A bank real-time online monitoring anti-theft method and system and a storage medium thereof

Abstract

The application relates to the field of intelligent security, in particular to a bank real-time online monitoring anti-theft method and system and a storage medium thereof, which comprises the following steps: acquiring cash-out data, a cash-out signal and current cash quality data; determining an ATM machine invasion signal through the cash-out data, the cash-out signal and a preset cash-out judgment threshold value, and outputting the signal to a user; determining current cash data through the current cash quality data and a preset single-cash quality threshold value; determining a stolen cash signal through the current cash data, a preset residual cash data and a preset environment deviation threshold value, and outputting the signal to the user; and determining new residual cash data through the original residual cash data and the cash-out data, and replacing the original residual cash data. The application has the effects of precision, rapidness and automatic realization of intelligent anti-theft.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent security, in particular to a bank real-time online monitoring anti-theft method and system and a storage medium thereof. BACKGROUND

[0002] China has a large population and a vast territory, so there are a large number of ATMs to facilitate people to take cash, but because the number of ATMs is large and widely distributed, it is difficult to arrange personnel for security, so a large number of ATMs are unattended and can only be monitored through monitoring, which provides an opportunity for speculators to steal cash from ATMs. Once the cash in the ATM is stolen, if the local security is not notified in time, it is difficult to recover the money, and the cash in the bank mostly belongs to the users of the deposit, and the un-recovered money is easy to cause the cash in the bank to be less than the stored amount of data, thereby causing bad debts and affecting the bank's reputation. Once the bank counter appears a case of holding a knife to threaten the teller or even robbing the bank, it is also easy to cause bad debts, and because the staff are controlled, it is difficult for the staff in the bank to pass the information to the outside world, so it is difficult for the outside world to quickly discover the situation, and therefore it is urgent to develop a fast, accurate and automatic intelligent anti-theft system. SUMMARY

[0003] In order to improve the problem that the stolen or robbed cash in the bank is difficult to be discovered in time, the present application provides a bank real-time online monitoring anti-theft method, system and storage medium thereof.

[0004] The bank real-time online monitoring anti-theft method provided by the present application adopts the following technical scheme:

[0005] A bank real-time online monitoring anti-theft method, comprising:

[0006] obtaining dispensing data, dispensing signals and current cash quality data;

[0007] determining an ATM intrusion signal through the dispensing data, the dispensing signals and a preset dispensing judgment threshold, and outputting to a user;

[0008] determining current cash data through the current cash quality data and a preset single cash quality threshold;

[0009] determining a stolen cash signal through the current cash data, a preset remaining cash data and a preset environmental deviation threshold, and outputting to a user;

[0010] determining new remaining cash data through the original remaining cash data and the dispensing data, and replacing the original remaining cash data.

[0011] By adopting the technical scheme, whether the ATM is invaded is automatically judged according to the working state of the ATM, and the corresponding ATM invasion signal and stolen cash signal are output, so that the probability that the external monitoring camera is found by the lawbreaker and then shielded to be invalid is reduced, the state of the cash is directly detected, the intelligent degree is improved, and intelligent theft prevention is more accurate and effective.

[0012] Optionally, further comprising:

[0013] acquiring time data;

[0014] determining automatic dispensing speed data according to the current cash data and the time data;

[0015] determining an abnormal dispensing signal according to the automatic dispensing speed data and a preset dispensing speed threshold value, and outputting the abnormal dispensing signal to a user.

[0016] By adopting the technical scheme, whether the ATM is invaded is automatically judged according to the working state of the ATM, and the corresponding ATM invasion signal and stolen cash signal are output, so that the probability that the external monitoring camera is found by the lawbreaker and then shielded to be invalid is reduced, the state of the cash is directly detected, the intelligent degree is improved, and intelligent theft prevention is more accurate and effective.

[0017] Optionally, further comprising:

[0018] The current cash quality data is multiple;

[0019] determining centroid coordinate data according to the multiple current cash quality data and a preset cash distribution coordinate threshold value;

[0020] determining coordinate offset data according to the time data, the automatic dispensing speed data and the centroid coordinate data;

[0021] determining the abnormal dispensing signal according to the coordinate offset data and a preset coordinate offset threshold value and outputting the abnormal dispensing signal.

