CN112785125A - Method and system for monitoring private automatic use behavior risk of reserved grains and early warning - Google Patents
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Abstract
本发明公开了一种用于监测储备粮私自动用行为风险及预警的方法及系统，属于粮情数据监控技术领域。本发明方法，包括：以预设的时间，采集储粮仓房的粮情数据，根据采集的情况确定储量仓房是否出现粮情数据异常；针对异常的粮情数据，调用视频数据，根据视频数据，检测粮情数据异常的时段是否出现出入仓库车辆及人员行动，若存在出入库车辆及人员行动，触发中级风险预警；调用粮食数据平台存储的粮食轮换计划，根据零食轮换计划中的轮换时间周期，建立有效连续日期集合；根据有效连续日期集合，判断是否出现储备粮私自动用行为，若出现触发高级风险报警。本发明可以有效排查潜在转圈粮行为，给实际监管工作开展提供参考依据。
The invention discloses a method and a system for monitoring the behavior risk and early warning of private use of grain reserves, belonging to the technical field of grain condition data monitoring. The method of the invention includes: collecting the grain condition data of the grain storage warehouse at a preset time, and determining whether the grain condition data is abnormal in the storage warehouse according to the collected situation; for the abnormal grain condition data, calling video data, and according to the video data, Detect whether there are vehicles and personnel moving in and out of the warehouse during the period of abnormal grain situation data. If there are vehicles and personnel moving in and out of the warehouse, a medium-level risk warning is triggered; the grain rotation plan stored in the grain data platform is called, and according to the rotation time period in the snack rotation plan, Establish a set of valid consecutive dates; according to the set of valid consecutive dates, determine whether there is unauthorized use of grain reserves, and if so, trigger an advanced risk alarm. The present invention can effectively check out potential grain rotation behaviors, and provide a reference basis for the actual supervision work.
Description
Technical Field
The invention relates to the technical field of grain condition data monitoring, in particular to a method and a system for monitoring the private automatic use behavior risk of reserved grains and early warning.
Background
The reserved grain private-use behavior refers to the situation that reserved grains which are not in the rotation period and do not have the delivery plan and are stored in the sealed warehouse are used by a reserved enterprise private opening warehouse without permission, and the stored grains are illegally used. In the daily supervision work of deposit grain, the deposit storehouse is few, and the regional span is big hardly realizes the personnel's of high frequency inspection, and the deposit enterprise sells the profit out of the storehouse with deposit grain privately at the time stage that market price is high, and low price purchase grain fills the deposit storehouse again in, when waiting for next personnel inspection, seems deposit grain still intact, but the quantity and the quality of true deposit grain can't guarantee.
Currently, there are three main bodies for national grain storage supervision, namely, intermediate grain storage, national grain administration management system and national agriculture development bank. According to the common supervision responsibility of the three parties, the three parties participate in organization and coordination when determining the reserve library point, and the common confirmation and common supervision of the three parties in the links of fixed point, starting, expense allocation, storage, statistics, supervision and the like are ensured. Wherein, the grain management system takes administrative supervision responsibility and the agricultural issuing has financial loan supervision responsibility. However, many problems still appear in the actual supervision operation, and firstly, the standards are not uniform, the unit properties of three parties are different, and the execution force is quite insufficient; secondly, the information barrier is serious, the grain industry belongs to the traditional industry, although the informatization level is improved in recent years, the situation of information chimney information isolated island still exists, the private automatic use behavior of stored grains relates to a plurality of links such as storage, logistics, collection and payment, and the like, so that a supervision institution is difficult to obtain all information and make accurate judgment; thirdly, the management cost is too high, the grain storage points need to be distributed in various cities, districts, counties and towns in the district, the geographic positions are generally scattered, and the patrol work aiming at the grain storage points is difficult to implement.
Disclosure of Invention
Aiming at the problems, the invention provides a method for monitoring the private automatic use behavior risk of reserved grains and early warning, which comprises the following steps:
collecting grain condition data of a grain storage warehouse within preset time, and determining whether the grain condition data of the storage warehouse are abnormal or not according to the collected conditions;
the video data are called according to abnormal grain condition data, whether the actions of vehicles and personnel entering and exiting the warehouse occur in the abnormal time period of the grain condition data or not is detected according to the video data, and if the actions of the vehicles and the personnel entering and exiting the warehouse exist, intermediate risk early warning is triggered;
calling a grain rotation plan stored in a grain data platform, and establishing an effective continuous date set according to a rotation time period in the snack rotation plan;
and judging whether the reserved grains are used for private automatic movement or not according to the effective continuous date set, and if so, triggering advanced risk alarm.
