Bank real-time online monitoring anti-theft method and system and storage medium thereof

Abstract

The invention relates to the field of intelligent security and protection, in particular to a bank real-time online monitoring anti-theft method and system and a storage medium thereof, and the method comprises the steps: obtaining money output data, a money output signal and current cash quality data; determining an ATM intrusion signal according to the withdrawal data, the withdrawal signal and a preset withdrawal judgment threshold value, and outputting the ATM intrusion signal to a user; determining current cash data according to the current cash quality data and a preset single cash quality threshold value; determining a cash stealing signal according to the current cash data, preset residual cash data and a preset environment deviation threshold value, and outputting the cash stealing signal to a user; and determining new remaining cash data according to the original remaining cash data and the cash dispensing data, and replacing the original remaining cash data. The intelligent anti-theft system has the effect of accurately, quickly and automatically realizing intelligent anti-theft.

Description

Technical Field

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

[0002] my country has a large population and a vast territory, so there are a large number of ATMs for people to withdraw cash. However, due to the large number of ATMs and their wide distribution, it is difficult to arrange personnel for security. Therefore, a large number of ATMs are unattended and can only be monitored through surveillance. This provides opportunities for speculators to steal cash from ATMs. Once the cash in the ATM is stolen, if the surveillance does not notify the local security in time, it is easy to make it difficult to recover the money. Most of the cash in the bank belongs to the deposit users. The unrecovered money is likely to cause the situation that the cash in the bank is less than the stored amount data, thereby causing bad debts and affecting the bank's reputation. Once there is an incident of threatening the teller with a knife or even robbing the bank at the bank counter, bad debts are also likely to occur. And because the staff are controlled, it is difficult for the staff in the bank to pass the situation to the outside world, making it difficult for the outside of the bank to quickly discover the situation. Therefore, it is urgent to develop a fast, accurate and automatic intelligent anti-theft system. Summary of the invention

[0003] In order to improve the problem that it is difficult to detect the theft or robbery of cash in a bank in a timely manner, the present application provides a bank real-time online monitoring anti-theft method, system and storage medium thereof.

[0004] The present application provides a real-time online monitoring and anti-theft method for banks, which adopts the following technical solutions: A bank real-time online monitoring anti-theft method, comprising: Obtain withdrawal data, withdrawal signals and current cash quality data; Determine the ATM intrusion signal through the withdrawal data, the withdrawal signal and the preset withdrawal judgment threshold, and output it to the user; Determine the current cash data by comparing the current cash quality data with a preset single cash quality threshold; Determine a cash theft signal through the current cash data, the preset remaining cash data and the preset environment deviation threshold, and output it to the user; The new remaining cash data is determined by the original remaining cash data and the withdrawal data, and replaces the original remaining cash data.

[0005] By adopting the above technical solution, the ATM machine can automatically determine whether it has been invaded through its working status and output corresponding ATM intrusion signals and cash theft signals, thereby reducing the probability of external surveillance cameras being discovered by criminals and then blocking the surveillance cameras, making them invalid. The status of cash can be directly detected, the degree of intelligence can be improved, and intelligent anti-theft can be achieved more accurately and effectively.

[0006] Optionally, also include: Get time data; Determine automatic cash withdrawal speed data by using the current cash data and the time data; An abnormal withdrawal signal is determined by comparing the automatic withdrawal speed data with a preset withdrawal speed threshold and is output to the user.

[0007] By adopting the above technical solution, whether the ATM machine is in a normal working state is determined by the withdrawal speed of the ATM machine, and an abnormal withdrawal signal is automatically output.

[0008] Optionally, also include: The current cash quality data is multiple; Determine centroid coordinate data by using a plurality of the current cash mass data and a preset cash distribution coordinate threshold; Determine coordinate offset data through the time data, the automatic withdrawal speed data and the centroid coordinate data; The abnormal withdrawal signal is determined and outputted through the coordinate offset data and a preset coordinate offset threshold.