[0022] By adopting the technical scheme, whether the ATM is invaded is automatically judged according to the working state of the ATM, and the corresponding ATM invasion signal and stolen cash signal are output, so that the probability that the external monitoring camera is found by the lawbreaker and then shielded to be invalid is reduced, the state of the cash is directly detected, the intelligent degree is improved, and intelligent theft prevention is more accurate and effective.

[0023] Optionally, further comprising:

[0024] The coordinate offset threshold value includes a coordinate offset tendency threshold value and a jitter threshold value;

[0025] determining coordinate offset tendency data and coordinate offset speed data according to the coordinate offset data and the time data;

[0026] determining coordinate tendency state data according to the coordinate offset tendency data and the coordinate offset tendency threshold value;

[0027] determine jitter data through the coordinate offset speed data and the time data;

[0028] determine jitter state data through the jitter data and the jitter threshold value;

[0029] determine the abnormal dispensing signal and output through the coordinate tendency state data and the jitter state data.

[0030] By adopting the technical scheme, the dispensing of the cash in the cash box is detected automatically, whether there is abnormal dispensing and abnormal reduction of cash is judged more accurately, and the abnormal dispensing signal is output automatically to remind the external security personnel.

[0031] Optionally, the method further comprises:

[0032] acquire dispensing data, dispensing signal and dispensing cash quality data;

[0033] determine dispensing state data through the dispensing data, the dispensing signal and a preset dispensing judgment threshold value;

[0034] determine dispensing amount state data through the dispensing cash quality data, the single cash quality threshold value and the dispensing data; determine an unexpected dispensing signal and output through the dispensing state data, the dispensing amount state data and a preset unexpected threshold value.

[0035] By adopting the technical scheme, the dispensing amount and the dispensing speed through the counter window are used to automatically judge the state of the teller, so that whether the teller is in a normal working state is judged, without the need for an additional camera, the probability of the camera being evaded by the lawbreaker is reduced, the safety is further improved, and the unexpected dispensing signal is output automatically to remind the external security personnel.

[0036] Optionally, the method further comprises:

[0037] determine dispensing difference data through the dispensing state data, the single cash quality threshold value and a plurality of continuous dispensing cash quality data;

[0038] determine dispensing interval time data through the time data and the dispensing cash quality data;

[0039] determine dispensing amount abnormal data through the dispensing difference data and a preset unexpected difference change threshold value;

[0040] determine dispensing panic degree data through the dispensing interval time data and a preset dispensing degree data;

[0041] The unexpected cash withdrawal signal is determined and output by the cash withdrawal amount abnormal data and the cash withdrawal panic degree data.

[0042] By adopting the technical scheme, the state of the teller is more accurately judged, the accuracy is further improved, and the security is improved.

[0043] The bank real-time online monitoring anti-theft system provided in the application adopts the following technical scheme:

[0044] The bank real-time online monitoring anti-theft system comprises:

[0045] The recognition module is configured to perform image recognition on the cash, obtain the cash-out signal and the cash withdrawal signal, and output the signals.

[0046] The pressure detection module is configured to perform pressure detection on the cash, obtain the current cash quality data and the cash withdrawal quality data, and output the data.

[0047] The data processing module receives the cash-out signal, the cash withdrawal signal, the current cash quality data and the cash withdrawal quality data, performs data processing, obtains the ATM machine intrusion signal, the stolen cash signal, the abnormal cash-out signal and the unexpected cash withdrawal signal, and outputs the signals to a user.

[0048] By adopting the technical scheme, the cash in the cash box is recognized by the recognition module, the quality of the cash delivered by the cash box or the teller to the cash withdrawal person is detected by the pressure detection module, the amount of the cash is calculated, it is convenient to automatically calculate and judge whether the current cash withdrawal is abnormal, the intelligent judgment whether there is a security problem can be realized without monitoring the external environment, the security problem is not easy to be found by the lawbreaker, the lawbreaker is difficult to prepare in advance, and the ATM machine intrusion signal, the stolen cash signal, the abnormal cash-out signal and the unexpected cash withdrawal signal are automatically output to the external security personnel, and the probability that the bank staff is held and cannot remind the external security personnel is reduced.

[0049] The computer readable storage medium provided in the application adopts the following technical scheme:

[0050] The computer readable storage medium stores a computer program capable of being loaded and executed by a processor to perform the bank real-time online monitoring anti-theft method.

[0051] By adopting the technical scheme, the computer program is stored by the computer readable storage medium.