Optionally, the grain condition data collected from the grain storage warehouse is collected by using an internet of things gateway with a 4G or Nb-IOt communication function.
Optionally, the preset period comprises a plurality of periods.
Optionally, the grain situation data is abnormal, including:
in the process of collecting grain condition data of the grain storage warehouse, the collection fails for three times continuously, the collection fails in the same preset time period for 3 days continuously, or the lowest temperature collected for the nth time-the lowest temperature collected for the n-1 st time is more than 10 ℃, wherein n is more than 2.
Optionally, the identification accuracy of the video data is greater than 95%.
The invention also provides a system for monitoring the private automatic use behavior risk of reserved grains and early warning, which comprises the following steps:
the data acquisition unit is used for acquiring grain condition data of the grain storage warehouse in preset time and determining whether the grain condition data of the storage warehouse are abnormal or not according to the acquired condition;
the video data monitoring unit calls video data aiming at abnormal grain condition data, detects whether the actions of vehicles and personnel entering and exiting the warehouse occur in the abnormal time period of the grain condition data according to the video data, and triggers intermediate risk early warning if the actions of the vehicles and the personnel entering and exiting the warehouse occur;
the processing unit calls a grain rotation plan stored in the grain data platform and establishes an effective continuous date set according to a rotation time period in the snack rotation plan;
and the output unit judges whether the reserved grains are used for private automatic use or not according to the effective continuous date set, and if so, high-level risk alarm is triggered.
Optionally, the grain condition data collected from the grain storage warehouse is collected by using an internet of things gateway with a 4G or Nb-IOt communication function.
Optionally, the preset period comprises a plurality of periods.
Optionally, the grain situation data is abnormal, including:
in the process of collecting grain condition data of the grain storage warehouse, the collection fails for three times continuously, the collection fails in the same preset time period for 3 days continuously, or the lowest temperature collected for the nth time-the lowest temperature collected for the n-1 st time is more than 10 ℃, wherein n is more than 2.
Optionally, the identification accuracy of the video data is greater than 95%.
According to the method, potential grain circling behaviors can be effectively checked through data deposited by a business system, and a reference basis is provided for development of actual supervision work.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a block diagram of the system of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The invention provides a method for monitoring the private automatic use behavior risk of reserved grains and early warning, which comprises the following steps as shown in figure 1:
collecting grain condition data of a grain storage warehouse within preset time, and determining whether the grain condition data of the storage warehouse are abnormal or not according to the collected conditions;
the video data are called according to abnormal grain condition data, whether the actions of vehicles and personnel entering and exiting the warehouse occur in the abnormal time period of the grain condition data or not is detected according to the video data, and if the actions of the vehicles and the personnel entering and exiting the warehouse exist, intermediate risk early warning is triggered;
calling a grain rotation plan stored in a grain data platform, and establishing an effective continuous date set according to a rotation time period in the snack rotation plan;
and judging whether the reserved grains are used for private automatic movement or not according to the effective continuous date set, and if so, triggering advanced risk alarm.
Wherein, the grain condition data of the grain storage warehouse is collected by using an internet of things gateway with a 4G or Nb-IOt communication function.
Wherein the preset period comprises a plurality of periods.
Wherein, the grain situation data is unusual, include:
in the process of collecting grain condition data of the grain storage warehouse, the collection fails for three times continuously, the collection fails in the same preset time period for 3 days continuously, or the lowest temperature collected for the nth time-the lowest temperature collected for the n-1 st time is more than 10 ℃, wherein n is more than 2.
Wherein the identification accuracy of the video data is more than 95%.
The invention is further illustrated by the following examples:
based on the grain situation data, video monitoring service data and grain rotation plan record in daily production and operation of the grain depot, the risk monitoring method performs cross verification under the condition that each item of data is self-consistent and complete, thereby checking the authenticity of the grain depot service and checking the risk of private use of reserved grains.
