A method for detecting abnormal data of urban infrastructure

Abstract

This application discloses a method for detecting abnormal data in urban infrastructure, which relates to the field of data processing technology. The method comprises: obtaining occlusion data collected by infrared sensors and barrier gate passage records from a barrier lift monitoring system; if the occlusion data and the barrier gate passage records do not meet a matching condition, the barrier gate passage record is determined to be abnormal data. The purpose of this method is to reduce the detection cost of abnormal barrier gate records.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method for detecting abnormal data of urban infrastructure. Background Art

[0002] Currently, vehicle access barriers are widely used in various scenarios, such as site entrances and exits, and weighbridge measurement. When a vehicle arrives at the barrier, the license plate recognition device captures and analyzes the license plate information, and then updates the entry and exit data before allowing the vehicle to pass.

[0003] To detect abnormal vehicle traffic, a backup license plate recognition device is typically deployed alongside the original license plate recognition device to obtain backup entry and exit data. This backup entry and exit data can then be compared with the original entry and exit data, eliminating any duplicate data and leaving only abnormal entry and exit data.

[0004] However, deploying an additional license plate recognition system requires installing front-end equipment such as license plate recognition cameras and induction coils, which results in a significant investment in capital and manpower. Therefore, existing solutions for detecting abnormal gate records are costly.

[0005] The above content is only used to assist in understanding the technical solution of this application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0006] The main purpose of this application is to provide a method for detecting abnormal data of urban infrastructure, aiming to solve the technical problem of high detection cost of abnormal records of gates.

[0007] To achieve the above objectives, this application proposes a method for detecting abnormal data in urban infrastructure, which includes:

[0008] Obtain the occlusion data collected by the infrared sensor and the gate passage records in the lifting barrier monitoring system;

[0009] If the occlusion data and the barrier gate passage record do not meet the matching condition, the barrier gate passage record is determined to be abnormal data.

[0010] In one embodiment, if the occlusion data and the barrier gate passage record do not meet a matching condition, the step of determining that the barrier gate passage record is abnormal data includes:

[0011] Determining the occlusion record in the occlusion data and the barrier gate operation in the barrier gate passage record;

[0012] If the number of occlusions in the occlusion record is greater than the number of instructions for the gate operation, the gate passage record is determined to be abnormal data and a human tampering warning is output;

[0013] If the number of occlusions in the occlusion record is less than the number of instructions for the barrier gate operation, the barrier gate passage record is determined to be abnormal data, and a barrier gate function abnormality warning is output.

[0014] In one embodiment, if the occlusion data and the barrier gate passage record do not meet a matching condition, the step of determining that the barrier gate passage record is abnormal data includes:

[0015] Determining an operation duration between adjacent occlusion records in the occlusion data;

[0016] Determine the time duration of the gate raising and lowering according to the gate passage record;

[0017] If the operation duration is longer than the barrier lift-down duration, the barrier pass record is determined to be abnormal data, and a vehicle following or human tampering warning is output.

[0018] In one embodiment, the adjacent occlusion records include a first occlusion record and a second occlusion record, and the step of determining the operation duration between adjacent occlusion records in the occlusion data includes:

[0019] Determine the barrier gate lift operation time in the barrier gate passage record;

[0020] Determining the first blocking record and the second blocking record in the blocking data according to the gate lift operation time;

[0021] An operation duration between the first occlusion record and the second occlusion record is determined.

[0022] In one embodiment, after the step of determining that the barrier gate passage record is abnormal data if the occlusion data and the barrier gate passage record do not meet the matching condition, the method further includes:

[0023] If the occlusion data or the barrier gate passage record does not meet the quantity condition, the barrier gate passage record is determined to be abnormal data.

[0024] In one embodiment, if the occlusion data or the barrier gate passage record does not meet the quantity condition, the step of determining that the barrier gate passage record is abnormal data includes:

[0025] Determining a pole-raising occlusion record and a pole-lowering occlusion record in the occlusion data;

[0026] If the number of the barrier raising blocking record and the barrier lowering blocking record is inconsistent, the barrier gate passage record is determined to be abnormal data, and a barrier gate function abnormality warning is output.

