device through the data transceiver.
The invention has the following beneficial effects:
the method and the system for dynamically adjusting the sensor data acquisition algorithm realize dynamic adjustment of the acquisition mode or the recognition algorithm of the sensor acquisition device based on the data and the plan of the relevant sensor acquisition device, realize that the sensor acquisition device can be matched with the external environment conditions in real time, and achieve the effect of keeping the data accurate. According to the invention, the local end of the sensor acquisition device carries out pattern recognition on the acquisition mode or the recognition algorithm, the remote end carries out optimization operation with larger load, and the acquisition mode or the recognition algorithm is updated remotely on line, so that the updating efficiency is improved. Meanwhile, only the identification result is sent to the remote end, so that huge construction cost and difficulty in the condition of massive deployment of the sensor acquisition devices are saved.
The implementation of the invention can also change the acquisition mode or the recognition algorithm of the sensor acquisition device in batches under the condition of requirement so as to meet different functional requirements on the set sensor acquisition device, and the invention is suitable for the working conditions with different requirements.
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FIG. 1 is a functional block diagram of the system for dynamically adjusting a sensor data acquisition algorithm.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The invention provides a method for dynamically adjusting a sensor data acquisition algorithm and a system for dynamically adjusting the sensor data acquisition algorithm, aiming at solving the defects that the sensor acquisition device in the prior art has a single algorithm and cannot actively adapt to the environment, so that the real-time accuracy of acquired data cannot be ensured. According to the invention, based on the data and the plan of the relevant sensor acquisition device, the acquisition mode or the recognition algorithm of the sensor acquisition device is dynamically adjusted, the sensor acquisition device can be matched with the external environment conditions in real time, and the effect of keeping the data accurate is achieved.
The invention relates to a method for dynamically adjusting a sensor data acquisition algorithm, which mainly comprises the following steps:
1) carrying out pattern recognition on original data collected by a sensor collecting device to obtain a recognition result;
2) and comparing the recognition result with a preset plan, judging whether the recognition result has specified defects in the plan (for example, the sensor acquisition devices adjacent to the current sensor acquisition device recognize a certain license plate, but the current sensor cannot be recognized accurately all the time), and if so, optimizing the acquisition mode or the recognition algorithm of the sensor acquisition device corresponding to the current recognition result according to an optimization scheme corresponding to the current defect and set in the plan.
The invention provides a system for dynamically adjusting a sensor data acquisition algorithm based on the method for dynamically adjusting the sensor data acquisition algorithm, which is used for executing the method for dynamically adjusting the sensor data acquisition algorithm; as shown in fig. 1, the sensor acquisition device is connected to the raw data storage device, and stores the acquired raw data in the raw data storage device; the sensor acquisition device is connected with the pattern recognition algorithm storage device and stores the pattern recognition algorithm; the original data storage device and the pattern recognition algorithm storage device are respectively connected with the pattern recognition device, the pattern recognition device calls a pattern recognition algorithm, and pattern recognition is carried out on original data stored in the original data storage device to obtain a recognition result; the pattern recognition device sends the recognition result to the data storage device through the data transceiver, and the data storage device is connected with the plan management module and judges whether the recognition result has the specified defects in the plan; the data storage device is connected with the learning deduction module, the plan management module is connected with the learning deduction module, and the acquisition mode or the identification algorithm of the sensor acquisition device corresponding to the current identification result is optimized according to the optimization scheme corresponding to the current defect and set in the plan; the learning deduction module is connected with the data transceiver, and the optimized acquisition mode or the optimized recognition algorithm is updated to the sensor acquisition device through the data transceiver.
In the invention, the sensor acquisition device (such as a camera) is provided with at least one data transceiver (such as a 4G communication module for wireless communication). The pattern recognition algorithm stored by the pattern recognition algorithm storage means may be updated by the data transceiving means.
In step 1), when pattern recognition is performed on the raw data acquired by the sensor acquisition device, firstly, obtaining temporary recognition values of part (such as most of all the sensor acquisition devices) of the sensor acquisition devices, and comparing the temporary recognition values of the current sensor acquisition device with those of other sensor acquisition devices to obtain a recognition result, wherein the recognition result comprises a difference value between the temporary recognition values of the current sensor acquisition device and those of other sensor acquisition devices.
The original data acquired by the sensor acquisition device is stored in an original data storage device of the sensor acquisition device, generally, only the identification result is sent to the remote end, and when the current sensor acquisition device is judged to have inaccurate acquisition and needs to be optimized according to a plan, the original data is sent to the remote end, for example, when detailed evidence collection is needed, and for example, when the identification algorithm needs to be optimized again according to the original data.