Checking grain condition data;
the internet of things gateway with the 4G or Nb-IOt communication function is installed in a grain storage warehouse, the grain condition data of the warehouse are collected by the internet of things gateway, the gateway is used for monitoring the grain condition in the grain storage warehouse in the morning, the middle and the evening, continuous and effective grain condition monitoring is guaranteed, and if the grain condition data is interrupted or abnormal, the situation that operation possibly occurs in the grain storage warehouse, namely the situation of private automatic use is indicated. The Internet of things gateway is used for directly collecting grain conditions through wireless communication to detect, so that the situation that the grain conditions are artificially modified after being summarized to the digital grain depot system is avoided, and the covering is intentionally real-time. The following three conditions are considered as abnormal grain conditions, and primary early warning should be triggered. The date of the abnormal grain condition is the date of the abnormal grain condition.
And if the collection fails for three times, determining that the grain condition is abnormal.
If the grain condition is failed to be collected in the uniform time period for 3 consecutive days, the grain condition is considered to be abnormal
The lowest temperature of the nth collection-the lowest temperature of the nth-1 collection is more than 10 ℃, and the grain condition is considered to be abnormal
Checking video data;
video monitoring data is already standard distribution of the current digital grain depot system, and the digital grain depot system and a provincial grain supervision platform can store video clips or picture records of grain depot input depot services. And calling video data in the bin and video data outside the bin respectively, and detecting by using a vehicle identification algorithm and a human body detection algorithm.
And detecting the video monitoring outside the grain bin by using a vehicle identification algorithm, and detecting whether vehicles appear in the abnormal time period of the grain situation under the condition that the vehicle identification accuracy is over 95 percent. If the grain condition is abnormal and the vehicle appears at the same time, the grain delivery operation is likely to happen.
And detecting the video monitoring in the granary by using a human body detection algorithm, and detecting whether a person acts in the granary within an abnormal time period of the grain condition under the condition that the human body detection accuracy is over 95 percent. If the abnormal conditions occur at the same time when people move in the granary, the granary is represented to be possible to operate.
If the movement of the personnel in the granary is detected and vehicles stay outside the granary at the time of abnormal grain conditions, the possibility that the grains are used privately is indicated. And triggering intermediate early warning.
Alternately recording the stored grains;
and acquiring a grain rotation plan from the grain provincial platform by using the data crawler. According to the time period of the rotation, forming a grain rotation effective continuous date set:
foodstuff rotation effective period (XX month XX day in XX year )
The dates of grain abnormality also form a discontinuous date set:
date of abnormality in grain conditions [ XX month XX day in XX year, … ]
If it is not
Grain condition abnormal date e-grain rotation effective period
I.e. the grain exception date, is a subset of the grain rotation validity period. It shows that the grain warehouse does not need to be used by private persons when the grain warehouse does not take out the grain from the warehouse in the grain rotation period.
If it is not
Date of abnormal grain condition and period of validity of grain rotation
The obtained abnormal days of the grain condition account for more than 95 percent of the abnormal days of the grain condition, and the situation of selfishness is not existed.
If it is not
Date of abnormal grain condition and period of validity of grain rotation
The obtained abnormal grain condition days account for less than 95% of the abnormal grain condition dates, which indicates that most of the abnormal grain condition dates are beyond the rotation period and have the possibility of private use.
Comprehensively judging;
the cross verification of three types of data of comprehensive grain situation data, video data and grain rotation plans is comprehensive and multidimensional for checking the business behaviors of the grain depot.
If the video recognition algorithm is used to find that vehicles and personnel move inside and outside the granary within the date of abnormal grain conditions, and the date of abnormal grain conditions is obviously not in the condition of a reserved grain rotation period, high-level early warning is triggered.
The invention also provides a system 200 for monitoring the private automatic use behavior risk of reserved grains and early warning, as shown in fig. 2, comprising:
the data acquisition unit 201 is used for acquiring grain condition data of the grain storage warehouse in preset time and determining whether the grain condition data of the storage warehouse are abnormal or not according to the acquired condition;
the video data monitoring unit 202 calls video data according to abnormal grain situation data, detects whether the actions of vehicles and personnel entering and exiting the warehouse occur in abnormal time periods of the grain situation data according to the video data, and triggers intermediate risk early warning if the actions of the vehicles and the personnel entering and exiting the warehouse occur;
the processing unit 203 calls a grain rotation plan stored in the grain data platform, and establishes an effective continuous date set according to a rotation time period in the snack rotation plan;
and the output unit 204 judges whether the reserved grain private automatic use behavior occurs or not according to the effective continuous date set, and if so, a high-level risk alarm is triggered.