[0027] In one embodiment, the infrared sensor is an infrared transmitting sensor and an infrared receiving sensor. Before the step of obtaining the occlusion data collected by the infrared sensor and the gate passage record in the lifting bar monitoring system, the following steps are further included:

[0028] Controlling the infrared transmitting sensor to transmit infrared rays to the infrared receiving sensor;

[0029] When the infrared receiving sensor detects that the infrared ray is interrupted, the infrared receiving sensor is controlled to generate the shielding data.

[0030] In one embodiment, before the step of obtaining the occlusion data collected by the infrared sensor and the gate passage record in the lifting bar monitoring system, the following steps are further included:

[0031] When a user acquisition request is detected, obtaining the user identity of the user;

[0032] If the user identity meets the permission conditions, the steps of obtaining the occlusion data collected by the infrared sensor and the gate passage record in the lifting bar monitoring system are executed.

[0033] One or more technical solutions proposed in this application have at least the following technical effects:

[0034] This application provides a method for detecting abnormal data in urban infrastructure. By comparing occlusion data collected by infrared sensors with barrier gate passage records in a barrier lift monitoring system, it can accurately determine whether barrier gate passage records are consistent with actual vehicle traffic, thereby detecting abnormal data. Furthermore, compared to backup license plate recognition devices, infrared sensors are less expensive and more flexible to install. Therefore, this solution is low-cost to implement and does not conflict with existing equipment during installation, effectively shortening the installation cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0037] Figure 1 A flowchart of a first embodiment of a method for detecting abnormal data in urban infrastructure provided by this application;

[0038] Figure 2A flowchart of a second embodiment of a method for detecting abnormal data in urban infrastructure provided by this application;

[0039] Figure 3 A schematic diagram of a scenario provided in Example 2 of a method for detecting abnormal data of urban infrastructure in this application;

[0040] Figure 4 A schematic diagram of a scenario provided in Example 2 of a method for detecting abnormal data of urban infrastructure in this application;

[0041] Figure 5 A flowchart of a third embodiment of a method for detecting abnormal data in urban infrastructure provided by this application;

[0042] Figure 6 A schematic diagram of a scenario provided in Example 3 of a method for detecting abnormal data in urban infrastructure according to this application;

[0043] Figure 7 A flowchart of a third embodiment of a method for detecting abnormal data in urban infrastructure provided by this application;

[0044] Figure 8 A flowchart of a fourth embodiment of a method for detecting abnormal data in urban infrastructure provided by this application;

[0045] Figure 9 A flowchart of a fourth embodiment of a method for detecting abnormal data in urban infrastructure provided by this application;

[0046] Figure 10 A schematic diagram of a scenario provided in Example 4 of a method for detecting abnormal data of urban infrastructure in this application;

[0047] Figure 11 A flowchart of a fifth embodiment of a method for detecting abnormal data in urban infrastructure provided by this application;

[0048] Figure 12 Schematic diagram of an infrared radiation sensor provided in Example 5 of a method for detecting abnormal data of urban infrastructure in this application;

[0049] Figure 13 A schematic diagram of the detection results provided in Example 5 of a method for detecting abnormal data in urban infrastructure according to this application;

[0050] Figure 14 This is a flow chart of Example 6 of a method for detecting abnormal data in urban infrastructure provided by this application.

[0051] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0053] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0054] The main solution of the embodiment of the present application is: to obtain the occlusion data collected by the infrared sensor and the barrier gate passage record in the lifting bar monitoring system; if the occlusion data and the barrier gate passage record do not meet the matching conditions, the barrier gate passage record is determined to be abnormal data.

[0055] A common abnormal record detection solution involves deploying a backup license plate recognition device in addition to the original license plate recognition device to obtain backup entry and exit data. This backup entry and exit data can then be compared with the original entry and exit data, eliminating duplicate data and leaving only abnormal entry and exit data. This solution has the following drawbacks:

[0056] 1. High cost. Deploying an additional license plate recognition system requires installing front-end equipment such as license plate recognition cameras and induction coils, which results in a significant investment of capital and manpower.

[0057] 2. The installation period is long and the construction workload is substantial. This process not only involves deep excavation to lay the lines, but also requires meticulous backfilling to ensure the ground is restored to a flat surface. Furthermore, precise commissioning of the license plate recognition cameras is essential, further extending the overall installation period. 3. Site restrictions apply. Especially in scenarios where license plate recognition systems are already deployed, adding a backup system may conflict with the existing system.

[0058] The non-mandatory nature of barrier gate specifications leads to some discrepancies in technical standards. Despite this, most barrier gate systems generally only support two basic states: open and closed, lacking the ability to achieve a half-open state.

