Intelligent emergency broadcast safe broadcast monitoring controller

Abstract

The invention relates to an intelligent emergency broadcast safe broadcast monitoring controller, which belongs to the technical field of emergency broadcast monitoring and comprises an emergency broadcast scheduling platform and a broadcast time plan management module. The emergency broadcast scheduling platform comprises a data acquisition module, a broadcast scheme monitoring and analysis module, a real-time audio stream monitoring and analysis module and an intelligent visual monitoring terminal management module, and the emergency broadcast scheduling platform is connected with a visual intelligent monitoring and control terminal. According to the intelligent emergency broadcast safe broadcast monitoring controller, broadcast task data, audio stream metadata of the IP broadcast microphone and equipment operation logs are integrated through the data acquisition module to carry out multi-dimensional dynamic monitoring on broadcast tasks, and if a certain broadcast task is triggered in an abnormal time period and the audio stream contains unauthorized content, the broadcast task is not triggered in the abnormal time period. The system can mark time violation and content abnormity at the same time and accurately position composite risks, so that the abnormity identification accuracy can be effectively improved, and the false report and missing report rate can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency broadcast monitoring, and particularly to a monitoring controller for the safe broadcast of intelligent emergency broadcasts. Background Art

[0002] Intelligent emergency broadcast is an intelligent emergency information release system built based on modern information technologies such as the Internet of Things, big data, artificial intelligence, 5G communication, etc., aiming to quickly, accurately, and efficiently transmit emergency information through intelligent means, and improve the early warning, response, and handling capabilities of public safety incidents.

[0003] In recent years, with the development of radio technology, illegal radio stations (commonly known as "black broadcasts") have frequently appeared in many places. Black broadcasts not only occupy the radio spectrum and disrupt the radio management order, but also broadcast bad information, which endangers the physical and mental health of the people, and even endangers social stability and national security. Therefore, it is necessary to monitor the broadcast content. Traditional intelligent emergency broadcasts have the following defects: 1. Lack of the ability to actively monitor the abnormal states of scheduled broadcast tasks and real-time audio streams, relying on manual inspections; 2. Unable to effectively identify illegal broadcast behaviors during unauthorized periods; 3. Insufficient linkage between the early warning mechanism and the visualization terminal; 4. Lack of intelligent analysis of the deviation in the execution of the broadcast plan.

[0004] In order to effectively solve the hidden dangers of the safe broadcast of the emergency broadcast system, a monitoring controller for the safe broadcast of intelligent emergency broadcasts is proposed. It can monitor various real-time and scheduled broadcast tasks of the emergency broadcast platform, real-time broadcast audio streams such as IP broadcast microphones, and can alarm in time if problems are found, preventing misbroadcasts and abnormal broadcast events, and improving the efficiency of broadcast safety monitoring. Summary of the Invention

[0005] The present invention provides a monitoring controller for the safe broadcast of intelligent emergency broadcasts, which solves the problems raised in the above background art, can effectively improve the security and emergency response efficiency of the broadcast system, and prevent misbroadcasts and abnormal broadcast events.

[0006] The solution of the present invention to the above technical problems is as follows: A monitoring controller for the safe broadcast of intelligent emergency broadcasts includes an emergency broadcast scheduling platform and a broadcast time plan management module. The emergency broadcast scheduling platform includes a data collection module, a broadcast plan monitoring and analysis module, a real-time audio stream monitoring and analysis module, and an intelligent visualization monitoring terminal management module. The emergency broadcast scheduling platform is connected to a visualization intelligent monitoring and control terminal. The data collection module includes a data source access layer, a capture network layer, and a device operation log collection unit. The broadcast time plan management module transmits broadcast task data to the broadcast plan monitoring and analysis module and the real-time audio stream monitoring and analysis module;

[0007] The real-time audio stream monitoring and analysis module includes an audio feature extraction unit, an abnormal pattern recognition unit, and a voice content comparison unit;

[0008] The broadcast time plan management module constructs a three-dimensional time coordinate system and a dynamic time window, and performs overlapping analysis on the time axis based on graph theory to achieve task conflict detection;

[0009] The intelligent visualization monitoring terminal management module includes a multimodal alarm interface, an audible and visual alarm device, and an operation log blockchain evidence storage unit;

[0010] The monitoring method includes the following steps:

[0011] S1: Data acquisition: The data acquisition module synchronously and real-timely obtains broadcast task data, audio stream metadata of IP broadcast microphones, and device operation logs at a cycle of 200 ms;