Wherein, the grain condition data of the grain storage warehouse is collected by using an internet of things gateway with a 4G or Nb-IOt communication function.
Wherein the preset period comprises a plurality of periods.
Wherein, the grain situation data is unusual, include:
in the process of collecting grain condition data of the grain storage warehouse, the collection fails for three times continuously, the collection fails in the same preset time period for 3 days continuously, or the lowest temperature collected for the nth time-the lowest temperature collected for the n-1 st time is more than 10 ℃, wherein n is more than 2.
Wherein the identification accuracy of the video data is more than 95%.
According to the method, potential grain circling behaviors can be effectively checked through data deposited by a business system, and a reference basis is provided for development of actual supervision work.
By matching with the early warning effect provided by the invention, the supervision personnel can purposefully carry out on-site supervision work and on-site patrol work, the efficiency is improved, and the cost is reduced.
The on-site supervision work efficiency is improved, the cost is reduced, limited resources are put into other convenience by a supervision mechanism, and the overall level of stored grain management work is improved.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A method for monitoring reserve grain private voluntary action risk and early warning, the method comprising:
collecting grain condition data of a grain storage warehouse within preset time, and determining whether the grain condition data of the storage warehouse are abnormal or not according to the collected conditions;
the video data are called according to abnormal grain condition data, whether the actions of vehicles and personnel entering and exiting the warehouse occur in the abnormal time period of the grain condition data or not is detected according to the video data, and if the actions of the vehicles and the personnel entering and exiting the warehouse exist, intermediate risk early warning is triggered;
calling a grain rotation plan stored in a grain data platform, and establishing an effective continuous date set according to a rotation time period in the snack rotation plan;
and judging whether the reserved grains are used for private automatic movement or not according to the effective continuous date set, and if so, triggering advanced risk alarm.
2. The method of claim 1, wherein the collecting grain condition data of the grain storage warehouse is collected by using an internet of things gateway with a 4G or Nb-IOt communication function.
3. The method of claim 1, the preset period of time comprising a plurality of periods of time.
4. The method of claim 1, the grain situation data anomaly, comprising:
in the process of collecting grain condition data of the grain storage warehouse, the collection fails for three times continuously, the collection fails in the same preset time period for 3 days continuously, or the lowest temperature collected for the nth time-the lowest temperature collected for the n-1 st time is more than 10 ℃, wherein n is more than 2.
5. The method of claim 1, the video data having a recognition accuracy greater than 95%.
6. A system for monitoring reserve grain private mobile action risk and early warning, the system comprising:
the data acquisition unit is used for acquiring grain condition data of the grain storage warehouse in preset time and determining whether the grain condition data of the storage warehouse are abnormal or not according to the acquired condition;
the video data monitoring unit calls video data aiming at abnormal grain condition data, detects whether the actions of vehicles and personnel entering and exiting the warehouse occur in the abnormal time period of the grain condition data according to the video data, and triggers intermediate risk early warning if the actions of the vehicles and the personnel entering and exiting the warehouse occur;
the processing unit calls a grain rotation plan stored in the grain data platform and establishes an effective continuous date set according to a rotation time period in the snack rotation plan;
and the output unit judges whether the reserved grains are used for private automatic use or not according to the effective continuous date set, and if so, high-level risk alarm is triggered.
7. The system of claim 6, wherein the collected grain situation data of the grain warehouse is collected by using an internet of things gateway with a 4G or Nb-IOt communication function.
8. The system of claim 6, the preset period comprising a plurality of periods.
9. The system of claim 6, the grain status data anomaly, comprising:
in the process of collecting grain condition data of the grain storage warehouse, the collection fails for three times continuously, the collection fails in the same preset time period for 3 days continuously, or the lowest temperature collected for the nth time-the lowest temperature collected for the n-1 st time is more than 10 ℃, wherein n is more than 2.
10. The system of claim 6, the video data having a recognition accuracy greater than 95%.
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| CN114548860A (en) * | 2022-01-27 | 2022-05-27 | 北京良安科技有限公司 | Granary monitoring safety protection method, granary monitoring safety protection device, granary monitoring equipment and granary monitoring safety protection medium |
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| CN114548860A (en) * | 2022-01-27 | 2022-05-27 | 北京良安科技有限公司 | Granary monitoring safety protection method, granary monitoring safety protection device, granary monitoring equipment and granary monitoring safety protection medium |
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