[0059] It's worth noting that while some barrier gates allow for remote control to open and close, this operation often doesn't generate corresponding records, creating a gap in oversight. Furthermore, some barrier gate systems grant "post terminals" the ability to directly modify and delete data, which undoubtedly creates the potential for human intervention in barrier gate operations and circumvent oversight. Therefore, in certain application scenarios, the problem of human manipulation and lack of oversight does exist.

[0060] This application provides a solution that uses infrared sensors to monitor barrier pole occlusion data, then matches it with barrier pole passage records in a barrier pole monitoring system. If the two do not match, abnormal data is determined to be present. This solution uses infrared sensors instead of backup license plate recognition devices. Due to the low cost of infrared sensors, it can reduce the cost of detecting abnormal barrier pole records.

[0061] It should be noted that the implementation entity of this solution can be a computing service device with data processing, network communication, and program execution capabilities, such as a tablet computer, personal computer, mobile phone, etc., or a barrier gate abnormal data detection device capable of performing the above functions. The following embodiments are described using the barrier gate abnormal data detection device as an example.

[0062] Based on this, the embodiment of the present application provides a method for detecting abnormal data of urban infrastructure, referring to Figure 1 , Figure 1 This is a flow chart of a first embodiment of a method for detecting abnormal data in urban infrastructure according to the present application.

[0063] In this embodiment, the method for detecting abnormal data of urban infrastructure includes steps S10 to S20:

[0064] Step S10, obtaining the occlusion data collected by the infrared sensor and the gate passage record in the lifting bar monitoring system;

[0065] It's important to note that the infrared sensor is installed near the barrier pole to monitor its movement. As the barrier pole rises and falls, it blocks the infrared light that would otherwise directly hit the sensor, causing changes in the infrared radiation received by the sensor and generating corresponding occlusion data.

[0066] It should be noted that the barrier gate passage record in the barrier lift monitoring system is a record of a series of key events and states generated when a vehicle passes through the barrier gate, including but not limited to the following:

[0067] Vehicle Arrival: A vehicle approaches and stops in front of the barrier, preparing to pass through. This is usually triggered by a vehicle detector such as a ground induction coil, radar, or infrared sensor, detecting the presence of the vehicle.

[0068] Barrier lift operation: After confirming that the vehicle is legal and meets the conditions for passage, the barrier begins to lift the barrier. This can be triggered by a variety of factors, including successful license plate recognition, manual confirmation, remote control signals, etc.

[0069] Barrier Open: The barrier is fully raised and in the open state, allowing vehicles to pass. This can be determined based on the barrier's movement angle and distance.

[0070] Vehicle passing through the barrier: The vehicle passes through the barrier area quickly or slowly after the barrier is opened.

[0071] Vehicle leaves the gate: The vehicle completely passes through the gate area and continues to move forward.

[0072] Barrier Barrier Dropping: After a vehicle leaves the barrier, the barrier barrier begins to drop. This is usually triggered by a vehicle detector detecting the vehicle's departure, a preset delay time, or a remote control signal.

[0073] Barrier status closed: The barrier pole is completely down and in the closed state.

[0074] During the entire process, the barrier lifting monitoring system will record the timestamps, vehicle information, gate status and other information of each link in real time, and store it in the database for subsequent query and analysis.

[0075] Optionally, the processor proactively sends a data acquisition instruction to the infrared sensor and then receives occlusion data from the infrared sensor based on the instruction. Alternatively, the infrared sensor proactively sends occlusion data to the processor periodically or in real time. The processor can then directly use this occlusion data when performing anomaly detection. These methods effectively acquire occlusion data collected by the infrared sensor for subsequent analysis and processing.

[0076] Optionally, the processor can also obtain the gate passage record in the lifting bar monitoring system in an active or passive manner. The principle is the same as above and will not be repeated here.

[0077] Step S20: If the occlusion data and the barrier gate passage record do not meet the matching condition, the barrier gate passage record is determined to be abnormal data.

[0078] It's important to note that because remote control often doesn't generate corresponding records, and the guard booth has modification and deletion permissions, the barrier pass records in the barrier lift monitoring system are unreliable or at risk of tampering. However, the occlusion data detected by the infrared sensor, as a relatively independent data source, is highly stable and reliable and less susceptible to tampering. Therefore, these two related but independent data sources can be compared to verify their consistency.

