Low-power-consumption alarm method and system based on hybrid positioning

Abstract

The invention discloses a low-power-consumption alarm method and system based on hybrid positioning, and relates to the technical field of Internet of Things and intelligent security, and the method comprises the steps: dynamically distributing the time slot of a 5G signal and the transmitting frequency of a UWB pulse through a heterogeneous network time-frequency resource cooperation mechanism, and collecting the strength data of the 5G signal and a UWB arrival time measurement value in real time; based on the 5G signal strength data and the UWB arrival time measurement value, calculating three-dimensional coordinates of the terminal equipment in real time by using a dynamic weight fusion algorithm, and storing the three-dimensional coordinates into an annular buffer queue; extracting continuous three-dimensional coordinate data from the annular buffer queue, calculating a displacement integral and an acceleration change rate, confirming abnormal behaviors of the detection terminal equipment in combination with a dual threshold mechanism and delay, and generating an encrypted trigger instruction packet; according to the invention, through a heterogeneous network time-frequency resource cooperation mechanism, the time slot of the 5G signal and the emission frequency of the UWB pulse are dynamically allocated, and the resource utilization rate and the positioning data acquisition efficiency are significantly improved.

Description

Technical Field

[0001] The present invention relates to the technical fields of the Internet of Things and intelligent security, and in particular to a low-power alarm method and system based on hybrid positioning. Background Art

[0002] In recent years, with the rapid development of the Internet of Things (IoT) and intelligent devices, positioning technologies have been increasingly widely used in fields such as security, logistics, and smart homes. Traditional positioning technologies mainly rely on single technologies such as the Global Positioning System (GPS), Wi-Fi, and Bluetooth. However, these technologies have significant limitations in terms of accuracy, power consumption, and applicable scenarios. To address these issues, hybrid positioning technologies have emerged, which improve positioning accuracy and reliability by integrating multiple positioning technologies (such as 5G, Ultra-Wideband UWB, etc.). 5G technology provides new possibilities for high-precision positioning with its high bandwidth, low latency, and large-scale connection capabilities; while UWB technology has become an ideal choice for indoor positioning with its centimeter-level high-precision positioning ability. However, existing hybrid positioning technologies still face many challenges in practical applications, especially in aspects such as resource coordination, power consumption optimization, and abnormal behavior detection.

[0003] In the prior art, the resource coordination mechanism of hybrid positioning systems usually adopts a static allocation strategy and cannot dynamically adjust resources according to the real-time network state, resulting in low resource utilization and serious signal interference, which in turn affects positioning accuracy and system stability. In addition, when dealing with abnormal behavior detection, the prior art mostly relies on single-threshold judgment, lacking delay confirmation and multi-dimensional verification of abnormal behaviors, and is prone to false alarms or missed alarms. In terms of communication power consumption optimization, existing methods usually adopt a fixed communication method and fail to dynamically select the optimal communication method according to real-time communication power consumption data, resulting in high system power consumption and being difficult to meet the requirements of low-power application scenarios. These problems severely restrict the wide application of hybrid positioning technologies in fields such as security and smart homes. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a low-power alarm method based on hybrid positioning to solve the problems of inflexible resource coordination mechanism, low accuracy of abnormal behavior detection, and high communication power consumption in the prior art.

[0006] To solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a low-power alarm method based on hybrid positioning, which includes dynamically allocating time slots of 5G signals and transmission frequencies of UWB pulses through a heterogeneous network time-frequency resource coordination mechanism, and real-time collecting 5G signal strength data and UWB arrival time measurement values; based on the 5G signal strength data and UWB arrival time measurement values, using a dynamic weight fusion algorithm to calculate the three-dimensional coordinates of the terminal device in real time and store them in a circular buffer queue; extracting continuous three-dimensional coordinate data from the circular buffer queue, calculating the displacement integral and acceleration change rate, and combining a dual-threshold mechanism and a delay confirmation to detect abnormal behaviors of the terminal device and generate an encrypted trigger instruction packet; performing three-layer security verification on the encrypted trigger instruction packet to generate an alarm data packet, and selecting the communication method with the lowest power consumption according to the current communication power consumption data to send the alarm data packet.