[0009] By adopting the above technical solution, the speed of automatic withdrawal and the change of the center of mass of cash can be used to automatically determine whether there are criminals withdrawing cash, so as to combat the use of new technologies by criminals to bypass the detection of the ATM cash outlet to steal cash, improve anti-theft security, and automatically output abnormal withdrawal signals to alert external security personnel.

[0010] Optionally, also include: The coordinate shift threshold includes a coordinate shift tendency threshold and a jitter threshold; Determine coordinate offset tendency data and coordinate offset speed data through the coordinate offset data and the time data; Determine coordinate tendency state data by using the coordinate deviation tendency data and the coordinate deviation tendency threshold; Determine jitter data using the coordinate offset speed data and the time data; Determine jitter state data according to the jitter data and the jitter threshold; The abnormal withdrawal signal is determined and outputted through the coordinate inclination state data and the jitter state data.

[0011] By adopting the above technical solution, the withdrawal of cash piled in the cash vault can be automatically detected, and it can be more accurately determined whether there is abnormal withdrawal and abnormal reduction of cash, and an abnormal withdrawal signal can be automatically output to alert external security personnel.

[0012] Optionally, also include: Obtain withdrawal data, withdrawal signals and withdrawal cash quality data; Determine the withdrawal status data through the withdrawal data, the withdrawal signal and a preset withdrawal judgment threshold; The withdrawal amount status data is determined by the withdrawal cash quality data, the single cash quality threshold and the withdrawal data; the unexpected withdrawal signal is determined and outputted by the withdrawal status data, the withdrawal amount status data and a preset unexpected threshold.

[0013] By adopting the above technical solution, the state of the teller can be automatically judged by the withdrawal amount and withdrawal speed at the counter window, so as to judge whether the teller is in a normal working state without the need for extra cameras, thereby reducing the probability of the camera being evaded after being discovered by criminals, further improving security, and automatically outputting unexpected withdrawal signals to alert external security personnel.

[0014] Optionally, also include: Determine the withdrawal difference data through the withdrawal status data, the single cash quality threshold and a plurality of continuous withdrawal cash quality data; Determine the withdrawal interval time data by using the time data and the withdrawal cash quality data; Determining withdrawal amount abnormal data by comparing the withdrawal difference data with a preset unexpected difference change threshold; Determine the withdrawal panic degree data through the withdrawal interval time data and the preset withdrawal degree data; The unexpected withdrawal signal is determined and outputted based on the withdrawal amount abnormality data and the withdrawal panic degree data.

[0015] By adopting the above technical solution, the state of the teller can be judged more accurately, further improving accuracy and enhancing security.

[0016] The present application provides a real-time online monitoring and anti-theft system for banks, which adopts the following technical solutions: A real-time online monitoring and anti-theft system for a bank, comprising: An identification module, used for performing image recognition on cash, obtaining the cash-out signal and the cash-withdrawal signal and outputting them; A pressure detection module is used to perform pressure detection on cash, obtain the current cash quality data and withdrawal cash quality data and output them; The data processing module receives the cash-out signal, the cash withdrawal signal, the current cash quality data and the cash withdrawal quality data, and after data processing, obtains the ATM intrusion signal, the cash theft signal, the abnormal cash-out signal and the unexpected cash withdrawal signal, and outputs them to the user.

[0017] By adopting the above technical solution, the cash leaving the warehouse is identified by the identification module, and the cash handed to the cashier by the cash vault or the teller is quality checked by the pressure detection module, so as to calculate the amount of cash, and it is convenient to automatically calculate and judge whether there is any abnormality in the current cash withdrawal, so as to realize intelligent judgment whether there is a security problem without monitoring the external environment, and it is not easy to be discovered by criminals, making it difficult for criminals to prepare in advance, and automatically output ATM intrusion signals, cash theft signals, abnormal withdrawal signals and accidental withdrawal signals to external security personnel, thereby reducing the probability of bank staff being held hostage and unable to alert external security personnel.

[0018] The present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute a real-time online monitoring and anti-theft method for a bank.