[0052] In summary, the application has at least one of the following beneficial technical effects:

[0053] 1. Automatic determination of the working state of the ATM, direct detection of the state of the cash, improvement of the intelligent degree, more accurate and effective realization of intelligent anti-theft.

[0054] 2. Detecting the working state of the teller, automatically determining the state of the teller, and improving the security. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 is a flowchart of a bank real-time online monitoring anti-theft method in an embodiment of the present application.

[0056] Figure 2 is a flowchart of steps S2-S22.

[0057] Figure 3 is a flowchart of steps S3-S33.

[0058] Figure 4 is a flowchart of steps S4-S45.

[0059] Figure 5 is a flowchart of steps S5-S53.

[0060] Figure 6 is a flowchart of steps S6-S64.

[0061] Figure 7 is a module diagram of a bank real-time online monitoring anti-theft system in an embodiment of the present application.

[0062] BRIEF DESCRIPTION OF DRAWINGS 1. Identification module; 2. Pressure detection module; 3. Data processing module. DETAILED DESCRIPTION

[0063] The following will be described in detail in combination with the accompanying Figure 1-7 The present application will be further described in detail.

[0064] An embodiment of the present application discloses a bank real-time online monitoring anti-theft method. Referring to Figure 1 , the bank real-time online monitoring anti-theft method comprises the following steps:

[0065] S1, obtaining dispensing data, dispensing signals and current cash quality data;

[0066] S11, determining the ATM intrusion signal through the dispensing data, the dispensing signal and the preset dispensing judgment threshold, and outputting to the user; S12, determining the current cash data through the current cash quality data and the preset single cash quality threshold;

[0067] S13, determining the stolen cash signal through the current cash data, the preset remaining cash data and the preset environmental deviation threshold, and outputting to the user;

[0068] S14, determining new remaining cash data by combining the original remaining cash data and the dispensing data, and replacing the original remaining cash data.

[0069] In detail, the dispensing data is the data information received by the ATM machine that needs to be dispensed, such as inserting a bank card and inputting 5000 yuan for withdrawal. At this time, 5000 yuan is the dispensing data. The dispensing signal is whether the cash in the dispensing port is dispensed, which is generally realized by, for example, a camera with image recognition function, or by taking a picture through the camera and then transmitting the video obtained by the camera to the processor for processing. The current cash quality data is obtained by weighing the cash in the cash box connected to the ATM machine, which is generally realized by a pressure sensor arranged below the cash box. If the dispensing data is 0, but the dispensing signal indicates that cash is taken out from the dispensing port, and the dispensing judgment threshold is set as (0, 1, abnormal), it means that the situation of no dispensing data and dispensing signal is abnormal, which may be that the ATM machine is invaded to control the ATM machine to dispense money, or the device is inserted into the ATM machine from the dispensing port to extract cash, which will also cause the recognition of something in the dispensing port without dispensing data, so as to output the ATM machine invasion signal indicating that the ATM machine is invaded to the user such as the security room, so as to protect the ATM machine. The single cash quality threshold is the quality data of a single cash, for example, the quality of a 100 yuan cash is 1 g. If the current cash quality data is 1000 kg, it means that there are 10 6 pieces of 100 yuan cash, which is the current cash data. The remaining cash data is the cash data that should be left after combining the dispensing data, for example, the initial remaining cash data is (5000+10 8 ) yuan, and the dispensing data is 5000 yuan. After dispensing, the remaining cash data is 10 8 yuan, and there are 10 6 pieces of 100 yuan cash after weighing, at this time, the remaining cash data is equal to the current cash data, indicating that the cash box is normal. If the environmental deviation threshold is set as 1%, it means that the difference between the current cash data and the remaining cash data is within the range of ±1% if it is a normal phenomenon, for example, affected by environmental factors such as humidity. If the difference between the current cash data and the remaining cash data exceeds the environmental deviation threshold, it means that the cash in the cash box is stolen, for example, by a new method of stealing that can ignore the image recognition of the dispensing port and will not damage the ATM machine to trigger the protection alarm. At this time, the corresponding stolen cash signal is output to the security room.

[0070] Reference Figure 2 , the steps further comprise:

[0071] S2, obtaining time data;

[0072] S21, determining automatic dispensing speed data by current cash data and time data;

[0073] S22, determining abnormal dispensing signal by automatic dispensing speed data and preset dispensing speed threshold value, and outputting to user.