[0079] Optionally, perform matching analysis from at least one of the following dimensions:

[0080] Time dimension: If the occlusion data shows that the barrier pole is blocked within a certain time period, but there is no corresponding vehicle passing record in the barrier passage record, or there is a significant deviation between the time of the vehicle passing record and the time of the occlusion data, it can be determined as a time mismatch.

[0081] For example, each obstruction record is retrieved from the obstruction database. For each obstruction record, its obstruction timestamp is determined. Based on this timestamp, a time window is extended forward and backward by a certain amount, such as 1 minute. Within this time window, the barrier gate passage record database is queried to see if there is a corresponding vehicle passing record.

[0082] If no vehicle passing record is found within the time window, it is determined to be a time mismatch.

[0083] If a vehicle passing record is found within the time window, the timestamp of that record is compared with the timestamp of the obstruction record, and the time difference between the two is calculated to determine whether there is a significant deviation, such as exceeding the preset time difference. If a significant deviation is found, it is also determined to be a time mismatch.

[0084] State dimension: If the occlusion data indicates that the barrier pole is blocked during a specific period of time, but the barrier pass record shows that no vehicles passed during that period, or if the barrier pole should be open but is actually closed, it can be determined as a state mismatch.

[0085] For example, all barrier pole records that were not blocked within a specific time period are retrieved from the blocking database. For each record, the unblocked time period is determined. Within the above time period, the barrier pole passage record database is queried to find all passage records within the time period.

[0086] If the barrier is determined to be in the open state based on the occlusion data, but is actually in the closed state during the time period based on the barrier passage record, it is determined to be a state mismatch.

[0087] Logical Dimension: In some cases, there may be logical inconsistencies between occlusion data and barrier gate pass records. For example, the occlusion data may show that the barrier gate pole was blocked multiple times continuously, but the barrier gate pass record only records a single vehicle passing through. In this case, the data can also be considered mismatched.

[0088] For example, a time window is set, such as 8:00-12:00. The number of occlusions within this time window is then counted in the occlusion data database, and the number of vehicles passing through this time window is counted in the gate passage record database. If the number of occlusions / 2 is not equal to the number of vehicles passing through, it indicates a logical contradiction.

[0089] Since the default occlusion data has a higher priority, the gate passage record is determined to be abnormal data.

[0090] This embodiment provides a method for detecting abnormal data in urban infrastructure. By comparing occlusion data collected by infrared sensors with barrier gate passage records from a barrier lift monitoring system, it can accurately determine whether the barrier gate passage records match actual vehicle traffic, thereby detecting abnormal data. Furthermore, compared to backup license plate recognition devices, infrared sensors are less expensive and more flexible to install. Therefore, this solution is cost-effective to implement and does not conflict with existing equipment during installation, effectively shortening the installation cycle.

[0091] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 2 Step S20 may include steps A10 to A30:

[0092] Step A10, determining the occlusion record in the occlusion data and the barrier gate operation in the barrier gate passage record;

[0093] Step A20: If the number of obstructions in the obstruction record is greater than the number of gate operation instructions, the gate passage record is determined to be abnormal data, and a tampering warning is output;

[0094] Step A30: If the number of occlusions in the occlusion record is less than the number of instructions for the barrier gate operation, the barrier gate passage record is determined to be abnormal data, and a barrier gate function abnormality warning is output.

[0095] Under normal circumstances, each movement of the barrier pole should be triggered by a clear command.

[0096] like Figure 3 As shown, if the number of occlusions in the occlusion record exceeds the number of gate operation instructions, that is, the occlusion record cannot be matched to the corresponding gate pass record, it means that the gate has been opened abnormally. For example, some gates have been opened manually and no pass records have been generated, or some pass records have been manually deleted. Therefore, in this case, the gate pass record is judged to be abnormal data and a tampering warning is output.

[0097] like Figure 4 As shown, if the occlusion record shows fewer barrier pole movements than the number of commands, this may mean that the barrier system did not correctly respond to all commands, or that the barrier pole did not move as expected after receiving the command. This situation usually points to a malfunction or problem with the barrier system itself, such as a mechanical failure, electrical failure, or sensor failure. Therefore, in this case, the barrier passage record is considered abnormal data and a barrier function abnormality warning is issued.