[0019] By adopting the above technical solution, the computer program is stored in a computer-readable storage medium.

[0020] In summary, the present application includes at least one of the following beneficial technical effects: 1. Automatically determine the working status of the ATM machine, directly detect the status of cash, improve the degree of intelligence, and realize intelligent anti-theft more accurately and effectively.

[0021] 2. Detect the teller's working status, automatically determine the teller's status, and improve security. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of a bank real-time online monitoring and anti-theft method in an embodiment of the present application.

[0023] Figure 2 It is a flowchart diagram of step S2 to step S22.

[0024] Figure 3 It is a flowchart diagram of step S3 to step S33.

[0025] Figure 4 It is a flowchart diagram of step S4 to step S45.

[0026] Figure 5It is a flowchart diagram of step S5 to step S53.

[0027] Figure 6 It is a flowchart diagram of step S6 to step S64.

[0028] Figure 7 It is a module diagram of a bank real-time online monitoring anti-theft system in an embodiment of the present application.

[0029] Explanation of the accompanying drawings: 1. Identification module; 2. Pressure detection module; 3. Data processing module. DETAILED DESCRIPTION

[0030] The following is combined with Figure 1-7 This application is described in further detail.

[0031] The present application embodiment discloses a bank real-time online monitoring anti-theft method. Figure 1 , the bank's real-time online monitoring anti-theft method includes the following steps: S1. Obtaining withdrawal data, withdrawal signals and current cash quality data; S11, determine the ATM intrusion signal through the withdrawal data, withdrawal signal and the preset withdrawal judgment threshold, and output it to the user; S12, determine the current cash data through the current cash quality data and the preset single cash quality threshold; S13, determining a cash theft signal through current cash data, preset remaining cash data and a preset environment deviation threshold, and outputting it to the user; S14. Determine new remaining cash data based on the original remaining cash data and withdrawal data, and replace the original remaining cash data.

[0032] Details: The withdrawal data is the data information that the ATM receives that needs to be withdrawn. For example, if you insert a bank card and enter 5,000 yuan to withdraw, 5,000 yuan is the withdrawal data. The withdrawal signal is whether the cash recognized by the ATM at the cash outlet has been withdrawn. It is generally achieved through a camera with image recognition function, or by taking a picture with a camera and then transmitting the video obtained by the camera to a processor for processing. The current cash quality data is obtained by weighing the cash in the purse connected to this ATM, and is generally achieved by a pressure sensor set under the purse. If the withdrawal data is 0, but the withdrawal signal indicates that cash has been withdrawn The cash withdrawal is taken out from the cash outlet. If the cash withdrawal judgment threshold is (0, 1, abnormal), it means that the situation where there is no cash withdrawal data but there is a cash withdrawal signal is an abnormal situation. It may be that the ATM machine is invaded through data to control the ATM machine to spit out money, or the device is inserted into the ATM machine from the cash withdrawal port to withdraw cash. This will also lead to the recognition that there is something in the cash withdrawal port, but there is no cash withdrawal data, so as to output an ATM intrusion signal indicating that the ATM machine has been invaded to users such as the security room to protect the ATM machine; the single cash quality threshold is the quality data of a cash piece. For example, the weight of a 100-yuan cash piece is 1g. If the current cash quality data is 1000kg, it means that there is 10 6 100 yuan in cash, which is the current cash data, and the remaining cash data is the remaining cash data after combining the withdrawal data. For example, the initial remaining cash data is (5000+10 8 ) yuan, and the withdrawal data is 5000 yuan, then after the withdrawal, the remaining cash data is 10 8 Yuan, and after the withdrawal, it was weighed and found to be 10 6 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 vault has been stolen, for example, by criminals who ignore the image recognition of the cash outlet and do not damage the ATM machine and cannot trigger the protection alarm. At this time, the corresponding cash theft signal is output to the security room.

[0033] Reference Figure 2 , further comprising the following steps: S2, obtaining time data; S21, determining automatic withdrawal speed data based on current cash data and time data; S22. Determine an abnormal withdrawal signal based on the automatic withdrawal speed data and a preset withdrawal speed threshold, and output it to the user.