[0074] In detail, if time data is 1min0s, current cash data is 10 8 000 yuan, if time data is 1min1s, current cash data is 10 8 -1000 yuan, if time data is 1min2s, current cash data is 10 8 -2000 yuan, then automatic dispensing speed data is 1000 yuan / s, and if time data is 1min0s-1min1s-1min2s, current cash data is 10 8 , 10 8 -2000, 10 8 -6000, and if dispensing speed threshold value is 1500, then maximum dispensing speed of the ATM machine is 1500 yuan / s, and automatic dispensing speed data is 2000 yuan / s and 4000 yuan / s respectively, which exceeds dispensing speed threshold value, and at this time, it indicates that the ATM machine is in abnormal condition, for example, someone hacks into the system of the ATM machine to remove the dispensing speed of the ATM machine, or sticks a blower to the dispensing port to draw money out, and outputs corresponding abnormal dispensing signal to security room.

[0075] Referring to Figure 3 , the method further comprises the following steps:

[0076] S3, current cash quality data is multiple;

[0077] S31, determining centroid coordinate data by multiple current cash quality data and preset cash distribution coordinate threshold value;

[0078] S32, determining coordinate offset data by time data, automatic dispensing speed data and centroid coordinate data;

[0079] S33, determining abnormal dispensing signal by coordinate offset data and preset coordinate offset threshold value, and outputting.

[0080] Detailed: multiple pressure sensors are buried below the cash box to detect the cash mass data at different positions, and the cash distribution coordinate threshold is the position of the multiple pressure sensors, so that the centroid coordinate data can be calculated. For example, the cash mass data of No. 1 is 1000 kg, the coordinate is (0, 0), the cash mass data of No. 2 is 1000 kg, the coordinate is (1000, 0), the cash mass data of No. 3 is 1000 kg, the coordinate is (0, 1000), the cash mass data of No. 4 is 1000 kg, the coordinate is (1000, 1000), and the centroid coordinate data is (500, 500). The total cash mass data is 4000 kg. When dispensing, the cash in the cash box will be taken out, so the cash mass data at each position will change, and the centroid coordinate data will change. Combined with the automatic dispensing speed data, the speed of the centroid coordinate data changing with the dispensing speed of the cash can be obtained, which is the coordinate offset data. The coordinate offset threshold is the normal data of the coordinate offset data during normal dispensing. For example, the automatic dispensing speed data is normally 10 sheets / s, that is, the current cash mass data will be-10g / s. The cash in the cash box is taken out in order. It is not easy to understand, and it is explained in the way of manual cash taking. The cash is 100 sheets in a stack, and the vertical direction is 100 stacks in a stack. The horizontal is 10 screws in a row, and 10 rows are placed side by side to form an array. When the array is used, the lowermost one in the leftmost row of the uppermost layer is taken first, and then the uppermost one in the same row is taken. When the row is taken, the rightmost row of cash is taken. When the whole layer is taken, the cash in the next layer is taken. When the whole array is taken, the cash in the next array is taken. Therefore, when automatic taking is performed, it will also be taken in order according to the same automatic dispensing speed data of 10 sheets / s. Therefore, when the automatic taking is performed according to the same automatic dispensing speed data of 10 sheets / s, there will be an allowed coordinate offset data. For example, the cash in the lower left corner is taken, and then it is taken in a clockwise spiral. The coordinate offset data is first offset to the right and then clockwise. This is the coordinate offset threshold. If the coordinate offset data exceeds the range specified by the coordinate offset threshold, it means that the illegal person may not take the cash according to the rules specified by the coordinate offset threshold, and it also prevents illegal persons from placing weights in the cash box to increase the weight and cause the pressure sensor to misjudge.

[0081] Referring to Figure 4 Further comprising the following steps:

[0082] S4, the coordinate offset threshold includes a coordinate offset tendency threshold and a jitter threshold;

[0083] S41, the coordinate offset tendency data and the coordinate offset speed data are determined by the coordinate offset data and the time data;

[0084] S42, determine coordinate tendency state data by coordinate offset tendency data and coordinate offset tendency threshold value;

[0085] S43, determine jitter data by coordinate offset speed data and time data;

[0086] S44, determine jitter state data by jitter data and jitter threshold value;

[0087] S45, determine abnormal dispensing signal and output by coordinate tendency state data and jitter state data.