[0098] This embodiment provides a method for detecting abnormal data in urban infrastructure. Unlike time-based comparison, this solution detects anomalies by directly comparing the number of occlusions and the number of gate operation instructions. This method is relatively simple and direct. Furthermore, by comparing the relationship between the number of occlusions and the number of instructions, this solution can clearly determine whether the anomaly is caused by human intervention or a problem with the gate system itself. This precise classification method directly identifies the cause of the anomaly.

[0099] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above introduction and will not be described in detail later. Figure 5 Step S20 may include steps B10 to B30:

[0100] Step B10, determining the operation duration between adjacent occlusion records in the occlusion data;

[0101] Step B20, determining the barrier gate raising and lowering time according to the barrier gate passage record;

[0102] Step B30: If the operation duration is longer than the barrier gate raising and lowering duration, the barrier gate passage record is determined to be abnormal data, and a vehicle following or human tampering warning is output.

[0103] On the one hand, every time a vehicle passes through the barrier, the barrier will open and close once. The infrared sensor will detect two occlusion records in succession and calculate the operation time between these adjacent occlusion records to represent the actual time consumed by this passage.

[0104] On the other hand, the gate lifting and lowering time refers to the normal time required to go from a fully closed state to a fully open state.

[0105] Optionally, the barrier lift duration can be a preset duration set by technicians based on the barrier's site differences, power parameters, and other factors. This duration is the maximum time it takes for the barrier pole to complete the opening and closing operations when a vehicle passes through the barrier normally. In actual use, commands are used to obtain the preset barrier lift duration associated with the barrier's passage record, such as 1 minute.

[0106] Reference Figure 6 If the operation duration exceeds the barrier lift / lowering time threshold, it indicates a possible vehicle following the vehicle. This means the vehicle is being followed by another vehicle while passing through the barrier. In this case, the operation duration includes the time it takes for both vehicles to pass, and the barrier arm remains open for an extended period, exceeding the normal range. In this case, the barrier passage record is considered abnormal and a vehicle following warning is issued.

[0107] Optionally, the barrier lift duration is dynamically calculated based on the actual status. In actual application, when a vehicle passes through the barrier, the first time point corresponding to the barrier lift operation and the second time point corresponding to the barrier closing state are determined in the barrier passage record. The time interval between the first and second time points is then used as the barrier lift duration.

[0108] If the operation duration exceeds the threshold for the gate lift and lowering duration, it indicates possible tampering. Someone may have tampered with the gate pass record to evade tolls or for other purposes. In this case, the gate pass record is considered abnormal data and a tampering warning is output.

[0109] Furthermore, while the method of triggering a single detection with a single record can achieve high real-time performance, this approach places significant demands on processing resources, potentially impacting stability and longevity. With this in mind, this solution can adopt a phased detection strategy. Specifically, a fixed interval can be set, such as automatically initiating an anomaly detection round every two hours. This approach not only effectively reduces the pressure of real-time computing but also enables the timely detection and resolution of potential anomalies.

[0110] Reference Figure 7 , step B10 may include steps B11 to B13:

[0111] Step B11, determining the barrier gate lifting operation time in the barrier gate passage record;

[0112] Step B12, determining the first blocking record and the second blocking record in the blocking data according to the gate lift operation time;

[0113] Step B13: Determine the operation duration between the first occlusion record and the second occlusion record.

[0114] First, determine the node of the barrier lift operation in the barrier passage record, and read its associated third time node, such as 12:00, to define the obstruction record generated by this passage.

[0115] Then, we construct a timeline of the occlusion data to clearly show the temporal distribution of all occlusion records. On this timeline, we mark the timestamp corresponding to the third time node, and then set the first occlusion record after this timestamp as the first occlusion record, and the second occlusion record after this timestamp as the second occlusion record.

[0116] Finally, the time difference between the first occlusion record and the second occlusion record is calculated, which is the operation time consumed by this passage.

[0117] This embodiment provides a method for detecting abnormal data in urban infrastructure. By comparing operation duration with the gate lift and lowering duration, it can accurately identify abnormal or irregular behavior. When the operation duration is significantly greater than the gate lift and lowering duration, it is likely due to reasons such as vehicle tracking or human tampering. This determination method has high accuracy and can effectively and accurately monitor vehicle passage through the gate.