[0034] Detailed: If the time data is 1min0s, the current cash data is 10 8 Yuan, if the time data is 1min1s, the current cash data is 10 8 -1000 yuan, if the time data is 1min2s, the current cash data is 10 8 -2000 yuan, the automatic withdrawal speed data can be obtained as 1000 yuan / s, and if the time data is 1min0s-1min1s-1min2s, the current cash data is 10 8 , 10 8 -2000, 10 8 -6000, assuming the withdrawal speed threshold is 1500, it means that the maximum withdrawal speed of the ATM is 1500 yuan / s, but the automatic withdrawal speed data at this time has reached 2000 yuan / s and 4000 yuan / s respectively, exceeding the withdrawal speed threshold. This means that the ATM is in an abnormal situation. For example, someone has hacked into the ATM system to release the withdrawal speed of the ATM, or attached a fan to the withdrawal port to draw money out, outputting the corresponding abnormal withdrawal signal to the security room.

[0035] Reference Figure 3 , further comprising the following steps: S3. The current cash quality data is multiple; S31, determining centroid coordinate data through a plurality of current cash mass data and a preset cash distribution coordinate threshold; S32, determining coordinate offset data through time data, automatic withdrawal speed data and centroid coordinate data; S33. Determine and output an abnormal withdrawal signal through the coordinate offset data and a preset coordinate offset threshold.

[0036] In detail: Multiple pressure sensors are buried under the coin vault to detect and obtain cash mass data at different positions. The cash distribution coordinate threshold is the position of the multiple pressure sensors, so that the center of mass coordinate data can be calculated. For example, the cash mass data of No. 1 is 1000kg, the coordinate is (0,0), the cash mass data of No. 2 is 1000kg, the coordinate is (1000,0), the cash mass data of No. 3 is 1000kg, the coordinate is (0,1000), the cash mass data of No. 4 is 1000kg, the coordinate is (1000,1000), then the center of mass coordinate data can be obtained. The data is (500,500), and the total cash mass data is 4000kg. When withdrawing money, the cash mass data at each position will change because the money in the treasury will be taken away. At this time, the centroid coordinate data will change. Combined with the automatic withdrawal speed data, the speed at which the centroid coordinate data changes with the cash withdrawal speed can be obtained. This is the coordinate offset data. The coordinate offset threshold is the normal data of the coordinate offset data during normal withdrawal. For example, the automatic withdrawal speed data is normally 10 pieces / s, that is, the current cash mass data will be -10g / s, and the cash in the treasury will be -10g / s. The cash is extracted in sequence, which is not easy to understand. It is explained in terms of manual cash withdrawal. Cash is in stacks of 100 pieces. One stack is 100 pieces stacked vertically, and 10 pieces are stacked horizontally in a row. 10 rows are placed side by side as an array. When taking cash from this array, first take the bottom stack of the leftmost row on the top layer, and then take the top stack of the same row. After this row is used up, take the cash in the row on the right. After the whole layer is used up, take the cash in the next layer. After one array is fully used up, take the cash in the next array. Therefore, when withdrawing cash automatically, it will also be in a sequence. Therefore, when the automatic withdrawal is performed according to the same automatic withdrawal speed data of 10 pieces / s, there will be an allowed coordinate offset data. For example, the cash in the lower left corner is withdrawn, and then it is withdrawn in a clockwise spiral. In this case, the coordinate offset data first shifts to the upper right and then changes clockwise. This is the coordinate offset threshold. If the coordinate offset data exceeds the interval range specified by the coordinate offset threshold, it means that the criminals may not steal the cash according to the rules specified by the coordinate offset threshold. It also prevents the criminals from placing weights in the purse to increase the weight while stealing cash, causing the pressure sensor to misjudge.