[0088] In detail: the coordinate offset tendency threshold value is the allowed coordinate offset tendency, for example, the coordinate offset to the lower left direction, which is the coordinate offset tendency, the coordinate offset tendency data and the coordinate offset speed data are separated from the coordinate offset data according to time, the coordinate offset tendency data is the coordinate offset direction, and the coordinate offset speed data is the speed of the coordinate offset. If the coordinate offset tendency data is too large, which exceeds the valve of the coordinate offset tendency threshold value, it indicates that for example, the criminal may take a large amount of cash by the air blower, and the position of the cash taken is not controlled, which leads to the rapid reduction of local cash, so that the coordinate offset tendency data exceeds the range of the coordinate offset tendency threshold value, and the corresponding abnormal dispensing signal is output to the security room; and the jitter data is the change of the coordinate offset speed data, for example, if the allowed coordinate offset speed data is the change of 1° / s clockwise, and if the time data is 1min0s, the coordinate offset speed data is 1° / s clockwise, the time data is 1min1s, the coordinate offset speed data is 2° / s clockwise, and the time data is 1min2s, the coordinate offset speed data is-1° / s clockwise, so the jitter data is 2° / s clockwise 2 and-3° / s 2 , which can be understood as acceleration, indicating that the center of mass suddenly speeds up when it is offset, and then reverses the offset, indicating that the speed of taking cash suddenly changes, and then the direction of taking cash changes, which means that jitter occurs. If the jitter threshold value is [0.5, 1], it indicates that when the jitter data exceeds the range of the jitter threshold value, the abnormal dispensing signal is output to the security room.

[0089] Referring to Figure 5 , the method further comprises the following steps:

[0090] S5, obtaining dispensing data, dispensing signal and dispensing cash quality data;

[0091] S51, determining dispensing state data by dispensing data, dispensing signal and preset dispensing judgment threshold value;

[0092] S52, determining dispensing amount state data by dispensing cash quality data, single cash quality threshold value and dispensing data;

[0093] S53, determining an unexpected withdrawal signal and outputting by the withdrawal state data, the withdrawal amount state data and the preset unexpected threshold.

[0094] In detail, the withdrawal data is the data of the bank card user who wants to withdraw at the counter, for example, the user wants to withdraw 50000 yuan at the counter, and 50000 is the withdrawal data. The withdrawal signal is the image recognition on the window to determine whether the counter delivers money out of the counter. The withdrawal cash quality data is the pressure sensor under the user's cash delivery port on the window to detect the cash quality placed on the window by the teller, combined with the single cash quality threshold, to calculate the amount of cash. If there is a withdrawal signal but no withdrawal data, it means that there is no corresponding bank card for the teller, but the teller has delivered cash from the window. At this time, the withdrawal judgment threshold is used to determine that there should be no withdrawal signal, so the withdrawal state data indicating withdrawal anomaly is obtained. The detected withdrawal cash quality data is compared with the required withdrawal data to determine whether there is an anomaly. For example, the withdrawal data is only 10000 yuan, and the withdrawal cash quality data is 200, which means that 20000 yuan has actually been withdrawn. At this time, the withdrawal amount state data indicating the withdrawal amount anomaly is output. If either the withdrawal state data or the withdrawal amount state data has multiple consecutive anomalies, i.e. the number of consecutive anomalies exceeds the range of the unexpected threshold, or the anomalies are not continuous but the two anomalies are staggered, the corresponding unexpected withdrawal signal is output to the security room. The specific condition for triggering the unexpected withdrawal signal can be adjusted by adjusting the unexpected threshold. Sometimes, a large amount of money is withdrawn at one time, which may need to be delivered out of the window multiple times. The first time there is withdrawal data, and subsequent times only have withdrawal data without input of withdrawal data again. Because the subsequent payment does not pay for the previous input withdrawal data, continuous abnormal conditions are allowed.

[0095] Referring to Figure 6 The method further comprises the following steps:

[0096] S6, determining withdrawal difference data by the withdrawal state data, the single cash quality threshold and the consecutive multiple withdrawal cash quality data.

[0097] S61, determining withdrawal interval time data by the time data and the withdrawal cash quality data.

[0098] S62, determining withdrawal amount anomaly data by the withdrawal difference data and the preset unexpected difference change threshold.

[0099] S63, determining withdrawal panic degree data by the withdrawal interval time data and the preset withdrawal degree data.

[0100] S64, determining the unexpected cash withdrawal signal by the cash withdrawal amount abnormal data and the cash withdrawal panic degree data and outputting.