[0118] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 8 , step S20 may include step C10:

[0119] Step C10: If the blocking data or the barrier gate passage record does not meet the quantity condition, the barrier gate passage record is determined to be abnormal data.

[0120] In one feasible implementation, based on historical barrier passage records and obstruction data, traffic flow trends are analyzed daily, hourly, or within specific time windows. A traffic flow prediction model is then developed using statistical methods such as time series analysis and regression analysis, or machine learning algorithms.

[0121] Define a time window, such as one hour, for analyzing traffic records. Calculate the predicted traffic volume for this time window using the traffic flow prediction model. Then, determine the actual traffic volume for this time window based on obstruction data or barrier gate traffic records. If the difference between the actual traffic volume and a set threshold exceeds a preset difference, the barrier gate traffic record is considered abnormal.

[0122] In one possible embodiment, referring to Figure 9 , step C10 may include steps C11~C12:

[0123] Step C11, determining the pole-raising occlusion record and the pole-lowering occlusion record in the occlusion data;

[0124] Step C12: If the number of the barrier lift blocking record and the barrier drop blocking record is inconsistent, the barrier gate passage record is determined to be abnormal data, and a barrier gate function abnormality warning is output.

[0125] Under normal circumstances, a vehicle's passage triggers one barrier lift and one barrier drop. Therefore, barrier lift and barrier drop operations appear in pairs in the barrier pass record. Accordingly, the occlusion data detected by the infrared sensor should also appear in pairs.

[0126] It is known that in the occlusion data collection stage, the state is defined as 0 when no occlusion is detected, and the state is 1 when occlusion is detected.

[0127] During the data processing phase, the number of transitions from 0 to 1 and from 1 to 0 is counted. If the number of transitions is equal, the quantity condition is considered to be met and the barrier gate passage record is normal. If the number of transitions does not match, indicating an unpaired occlusion operation, the quantity condition is determined to be not met and the barrier gate passage record is abnormal data.

[0128] like Figure 10 As shown in the figure, when only a single blocking signal is detected, and the signal is close to the vehicle entry record in the barrier gate passage record, then the barrier gate was opened but not closed normally.

[0129] It can be understood that this solution does not rely on traffic flow prediction models or external factors, but directly makes judgments based on the number of barrier lifting and lowering records. It has low data requirements and small computational complexity, so it can process data faster and give judgment results.

[0130] This embodiment provides a method for detecting abnormal data in urban infrastructure. It performs single-dimensional analysis based on occlusion data or gate passage records. A simple comparison can be used to determine whether the data is abnormal. This simplicity makes the detection logic easy to implement and maintain.

[0131] Based on the first embodiment of the present application, in the fifth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above introduction and will not be described in detail later. Figure 11 Before step S10, the method for detecting abnormal data of urban infrastructure further includes steps D10 to D20:

[0132] Step D10, controlling the infrared transmitting sensor to transmit infrared rays to the infrared receiving sensor;

[0133] Step D20 , when the infrared receiving sensor detects that the infrared ray is interrupted, controlling the infrared receiving sensor to generate the shielding data.

[0134] It is understandable that there are many ways to set up an infrared sensor near the barrier pole to detect the operation of the barrier pole.

[0135] For example, an infrared distance sensor is installed on the ground at the bottom of the barrier pole. When the barrier pole is raised, the distance value detected by the infrared distance sensor will increase accordingly as the pole gradually rises. Conversely, when the barrier pole is lowered and gradually approaches the ground, the distance value detected by the sensor will gradually decrease, thereby determining the obstruction situation.

[0136] This plan Figure 12As shown in the figure, an infrared sensor is installed above one end of the barrier gate near the rotating shaft. When the barrier gate is closed or open, it will not block the infrared sensor. During the opening and closing process, the barrier gate rod will pass through the infrared sensor, thereby detecting all lifting and lowering activities of the barrier gate.

[0137] In actual application, the lifting pole monitoring system and the infrared sensor are synchronized through the same network time protocol standard time server to ensure that the time of the two is consistent.

[0138] First, the infrared sending sensor is controlled to start working and emit infrared rays towards the direction of the infrared receiving sensor.

[0139] Generally, the infrared receiving sensor can receive the infrared ray normally.

[0140] However, if the infrared light encounters a barrier pole during its transmission, it will be blocked or reflected, resulting in the infrared receiving sensor being unable to receive the complete infrared signal. Once the infrared receiving sensor detects an interruption in the infrared light, it converts this event into an electrical signal or digital signal and generates corresponding obstruction data.