[0012] S2: Broadcast plan monitoring and analysis: The broadcast plan monitoring and analysis module constructs a preset broadcast plan digital fingerprint library according to the broadcast task data. The broadcast plan monitoring and analysis module uses the dynamic time warping algorithm (DTW) to compare the actual broadcast task with the preset plan. The comparison method adopts double verification. Primary verification: Timestamp compliance check. Advanced verification: Semantic content similarity analysis. After the comparison, a deviation evaluation report is generated;

[0013] S3: Real-time audio stream monitoring and analysis: The real-time audio stream monitoring and analysis module uses the sliding window detection method to monitor the audio stream. When any of the following conditions is detected, a three-level alarm is triggered: 1. A valid broadcast signal is detected during an unauthorized period, with a confidence level ≥ 85%; 2. The audio stream anomaly lasts for more than a set threshold, and the default threshold is 10 seconds; 3. The deviation degree between the broadcast task and the preset plan > 5%;

[0014] S4: Visualization terminal synchronous display: When the alarm is triggered, the intelligent visualization monitoring terminal management module traces the source path of the abnormal event based on the decision tree visualization through the device operation log data, the real-time spectrum feature comparison view, and the emergency treatment plan recommendation list. The visualization intelligent monitoring and control terminal can display the relevant content in real time and trigger the audible and visual alarm of the intelligent terminal, so as to timely inform the seats and duty personnel of the emergency broadcast scheduling platform for early warning prevention and timely handling to prevent misbroadcasting and abnormal broadcasting.

[0015] Based on the above technical solutions, the present invention can also be improved as follows.

[0016] Further, the broadcast task data includes task type, execution time, and content identifier. The audio stream metadata includes sampling rate, bit rate, and channel status. The operation log data includes network delay, device temperature, and power status.

[0017] Further, the deviation evaluation report includes a time offset, a content difference degree, and a device exception code.

[0018] Further, the audio feature extraction unit is used for FFT spectrum analysis and signal-to-noise ratio detection. The abnormal pattern recognition unit is used for silent segment detection, burst noise recognition, and audio interruption tracking. The speech content comparison unit performs similarity analysis based on the ASR text.

[0019] Further, the three-dimensional time coordinate system data includes year / month / day, hour / minute / second, and priority weight. The dynamic time window displays a whitelist for normal periods and a blacklist for high-risk periods.

[0020] Further, the multi-modal alarm interface includes GIS positioning, a waveform diagram, and a spectral waterfall diagram. The audible and visual alarm device includes a sub-band sound pressure control module and an RGB three-color LED matrix.

[0021] Further, the data source access layer is docked with the task database of the emergency broadcast scheduling control platform. The capture network layer realizes the capture of audio stream metadata of the IP broadcast microphone based on the DPDK data plane development kit. The device operation log collection unit uses the Flink stream processing engine to realize real-time cleaning and aggregation of logs, and adaptive sampling frequency adjustment. Normal state: once every 60 seconds; warning state: once every 1 second.

[0022] The beneficial effects of the present invention are as follows: The present invention provides a smart emergency broadcast safe broadcast monitoring controller, which has the following advantages:

[0023] 1. Compared with the traditional broadcast monitoring system that lacks the ability to actively monitor the abnormal states of scheduled broadcast tasks and real-time audio streams and relies on manual inspections, such a smart emergency broadcast safe broadcast monitoring controller conducts multi-dimensional dynamic monitoring of broadcast tasks by integrating broadcast task data, audio stream metadata of the IP broadcast microphone, and device operation logs through a data acquisition module. If a certain broadcast task is triggered during an abnormal period and the audio stream contains unauthorized content, the system can simultaneously mark the time violation and content abnormality, accurately locate the composite risk, thereby effectively improving the accuracy of abnormal recognition and reducing the false alarm and missed alarm rates.

[0024] 2. It solves the problem that the traditional system relies on a fixed schedule, cannot flexibly adapt to dynamic scenarios such as holidays and temporary control, and requires manual inspection of time conflicts. When the broadcast task time overlaps with an abnormal period, the system automatically marks it as a violation task and triggers an alarm to avoid manual omissions.

[0025] 3. The hierarchical alarm mechanism is adopted to assist the duty personnel in quickly locating the root cause of the problem through visual tracking. The visual intelligent monitoring and control terminal can display the traceability path of abnormal events in real time, the real-time spectrum feature comparison view, the recommended list of emergency treatment plans, and trigger the audible and visual alarm of the intelligent terminal, so as to timely inform the seat and duty personnel of the emergency broadcast dispatching platform for early warning prevention and timely handling to prevent misbroadcasting and abnormal broadcasting.