[0101] In detail, the time data can determine whether the cash withdrawal quality data is continuous, and if the cash withdrawal state data is abnormal, that is, there is no cash withdrawal data but there is a cash withdrawal signal, but the cash withdrawal quality data changes every time, for example, the first received cash withdrawal data is 100000 yuan, the first cash withdrawal quality data is 20000 yuan, the second cash withdrawal quality data is 15600 yuan, and the third cash withdrawal quality data is 18500 yuan, and the obtained cash withdrawal difference data is-4400, +1900, and the unexpected difference threshold is set to 500, which indicates that when the previous cash withdrawal data is not completely withdrawn, the cash withdrawal difference data should be less than 500 every time, that is, the cash withdrawal data is 100000 yuan, and the window can only place cash 20000 yuan every time, so theoretically the cash withdrawal quality data should be 20000 yuan, even if there is an error, it should be between 19500-20000 yuan, and if the cash amount difference represented by the adjacent two cash withdrawal quality data is large, it indicates that the cash withdrawal may be abnormal, for example, the teller is threatened and panic to quickly take cash, or in the case of self-stealing, the teller quickly transfers cash to the partner, which is the cash withdrawal amount abnormal data; the time interval of cash withdrawal is obtained by the time data, that is, the cash withdrawal interval time data; the cash withdrawal degree data is set to (30s, not equal), which indicates that if the cash withdrawal interval time data is less than 30s, and the adjacent cash withdrawal interval time data is not equal, for example, if the cash withdrawal interval time is 15s, 20s, 18s, it is out of the range of the cash withdrawal degree data, which indicates that the state of the teller when withdrawing cash is to move as fast as possible but more panic, which may be in the state of self-stealing or being threatened; and when any of the cash withdrawal amount abnormal data and the cash withdrawal panic degree data is abnormal, the corresponding unexpected cash withdrawal signal is output to the security room.

[0102] The embodiment of the application discloses a bank real-time online monitoring anti-theft system. Referring to Figure 7 , the bank real-time online monitoring anti-theft system comprises an identification module 1, a pressure detection module 2 and a data processing module 3. The identification module 1 can adopt a camera with image recognition or an optical sensor capable of detecting whether cash passes, and is placed on the cash outlet of an ATM and the counter window, so as to obtain and output the cash-out signal and the cash withdrawal signal. The pressure detection module 2 can adopt a pressure sensor, which is placed under the cash box and the counter window, and the number of the pressure detection module 2 is multiple, which is arranged in an array under the cash box to detect the current cash quality data of the cash in the cash box and the cash withdrawal quality data of the cash placed on the counter window, and output.

[0103] Referring to Figure 7The data processing module 3 comprises a database and a processor. The database is used to store various threshold data, such as dispensing judgment threshold, single cash quality threshold, environmental deviation threshold, dispensing speed threshold, cash distribution coordinate threshold, coordinate offset threshold, withdrawal judgment threshold, accident threshold, accident difference change threshold, and withdrawal degree data. The processor receives dispensing signal, withdrawal signal, current cash quality data, and withdrawal cash quality data, then calls corresponding threshold data from the database to process and calculate data, so as to obtain the ATM invasion signal, cash theft signal, abnormal dispensing signal, and accidental withdrawal signal, and then outputs to the designated terminal equipment, such as the communication equipment of the security room.

[0104] The processor can include a CPU or an MPU, or a host system built with a CPU or an MPU as a core, including hardware or software. After the processor is provided to the meter, people can freely control the meter by programming, so that the meter runs according to the will of people. The processor can control local transmitters, remote transmitters, remote communication, etc. through internal protocols. Internal protocols generally refer to all protocols for realizing mutual communication or linkage within the same meter or within the same system, including part or all of the following protocols: human-computer interaction protocol, software / hardware (interface) protocol, chip bus (C-Bus) protocol, internal bus (I-Bus) protocol, etc. With the development of integrated circuit technology, some external bus (E-Bus) protocols are also included in internal protocols after being integrated into chips.

[0105] The embodiment of the present application discloses a computer readable storage medium. Referring to Figure 1 The computer readable storage medium stores a computer program capable of being loaded and executed by the processor to perform the bank real-time online monitoring anti-theft method.

[0106] The computer readable storage medium includes, for example, a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media capable of storing program codes.