[0037] Reference Figure 4 , further comprising the following steps: S4, coordinate shift threshold includes coordinate shift tendency threshold and jitter threshold; S41, determining coordinate shift tendency data and coordinate shift speed data through coordinate shift data and time data; S42, determining coordinate inclination state data through the coordinate offset inclination data and the coordinate offset inclination threshold; S43, determining jitter data through coordinate offset speed data and time data; S44, determining jitter state data according to the jitter data and the jitter threshold; S45. Determine the abnormal withdrawal signal through the coordinate inclination state data and the jitter state data and output it.

[0038] Detailed: The coordinate shift tendency threshold is the allowed coordinate shift tendency. For example, if the coordinate shifts to the lower left, this is the coordinate shift tendency. The coordinate shift tendency data and the coordinate shift speed data are separated from the coordinate shift data according to time. The coordinate shift tendency data is the coordinate shift direction, and the coordinate shift speed data is the coordinate shift speed. If the coordinate shift tendency data is too large, resulting in a valve that exceeds the coordinate shift tendency threshold, it means that, for example, criminals may use the exhaust fan to extract cash in large quantities, and fail to control the position of the extracted cash, resulting in a rapid reduction of local cash. As a result, the coordinate offset tendency data exceeds the range of the coordinate offset tendency threshold, and the corresponding abnormal withdrawal signal is output to the security room; the jitter data is the change of the coordinate offset speed data. For example, if the allowed coordinate offset speed data is a clockwise change of 1° / s, 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, the time data is 1min2s, and 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, means that the center of mass suddenly speeds up when it deviates, and then deviates in the opposite direction, which means that the speed of withdrawing cash suddenly becomes faster, and then the direction of withdrawing cash is changed. This is jitter. Assuming the jitter threshold is [0.5,1], it means that when the jitter data exceeds the range of the jitter threshold, an abnormal withdrawal signal is output to the security room.

[0039] Reference Figure 5 , further comprising the following steps: S5, obtaining withdrawal data, withdrawal signal and withdrawal cash quality data; S51, determining withdrawal status data through withdrawal data, withdrawal signal and preset withdrawal judgment threshold; S52, determining withdrawal amount status data through withdrawal cash quality data, single cash quality threshold and withdrawal data; S53, determining and outputting an unexpected withdrawal signal through the withdrawal status data, the withdrawal amount status data and a preset unexpected threshold value.

[0040] Detailed: The withdrawal data is the data received by the counter about the bank card user's withdrawal intention. For example, if the user wants to withdraw 50,000 yuan at the counter, 50,000 is the withdrawal data. The withdrawal signal is image recognition on the window to determine whether the counter hands the money out of the counter. The withdrawal cash quality data is the pressure sensor under the window where the user hands the cash to detect the quality of the cash 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 given to the teller, but the teller has handed out cash from the window. At this time, the withdrawal judgment threshold determines that there should be no withdrawal signal, so the withdrawal status data indicating withdrawal abnormality is obtained; and the detected withdrawal cash quality data is compared with the required withdrawal data to determine whether there is an abnormality, for example If the withdrawal data is only 10,000 yuan, but the withdrawal cash quality data is 200 sheets, it means that 20,000 yuan was actually withdrawn. At this time, the withdrawal amount status data indicating that the withdrawal amount is abnormal is output; and if there are multiple consecutive abnormalities in the withdrawal status data and the withdrawal amount status data, that is, the number of consecutive abnormalities exceeds the range of the accident threshold, or they are non-continuous abnormalities, but the two are staggered. Abnormalities will output the corresponding accidental withdrawal signal to the security room, and the specific conditions for triggering the accidental withdrawal signal can be adjusted by adjusting the accident threshold to trigger, because sometimes too much is withdrawn at one time, it may be necessary to hand over cash through the window multiple times, that is, there is withdrawal data for the first time, and there is only withdrawal data but no withdrawal data entered again later, because the withdrawal data entered last time has not been paid later, so continuous abnormal situations are allowed.