[0026] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly and implement it in accordance with the content of the specification, the following takes the preferred embodiments of the present invention and describes them in detail in conjunction with the drawings. The specific implementation manners of the present invention are given in detail by the following embodiments and their accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0028] Figure 1 is a schematic diagram of a smart emergency broadcast safe broadcast monitoring controller provided by an embodiment of the present invention;

[0029] Figure 2 is a schematic diagram of the structure of a visual intelligent monitoring and control terminal in a smart emergency broadcast safe broadcast monitoring controller provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The following combines the attached Figure 1-2 Describe the principles and features of the present invention. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention. In the following paragraphs, the present invention will be described more specifically by way of example with reference to the drawings. According to the following description and claims, the advantages and features of the present invention will be clearer. It should be noted that the drawings are all in a very simplified form and use non-precise scales, only for the purpose of conveniently and clearly assisting in explaining the purpose of the embodiments of the present invention.

[0031] It should be noted that when a component is referred to as being "fixed to" another component, it can be directly on the other component or there may also be an intermediate component. When a component is considered to be "connected" to another component, it can be directly connected to the other component or there may be an intermediate component at the same time. When a component is considered to be "disposed on" another component, it can be directly disposed on the other component or there may be an intermediate component at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs. The terms used in the description of the present invention herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0033] As Figure 1-2 shown, the present invention provides a monitoring controller for the safe broadcast of intelligent emergency broadcasts, including an emergency broadcast scheduling platform and a broadcast time plan management module. The emergency broadcast scheduling platform includes a data acquisition module, a broadcast plan monitoring and analysis module, a real-time audio stream monitoring and analysis module, and an intelligent visualization monitoring terminal management module. The emergency broadcast scheduling platform is connected to a visualization intelligent monitoring and control terminal. The data acquisition module includes a data source access layer, a capture network layer, and a device operation log acquisition unit. The broadcast time plan management module transmits broadcast task data to the broadcast plan monitoring and analysis module and the real-time audio stream monitoring and analysis module;

[0034] The real-time audio stream monitoring and analysis module includes an audio feature extraction unit, an abnormal pattern recognition unit, and a voice content comparison unit;

[0035] The broadcast time plan management module constructs a three-dimensional time coordinate system, a dynamic time window, and performs overlapping analysis based on the time axis of graph theory to achieve task conflict detection;

[0036] The intelligent visualization monitoring terminal management module includes a multi-modal alarm interface, an audible and visual alarm device, and an operation log blockchain evidence storage unit.

[0037] Preferably, the broadcast task data includes a task type, an execution time, and a content identifier. The audio stream metadata includes a sampling rate, a bit rate, and a channel state. The operation log data includes a network delay, a device temperature, and a power supply state.

[0038] Preferably, the deviation evaluation report includes a time offset, a content difference degree, and a device abnormal code.

[0039] Preferably, the audio feature extraction unit is used for FFT spectrum analysis and signal-to-noise ratio detection. The abnormal pattern recognition unit is used for silent segment detection, burst noise identification, and audio interruption tracking. The voice content comparison unit performs similarity analysis based on the ASR text.

[0040] Preferably, the three-dimensional time coordinate system data includes year / month / day, hour / minute / second, and priority weight. The dynamic time window displays a whitelist for normal periods and a blacklist for high-risk periods.

[0041] Preferably, the multi-modal alarm interface includes GIS positioning, waveform diagram, and spectral waterfall diagram, and the sound and light alarm device includes a sub-band sound pressure control module and an RGB three-color LED matrix.

[0042] The specific working principle and usage method of the present invention are as follows: S1: Data acquisition: The data acquisition module synchronously and real-time obtains broadcast task data, audio stream metadata of IP broadcast microphones, and device operation logs at a cycle of 200 ms. The data source access layer is docked with the task database of the emergency broadcast scheduling control platform. The audio stream metadata of the IP broadcast microphone is captured based on the DPDK data plane development kit in the network layer. The device operation log acquisition unit uses the Flink stream processing engine to realize real-time cleaning and aggregation of logs, and adaptive sampling frequency adjustment. Normal state: once every 60 seconds; warning state: once every 1 second.

[0043] S2: Broadcast plan monitoring and analysis: The broadcast plan monitoring and analysis module constructs a preset broadcast plan digital fingerprint library based on the broadcast task data. The broadcast plan monitoring and analysis module uses the dynamic time warping algorithm (DTW) to compare the actual broadcast task with the preset plan. The comparison method adopts double verification. Primary verification: timestamp compliance check; advanced verification: semantic content similarity analysis. After the comparison, a deviation evaluation report is generated. The broadcast plan digital fingerprint library adopts multi-dimensional feature extraction and coding. The spatio-temporal feature vector of the broadcast task data includes the task start timestamp accurate to milliseconds, the planned duration accurate to seconds, and the allowable error window Δt ∈ [1, 30] seconds.