[0107] The above are preferred embodiments of the present application, and do not limit the protection scope of the present application. Therefore, equivalent changes made according to the structure, shape, principle of the present application should be covered within the protection scope of the present application.

Claims

1. A method for real-time online monitoring and theft prevention of bank ATMs, characterized in that, include: Obtain withdrawal data, withdrawal signals, and current cash quality data; The ATM intrusion signal is determined by the withdrawal data, the withdrawal signal, and a preset withdrawal judgment threshold, and then output to the user. The current cash data is determined by comparing the current cash quality data with a preset single cash quality threshold. The cash theft signal is determined by the current cash data, the preset remaining cash data, and the preset environmental deviation threshold, and then output to the user. The new remaining cash data is determined by comparing the original remaining cash data with the withdrawal data, and the original remaining cash data is replaced. Obtain time data; The automatic withdrawal speed data is determined by combining the current cash data with the time data. Abnormal withdrawal signals are determined by comparing the automatic withdrawal speed data with a preset withdrawal speed threshold and then output to the user. The current cash quality data is multiple; The centroid coordinate data is determined by comparing multiple current cash quality data with a preset cash distribution coordinate threshold. The coordinate offset data is determined by the time data, the automatic disbursement speed data, and the centroid coordinate data. The abnormal withdrawal signal is determined and output by comparing the coordinate offset data with a preset coordinate offset threshold.

2. The method for real-time online monitoring and anti-theft of bank ATMs according to claim 1, characterized in that, Also includes: The coordinate offset threshold includes a coordinate offset tendency threshold and a jitter threshold; The coordinate offset trend data and coordinate offset velocity data are determined by the coordinate offset data and the time data; The coordinate tendency status data is determined by comparing the coordinate offset tendency data with the coordinate offset tendency threshold. The jitter data is determined by the coordinate offset velocity data and the time data; The jitter state data is determined by comparing the jitter data with the jitter threshold. The abnormal withdrawal signal is determined and output by using the coordinate tendency state data and the jitter state data.

3. A method for real-time online monitoring and theft prevention at bank counters, characterized in that, Also includes: Acquire withdrawal data, withdrawal signals, and cash withdrawal quality data; Withdrawal status data is determined by the withdrawal data, the withdrawal signal, and a preset withdrawal judgment threshold; The withdrawal amount status data is determined by the cash withdrawal quality data, the single cash quality threshold, and the withdrawal data. An unexpected withdrawal signal is determined and output by using the withdrawal status data, the withdrawal amount status data, and a preset unexpected threshold. The withdrawal difference data is determined by the withdrawal status data, the single cash quality threshold, and multiple consecutive withdrawal cash quality data. Acquire time data, and determine withdrawal interval time data by comparing the time data with the cash withdrawal quality data; Abnormal withdrawal amount data is determined by comparing the withdrawal difference data with a preset threshold for unexpected difference changes; The withdrawal anxiety level data is determined by comparing the withdrawal interval time data with the preset withdrawal level data; The unexpected withdrawal signal is determined and output by combining the abnormal withdrawal amount data and the withdrawal panic level data.

4. A real-time online monitoring and anti-theft system for bank ATMs, using the real-time online monitoring and anti-theft method for bank ATMs as described in claim 1, characterized in that, include: The identification module (1) is used to perform image recognition on cash, obtain the cash disbursement signal, and output it. The pressure detection module (2) is used to perform pressure detection on the cash, obtain the current cash quality data, and output it. The data processing module (3) receives the withdrawal signal and the current cash quality data, and after data processing, obtains the ATM intrusion signal, the cash theft signal, and the abnormal withdrawal signal, and outputs them to the user.

5. A real-time online monitoring and anti-theft system for bank counters, using the real-time online monitoring and anti-theft method for bank counters as described in claim 3, characterized in that, include: The recognition module (1) is used to perform image recognition on cash, obtain the withdrawal signal, and output it. The pressure detection module (2) is used to perform pressure detection on the cash, obtain the quality data of the withdrawn cash, and output it. The data processing module (3) receives the withdrawal signal and the cash quality data, processes the data, obtains the unexpected withdrawal signal, and outputs it to the user.

6. A computer-readable storage medium, characterized in that, The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1-2, which is a real-time online monitoring and anti-theft method for bank ATMs.

7. A computer-readable storage medium, characterized in that, The system stores a computer program that can be loaded by a processor and executed as described in claim 3, which is a method for real-time online monitoring and theft prevention at a bank counter.

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