In the invention, the identification result is sent to the remote end, and after the acquisition mode or the identification algorithm is optimized at the remote end, the optimized acquisition mode or the optimized identification algorithm is used for updating the sensor acquisition device on line. In the implementation process of the invention, only the identification result is sent, and the original data does not need to be sent to the data storage device, so that the huge construction cost and difficulty in the case of massively deploying the sensor acquisition devices are saved. And then realize sending the discernment result of a plurality of sensor collection system to same data storage device, also can not have the degree of difficulty and the cost problem in the aspect of construction and operation.
The optimization scheme of the invention is as follows: and optimizing the acquisition mode or the recognition algorithm of the current sensor acquisition device based on the data acquired by the current sensor acquisition device and other sensor acquisition devices through a machine learning algorithm or manual modeling or other optimization methods, and updating the acquisition mode or the recognition algorithm of the current sensor acquisition device into the optimized acquisition mode or recognition algorithm.
When the optimization is executed, according to the rules of a plan, the original data collected by one or more specific sensor collecting devices are sent to a data storage device, the collection mode or the recognition algorithm is optimized through a learning deduction module, and the optimized collection mode or the optimized recognition algorithm is sent to a mode recognition algorithm storage device connected with the current sensor collecting device.
In implementation, which raw data of which sensor acquisition devices need to be sent is determined by the rules of the plan. The basis of the optimization may be raw data acquired by a sensor acquisition device similar to or the same as the current sensor acquisition device, that is, in implementation, the basis of the optimization is not necessarily raw data of the same sensor acquisition device, but the data of the sensor acquisition device is necessarily correlated as long as the sensor acquisition device is optimized through machine learning.
As a specific implementation, in the rule of the plan, the acquisition mode or the recognition algorithm of the current sensor acquisition device is optimized according to the raw data acquired by the current sensor acquisition device and its related front and back multiple sensor acquisition devices.
The plan management module stores the plans of the cooperative work of the related sensors in a manual, semi-automatic or automatic mode, the invention stores the plans of the cooperative work of the sensor acquisition devices in a manual or semi-automatic mode, and adopts various modes to carry out the cooperative work of the plans, so that the manual intervention can be carried out under the condition that the plan comparison work cannot be automatically completed, and the semi-automatic optimization is realized. According to the implementation requirement, the plan comparison can also be carried out in a manual mode.
Wherein, the manual mode is to manually set a plan and take effect after approval; the semi-automatic mode is to automatically deduce to obtain an optimized plan according to the existing plan and the current recognition result, and the optimized plan takes effect after being manually approved.
When the load of the sensor acquisition device on the local end needs to be relieved, the process of pattern recognition can be transferred to a remote end for carrying out, such as on a data storage device. When the method is implemented, the original data storage device is further connected with a data transceiver, and when the rule of the plan requires the optimization of the acquisition mode or the recognition algorithm according to the original data, the original data acquired by the sensor acquisition device is sent to a remote end (such as a data storage device of the remote end), namely, the original data acquired by the sensor acquisition device is sent to the data storage device through the data transceiver. And after the remote end carries out pattern recognition and acquisition pattern or recognition algorithm optimization, the optimized acquisition pattern or recognition algorithm is used for updating the sensor acquisition device on line.
Based on the idea of the invention, the method can also be applied to changing the acquisition mode or the recognition algorithm of the sensor acquisition devices in batches, and can be used for changing the function realization of all the sensor acquisition devices in a certain area. For example, in some special cases, the collection pattern or recognition algorithm of some sensor collection devices is batch updated by the protocol management module to increase the handling capacity of the sensor collection devices for special events. Specifically, for example, the function of the sensor acquisition device needs to be changed from license plate recognition to search of a certain characteristic unlicensed vehicle, the implementation of the invention can modify the algorithm of the camera which may appear in the vehicle in a short time, after the vehicle is found, other irrelevant cameras are modified to return to the original algorithm (such as full road segment coverage, the process is millisecond level), and the relevant cameras keep the algorithm to continuously track the vehicle.
In the invention, the learning deduction module can optimize the current acquisition mode or recognition algorithm of the sensor acquisition device through a machine learning algorithm or an artificial modeling method and other optimization methods, and if the machine learning algorithm or the artificial modeling method is adopted, the learning deduction module is a machine learning module or an artificial modeling model uploading module correspondingly.
The above examples are provided only for illustrating the present invention and are not intended to limit the present invention. Changes, modifications, etc. to the above-described embodiments are intended to fall within the scope of the claims of the present invention as long as they are in accordance with the technical spirit of the present invention.