[0044] The deviation evaluation report generation mechanism first performs time axis deviation detection. 1. Use the dynamic time warping (DTW) algorithm to align the planned and executed time series. The specific algorithm is as follows:

[0045] def dtw_distance(plan, actual):

[0046] # Build the cumulative cost matrix

[0047] matrix = np.zeros((len(plan), len(actual)))

[0048] for i in range(len(plan)):

[0049] for j in range(len(actual)):

[0050] cost = abs(plan[i] - actual[j])

[0051] if i == 0 and j == 0:

[0052] matrix[i,j] = cost

[0053] elif i == 0:

[0054] matrix[i,j] = matrix[i,j - 1]+cost

[0055] elif j == 0:

[0056] matrix[i,j] = matrix[i - 1,j]+cost

[0057] else:

[0058] matrix[i,j] = min(matrix[i - 1,j],matrix[i,j - 1],matrix[i - 1,j - 1])+cost

[0059] return matrix[-1,-1] # Return the final deviation value

[0060]

[0061] 2. Perform content consistency analysis, calculate audio similarity based on the improved Pearson correlation coefficient, and the specific algorithm is as follows:

[0062] Similarity=\frac{\sum(P_i-\bar{P})(A_i-\bar{A})}{\sqrt{\sum(P_i-\bar{P})^2\sum(A_i-\bar{A})^2}}

[0063] \quad\text{(P = planned spectrum, A = actual spectrum)},

[0064] Detect text semantic differences based on the cosine similarity of feature vectors of the BERT model

[0065] 3. Intelligent report generation engine, construct a fault knowledge graph:

[0066] graph LR

[0067] A[Time deviation] --> B{Cause analysis}

[0068] B --> C[Network latency]

[0069] B --> D[Device clock out of sync]

[0070] B --> E[Task queue blocked]

[0071] C --> F[Check switch status]

[0072] D --> G [Calibrate the PTP server];

[0073] Use the decision tree algorithm (C4.5) for root cause inference.

[0074] Finally, report the structured output. The specific algorithm is as follows:

[0075] {"report_id":"DEV2023-0715",

[0076] "deviation_type":["time offset","content distortion"],

[0077] "quantification_metrics":{"time_deviation":12.7,

[0078] "content_similarity":0.82,

[0079] "device_abnormal_code":0xE45A},

[0080] "impact_assessment":{"risk_level":"high risk","possible_impact_scope":["terminal group A","relay station 3"]},

[0081] "disposal_suggestions":["Immediately terminate task ID: EB2023-7A9B","Check the power supply line of the IP microphone"]}

[0082] S3: Real-time audio stream monitoring and analysis: The real-time audio stream monitoring and analysis module uses the sliding window detection method for audio stream monitoring. When any of the following conditions is detected, a level 3 alarm is triggered: 1. A valid broadcast signal is detected during an unauthorized period, with a confidence level ≥ 85%; 2. The audio stream anomaly persists for more than the set threshold, and the default threshold is 10 seconds; 3. The deviation degree of the broadcast task from the preset plan > 5%;

[0083] S4: Visual terminal synchronous display: When an alarm is triggered, the intelligent visual monitoring terminal management module traces the source path of the abnormal event through visual tracking based on the device operation log data, real-time spectrum feature comparison view, and emergency handling plan recommendation list. The visual intelligent monitoring and control terminal can display the relevant content in real time and trigger the audible and visual alarm of the intelligent terminal, so as to promptly inform the seat and duty personnel of the emergency broadcast scheduling platform for early warning and prevention, and handle it in a timely manner to prevent misbroadcasting and abnormal broadcasting.

[0084] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The content not described in detail in this specification belongs to the prior art known to those skilled in the art.