[0041] Reference Figure 6 , further comprising the following steps: S6, determining withdrawal difference data through withdrawal status data, a single cash quality threshold and a plurality of continuous withdrawal cash quality data; S61, determining the withdrawal interval time data through the time data and the withdrawal cash quality data; S62, determining withdrawal amount abnormal data by comparing the withdrawal difference data with a preset unexpected difference change threshold; S63, determining the withdrawal panic degree data by using the withdrawal interval time data and the preset withdrawal degree data; S64. Determine and output an unexpected withdrawal signal based on the withdrawal amount abnormality data and the withdrawal panic degree data.

[0042] In detail: the time data can be used to determine whether the withdrawal cash quality data is continuous. If the withdrawal status data indicates an abnormality, that is, there is no withdrawal data but a withdrawal signal exists, but the withdrawal cash quality data changes each time, for example, the first withdrawal data received is 100,000 yuan, the first withdrawal cash quality data is 20,000 yuan, the second withdrawal cash quality data is 15,600 yuan, and the third withdrawal cash quality data is 18,500 yuan. The withdrawal difference data are -4400 and +1900 respectively. Assuming the unexpected difference change threshold is 500, it means that when the previous withdrawal data has not been completely withdrawn, the withdrawal difference data each time should be less than 500, that is, the withdrawal data is 100,000 yuan, and the window can only place 20,000 yuan in cash each time. In theory, the withdrawal cash quality data should be 20,000 yuan. Even if there is an error, it should be between 19,500 and 20,500 yuan. 000 yuan, and if the difference in the cash amount represented by the cash quality data of two adjacent withdrawals is large, it means that there may be an abnormality in the withdrawal, for example, the teller is coerced to take the cash in a panic and quickly, or is stealing from the employer and seizing the time to pass the cash to his accomplice, which is the abnormal withdrawal amount data; the time interval of withdrawals is obtained through the time data, which is the withdrawal interval time data; assuming that the withdrawal degree data is (30s, unequal), it means that if the withdrawal interval time data is less than 30s, and the adjacent withdrawal interval time data are not the same, for example, if the withdrawal interval time is 15s, 20s, 18s, which is outside the range of the withdrawal degree data, it means that the teller is in a state of moving as fast as possible but in a panic when withdrawing money, and may be in a state of guilty embezzlement or coercion; and when any of the abnormal withdrawal amount data and the withdrawal panic degree data is abnormal, the corresponding unexpected withdrawal signal is output to the security room.

[0043] The present application embodiment discloses a real-time online monitoring anti-theft system for banks. Figure 7 The real-time online monitoring and anti-theft system of a bank includes an identification module 1, a pressure detection module 2 and a data processing module 3. The identification module 1 can be a camera with image recognition, or a photoelectric sensor with a function of detecting whether cash passes through. It is placed on the cash outlet and the counter window of the ATM machine to obtain a cash withdrawal signal and a cash withdrawal signal, and output them. The pressure detection module 2 can be a pressure sensor, which is placed under the purse and the counter window. There are multiple pressure detection modules 2, which are distributed in an array under the purse to detect the current cash quality data of the cash in the purse and the cash withdrawal quality data of the cash placed at the counter window, and output them.

[0044] Reference Figure 7The data processing module 3 includes a database and a processor. The database is used to store various threshold data, such as a withdrawal judgment threshold, a single cash quality threshold, an environmental deviation threshold, a withdrawal speed threshold, a cash distribution coordinate threshold, a coordinate offset threshold, a withdrawal judgment threshold, an accident threshold, an accident difference change threshold, a withdrawal degree data and other threshold data. The processor receives a withdrawal signal, a withdrawal signal, current cash quality data and withdrawal cash quality data, and then calls the corresponding threshold data from the database to process and calculate the data, thereby obtaining an ATM intrusion signal, a cash theft signal, an abnormal withdrawal signal and an accidental withdrawal signal, and then outputs them to a designated terminal device, such as a communication device in a security room.