[0141] Reference Figure 13 , define the state as 0 when no occlusion is detected and the state as 1 when occlusion is detected.

[0142] This embodiment provides a method for detecting abnormal data of urban infrastructure, which uses infrared interruption to determine the obstruction situation. The detection of the obstruction situation is more direct and sensitive, will not be affected by other environmental factors, and can accurately detect the obstruction situation of the gate pole in real time.

[0143] Based on the first embodiment of the present application, in the sixth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above introduction and will not be described in detail later. Figure 14 Before step S10, the method for detecting abnormal data of urban infrastructure further includes steps E10 to E20:

[0144] Step E10: when a user's acquisition request is detected, acquiring the user's identity;

[0145] Step E20: If the user identity meets the permission conditions, the step of obtaining the occlusion data collected by the infrared sensor and the gate passage record in the lifting bar monitoring system is executed.

[0146] When a user wants to access or obtain infrared sensor data and gate pass records, a request is initiated. This request can be submitted through user interfaces such as web pages, apps, and consoles.

[0147] Upon receiving the request, the processor retrieves user identity information, including username, password, token, and biometric information. It then checks whether the user's identity satisfies the required permissions to access infrared sensor data and barrier pass records, including but not limited to the user's role, responsibilities, security level, and other factors.

[0148] If the user identity meets the permission conditions, the subsequent steps will be executed, namely obtaining the occlusion data collected by the infrared sensor and the gate passage records in the lifting barrier monitoring system.

[0149] This embodiment provides a method for detecting abnormal data in urban infrastructure. Before detecting abnormal data, user identity verification is performed. This step ensures that only authorized users can access the data, preventing malicious tampering with obscured data and gate pass records, thereby ensuring data security and privacy.

[0150] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the method for detecting abnormal data of urban infrastructure in the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0151] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for detecting abnormal data of urban infrastructure, characterized in that: The method comprises: Control the infrared sending sensor to transmit infrared rays to the infrared receiving sensor; When the infrared receiving sensor detects that the infrared ray is interrupted, the infrared receiving sensor is controlled to generate blocking data, wherein the blocking data includes a blocking record and an adjacent blocking record, and the adjacent blocking record includes a first blocking record and a second blocking record; Obtain gate passage records from the lift monitoring system; If the occlusion data and the barrier gate passage record do not meet the matching conditions, the barrier gate passage record is determined to be abnormal data, wherein the occlusion record in the occlusion data and the barrier gate operation in the barrier gate passage record are determined; if the number of occlusions in the occlusion record is greater than the number of instructions for the barrier gate operation, the barrier gate passage record is determined to be abnormal data, and a warning of human tampering is output; if the number of occlusions in the occlusion record is less than the number of instructions for the barrier gate operation, the barrier gate passage record is determined to be abnormal data, and a warning of abnormal barrier function is output; the operation time between adjacent occlusion records in the occlusion data is determined; the barrier gate lifting and lowering time is determined according to the barrier gate passage record; if the operation time is greater than the barrier gate lifting and lowering time, the barrier gate passage record is determined to be abnormal data, and a warning of following a vehicle or human tampering is output; If the occlusion data or the barrier gate passage record does not meet the quantity condition, the barrier gate passage record is determined to be abnormal data.

2. The method according to claim 1, wherein The step of determining the operation duration between adjacent occlusion records in the occlusion data comprises: Determine the barrier gate lift operation time in the barrier gate passage record; Determining the first blocking record and the second blocking record in the blocking data according to the gate lift operation time; An operation duration between the first occlusion record and the second occlusion record is determined.

3. The method according to claim 1, wherein If the occlusion data or the gate passage record does not meet the quantity condition, the step of determining that the gate passage record is abnormal data includes: Determining a pole-raising occlusion record and a pole-lowering occlusion record in the occlusion data; If the number of the barrier raising blocking record and the barrier lowering blocking record is inconsistent, the barrier gate passage record is determined to be abnormal data, and a barrier gate function abnormality warning is output.

4. The method according to claim 1, wherein Before the step of obtaining the gate passage record in the lifting bar monitoring system, the method further includes: When a user acquisition request is detected, obtaining the user identity of the user; If the user identity meets the permission conditions, the step of obtaining the gate passage record in the lifting barrier monitoring system is executed.

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