Claims (10)
1. A method for dynamically adjusting a sensor data acquisition algorithm is characterized in that pattern recognition is carried out on original data acquired by a sensor acquisition device, temporary recognition values of part of the sensor acquisition devices are obtained first, the temporary recognition values of the current sensor acquisition device and other sensor acquisition devices are compared to obtain a recognition result, and the recognition result comprises a difference value of the temporary recognition values of the current sensor acquisition device and other sensor acquisition devices; and sending the recognition result to a remote end, comparing the recognition result with a preset plan, judging whether the recognition result has the specified defects in the plan, if so, carrying out acquisition mode or mode recognition algorithm optimization on the remote end according to an optimization scheme which is set in the plan and corresponds to the current defects, then carrying out online updating on the sensor acquisition device by the optimized acquisition mode or mode recognition algorithm, and optimizing the acquisition mode or mode recognition algorithm of the sensor acquisition device corresponding to the current recognition result.
2. The method of dynamically adjusting a sensor data acquisition algorithm of claim 1, wherein the optimization scheme is: and optimizing the acquisition mode or the mode recognition algorithm of the current sensor acquisition device based on the acquired data or returned original data of the current sensor acquisition device and other sensor acquisition devices through a machine learning algorithm, and updating the acquisition mode of the current sensor acquisition device into the optimized acquisition mode or the optimized mode recognition algorithm.
3. The method of claim 1, wherein when the rules of the plan require optimization of the acquisition mode or pattern recognition algorithm based on raw data, the raw data acquired by the sensor acquisition device is sent to the remote end, and after the remote end performs pattern recognition and optimization of the acquisition mode or pattern recognition algorithm, the sensor acquisition device is updated online with the optimized acquisition mode or pattern recognition algorithm.
4. The method of dynamically adjusting sensor data collection algorithms according to claim 1, wherein the method of storing the protocol of sensor collection device cooperation comprises a manual or semi-automatic mode as follows:
manual mode: manually setting a plan and taking effect after approval;
semi-automatic mode: and automatically deducing to obtain an optimized plan according to the existing plan and the current recognition result, and taking effect after manual approval.
5. A system for dynamically adjusting a sensor data acquisition algorithm, characterized by performing the method for dynamically adjusting a sensor data acquisition algorithm of any one of claims 1 to 4; the sensor acquisition device is connected with the original data storage device and stores the acquired original data in the original data storage device; the sensor acquisition device is connected with the pattern recognition algorithm storage device and stores the pattern recognition algorithm; the original data storage device and the pattern recognition algorithm storage device are respectively connected with the pattern recognition device, the pattern recognition device calls a pattern recognition algorithm, and pattern recognition is carried out on original data stored in the original data storage device to obtain a recognition result; the pattern recognition device sends the recognition result to the data storage device through the data transceiver, and the data storage device is connected with the plan management module and judges whether the recognition result has the specified defects in the plan; the data storage device is connected with the learning deduction module, the plan management module is connected with the learning deduction module, and the acquisition mode of the sensor acquisition device corresponding to the current identification result is optimized according to an optimization scheme corresponding to the current defects and set in the plan; the learning deduction module is connected with the data transceiver, and the optimized acquisition mode or the mode recognition algorithm is updated to the sensor acquisition device through the data transceiver.
6. The system for dynamically adjusting sensor data collection algorithms according to claim 5, wherein the identification results of multiple sensor collection devices are sent to the same data storage device.
7. The system for dynamically adjusting sensor data acquisition algorithms according to claim 6, wherein when algorithm or acquisition mode optimization is required, raw data acquired by a specific sensor acquisition device or devices is sent to a data storage device according to a predetermined rule, an acquisition mode is optimized through a learning and deduction module, and the optimized acquisition mode or mode recognition algorithm is sent to a mode recognition algorithm storage device connected with the current sensor acquisition device.
8. The system of claim 7, wherein the predetermined rules optimize the current sensor acquisition device acquisition mode or the pattern recognition algorithm based on the raw data acquired by the current sensor acquisition device and its associated multiple sensor acquisition devices.
9. The system for dynamically adjusting sensor data acquisition algorithms according to claim 7, wherein the learning derivation module optimizes the current acquisition mode or mode recognition algorithm of the sensor acquisition device through a machine learning algorithm or a manual modeling method, and correspondingly, the learning derivation module is a machine learning module or a manual modeling model uploading module.
10. The system for dynamically adjusting sensor data acquisition algorithms according to claim 5, wherein the raw data storage device is further connected to a data transceiver device, and raw data acquired by the sensor acquisition device is transmitted to the data storage device through the data transceiver device.
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