[0085] The above are only the preferred embodiments of the present invention, and do not impose any form of limitation on the present invention; any ordinary technician in the industry can smoothly implement the present invention as shown in the accompanying drawings of the specification and as described above; however, any minor changes, modifications and equivalent variations made by those skilled in the art within the scope of the technical solution of the present invention by using the technical content disclosed above are all equivalent embodiments of the present invention; at the same time, any equivalent changes, modifications and variations made to the above embodiments based on the essential technology of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A monitoring controller for the safe broadcast of intelligent emergency broadcasts, comprising an emergency broadcast scheduling platform and a broadcast time plan management module, characterized in that: The emergency broadcast scheduling platform includes a data acquisition module, a broadcast plan monitoring and analysis module, a real-time audio stream monitoring and analysis module, and a smart visualization monitoring terminal management module. The emergency broadcast scheduling platform is connected to a visualization smart monitoring and control terminal. The data acquisition module includes a data source access layer, a capture network layer, and a device operation log acquisition unit. The broadcast time plan management module transmits broadcast task data to the broadcast plan monitoring and analysis module and the real-time audio stream monitoring and analysis module; The real-time audio stream monitoring and analysis module includes an audio feature extraction unit, an abnormal pattern recognition unit, and a voice content comparison unit; The broadcast time plan management module constructs a three-dimensional time coordinate system and a dynamic time window, and performs overlapping analysis based on the time axis of graph theory to achieve task conflict detection; The smart visualization monitoring terminal management module includes a multi-modal alarm interface, an audible and visual alarm device, and an operation log blockchain evidence storage unit; The monitoring method includes the following steps: S1: Data acquisition: The data acquisition module synchronously and real-time obtains broadcast task data, audio stream metadata of the IP broadcast microphone, and device operation logs at a cycle of 200 ms; S2: Broadcast plan monitoring and analysis: The broadcast plan monitoring and analysis module constructs a preset broadcast plan digital fingerprint library according to the broadcast task data. The broadcast plan monitoring and analysis module uses the dynamic time warping algorithm (DTW) to compare the actual broadcast task with the preset plan. The comparison method adopts double verification. Primary verification: Timestamp compliance check. Advanced verification: Semantic content similarity analysis. After the comparison, a deviation evaluation report is generated; S3: Real-time audio stream monitoring and analysis: The real-time audio stream monitoring and analysis module uses the sliding window detection method to monitor the audio stream. When any of the following conditions is detected, a three-level alarm is triggered:

1. A valid broadcast signal is detected during an unauthorized period, and the confidence level ≥ 85%; 2. The audio stream anomaly lasts for more than the set threshold, and the default threshold is 10 seconds; 3. The deviation degree between the broadcast task and the preset plan > 5%; S4: Visualization terminal synchronous display: When the alarm is triggered, the smart visualization monitoring terminal management module traces the source path of the abnormal event based on the decision tree visualization of the device operation log data, the real-time spectrum feature comparison view, and the emergency handling plan recommendation list. The visualization smart monitoring and control terminal can display the relevant content in real time and trigger the audible and visual alarm of the smart terminal, so as to timely inform the seat and duty personnel of the emergency broadcast scheduling platform for early warning prevention and timely handling to prevent misbroadcast and abnormal broadcast.

2. The intelligent emergency broadcast safety broadcast monitoring controller according to claim 1, characterized in that The broadcast task data includes task type, execution time, and content identifier. The audio stream metadata includes sampling rate, bit rate, and channel status. The operation log data includes network delay, device temperature, and power status.

3. The intelligent emergency broadcast safety broadcast monitoring controller according to claim 1, characterized in that, The deviation evaluation report includes time offset, content difference degree, and device abnormal code.

4. The intelligent emergency broadcast safety broadcast monitoring controller according to claim 1, wherein The audio feature extraction unit is used for FFT spectrum analysis and signal-to-noise ratio detection. The abnormal pattern recognition unit is used for silent segment detection, burst noise recognition, and audio interruption tracking. The voice content comparison unit performs similarity analysis based on the ASR text.

5. The intelligent emergency broadcast safe broadcast monitoring controller according to claim 1, characterized in that, The three-dimensional time coordinate system data includes year / month / day, hour / minute / second, and priority weight, and the dynamic time window displays the white list during normal periods and the black list during high-risk periods.

6. The intelligent emergency broadcast safe broadcast monitoring controller according to claim 1, characterized in that, The multi-modal alarm interface includes GIS positioning, waveform diagram, and spectral waterfall diagram, and the audible and visual alarm device includes a frequency-band segmented sound pressure control module and an RGB three-color LED matrix.

7. The intelligent emergency broadcast safety broadcast monitoring controller according to claim 1, wherein, The data source access layer is docked with the task database of the emergency broadcast scheduling control platform. The capture network layer realizes the capture of audio stream metadata of the IP broadcast microphone based on the DPDK data plane development kit. The device operation log collection unit uses the Flink stream processing engine to realize real-time cleaning and aggregation of logs, and adaptive sampling frequency adjustment. Normal state: once every 60 seconds, warning state: once every 1 second.

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