[0045] The processor may include a central processing unit such as a CPU or MPU or a host system built around a CPU or MPU, including hardware or software. After the meter has a processor, people can freely control the metering instrument through programming to make it run according to people's wishes. The processor can control local measurement transmission, remote measurement transmission, remote communication, etc. through internal protocols. Internal protocols refer to all protocols that achieve mutual communication or links within the same metering instrument or the same system, including: human-computer interaction protocols, software / hardware (interface) protocols, chip bus (C-Bus) protocols, internal bus (I-Bus) protocols, etc. Part or all of the protocols. With the development of integrated circuit technology, some protocols that belong to the external bus (E-Bus) protocol are also classified as internal protocols after the external bus (E-Bus) is integrated into the chip.

[0046] The present application embodiment discloses a computer-readable storage medium. Figure 1 The computer-readable storage medium stores a computer program that can be loaded by a processor and executes a real-time online bank anti-theft monitoring method.

[0047] Computer-readable storage media include, for example, various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0048] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A real-time online monitoring and anti-theft method for a bank, characterized in that: include: Obtain withdrawal data, withdrawal signals and current cash quality data; Determine the ATM intrusion signal through the withdrawal data, the withdrawal signal and the preset withdrawal judgment threshold, and output it to the user; Determine the current cash data by comparing the current cash quality data with a preset single cash quality threshold; Determine a cash theft signal through the current cash data, the preset remaining cash data and the preset environment deviation threshold, and output it to the user; The new remaining cash data is determined by the original remaining cash data and the withdrawal data, and replaces the original remaining cash data.

2. A bank real-time online monitoring anti-theft method according to claim 1, characterized in that: Also includes: Get time data; Determine automatic cash withdrawal speed data by using the current cash data and the time data; An abnormal withdrawal signal is determined by comparing the automatic withdrawal speed data with a preset withdrawal speed threshold and is output to the user.

3. A bank real-time online monitoring anti-theft method according to claim 2, characterized in that: Also includes: The current cash quality data is multiple; Determine centroid coordinate data by using a plurality of the current cash mass data and a preset cash distribution coordinate threshold; Determine coordinate offset data through the time data, the automatic withdrawal speed data and the centroid coordinate data; The abnormal withdrawal signal is determined and outputted through the coordinate offset data and a preset coordinate offset threshold.

4. A bank real-time online monitoring anti-theft method according to claim 3, characterized in that: Also includes: The coordinate shift threshold includes a coordinate shift tendency threshold and a jitter threshold; Determine coordinate offset tendency data and coordinate offset speed data through the coordinate offset data and the time data; Determine coordinate tendency state data by using the coordinate deviation tendency data and the coordinate deviation tendency threshold; Determine jitter data using the coordinate offset speed data and the time data; Determine jitter state data according to the jitter data and the jitter threshold; The abnormal withdrawal signal is determined and outputted through the coordinate inclination state data and the jitter state data.

5. A bank real-time online monitoring anti-theft method according to claim 2, characterized in that: Also includes: Obtain withdrawal data, withdrawal signals and withdrawal cash quality data; Determine the withdrawal status data through the withdrawal data, the withdrawal signal and a preset withdrawal judgment threshold; Determine the withdrawal amount status data through the withdrawal cash quality data, the single cash quality threshold and the withdrawal data; An unexpected withdrawal signal is determined and outputted through the withdrawal status data, the withdrawal amount status data and a preset unexpected threshold value.

6. A bank real-time online monitoring anti-theft method according to claim 5, characterized in that: Also includes: Determine the withdrawal difference data through the withdrawal status data, the single cash quality threshold and a plurality of continuous withdrawal cash quality data; Determine the withdrawal interval time data by using the time data and the withdrawal cash quality data; Determining withdrawal amount abnormal data by comparing the withdrawal difference data with a preset unexpected difference change threshold; Determine the withdrawal panic degree data through the withdrawal interval time data and the preset withdrawal degree data; The unexpected withdrawal signal is determined and outputted based on the withdrawal amount abnormality data and the withdrawal panic degree data.

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

8. A computer-readable storage medium, characterized in that: The computer program is stored which can be loaded by a processor and execute the real-time online monitoring anti-theft method for banks as claimed in any one of claims 1 to 6.

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