[0008] As a preferred solution of the low-power alarm method based on hybrid positioning according to the present invention, wherein: the steps of dynamically allocating time slots of 5G signals and transmission frequencies of UWB pulses through a heterogeneous network time-frequency resource coordination mechanism, and real-time collecting 5G signal strength data and UWB arrival time measurement values are as follows:

[0009] Based on historical signal interference data and resource utilization statistics, define the coordination requirements of 5G and UWB networks;

[0010] Based on the coordination requirements of 5G and UWB networks, construct a conflict graph through a graph coloring algorithm, define the time slots of 5G signals and the transmission frequencies of UWB pulses as nodes in the conflict graph, define the signal interference relationship as edges, and assign a unique time slot and transmission frequency to each node to generate a time slot and transmission frequency allocation table, and synchronize the time of 5G signals and UWB pulses;

[0011] According to the time slot allocation table and time synchronization result, dynamically allocate time slots of 5G signals and transmission frequencies of UWB pulses, and real-time adjust the transmission power of 5G signals and the frequencies of UWB pulses;

[0012] According to the transmission power of the 5G signal adjusted in real time, capture the arrival angle and reference signal received power of the 5G signal through a multi-antenna array;

[0013] According to the frequency of the UWB pulse adjusted in real time, measure the arrival time difference of the UWB pulse through a high-precision clock.

[0014] As a preferred solution of the low-power alarm method based on hybrid positioning according to the present invention, wherein: the steps of calculating the three-dimensional coordinates of the terminal device in real time using a dynamic weight fusion algorithm based on the 5G signal strength data and UWB arrival time measurement values and storing them in a circular buffer queue are as follows:

[0015] Identify the reference signal received power and the signal-to-noise ratio of UWB pulses through PSD;

[0016] Based on the time difference of arrival of UWB pulses, calculate the high-precision distance between the terminal device and multiple anchors by minimizing the error, and generate the first set of preliminary coordinates. At the same time, based on the angle of arrival and the reference signal received power of the 5G signal, calculate the distance and direction between the terminal device and the base station, and generate the second set of preliminary coordinates;

[0017] According to the reference signal received power and the signal-to-noise ratio of UWB pulses, dynamically allocate weights, and perform weighted fusion on the two sets of preliminary coordinates to calculate the three-dimensional coordinates of the terminal device in real time. The expression is:

[0018]

[0019] where P(t) is the three-dimensional coordinate vector of the terminal device at time t, w 1 (t) is the dynamic weight of the UWB pulse, w 2 (t) is the dynamic weight of the G signal, A i is the coordinate of the i-th UWB anchor, Δt i is the time difference of arrival of the UWB pulse, c is the speed of light, B is the coordinate of the 5G base station, u is the direction vector obtained based on the 5G angle of arrival, d is the predicted distance between the terminal device and the base station obtained based on the 5G reference signal received power, P is the three-dimensional coordinate vector of the terminal device, N is the total number of UWB anchors, i is the anchor index variable, and t represents the current time;

[0020] Store the three-dimensional coordinate data and timestamp data of the terminal device into the circular buffer queue.

[0021] As a preferred solution of the low-power alarm method based on hybrid positioning according to the present invention, wherein: extract continuous three-dimensional coordinate data from the circular buffer queue, and calculate the displacement integral and the acceleration change rate. The specific steps are as follows:

[0022] Extract continuous three-dimensional coordinate data and the corresponding timestamps from the circular buffer queue through the read pointer;

[0023] According to the continuous three-dimensional coordinate data, identify the displacement between adjacent time points of the terminal device, and integrate the displacement to obtain the total displacement L of the terminal device;

[0024] According to the total displacement of the terminal device and the timestamp data, obtain the change rate of the acceleration of the terminal device. The expression is:

[0025]

[0026] Wherein, a(t) is the acceleration change rate of the terminal device at time point t, P(t - 1) is the three-dimensional coordinate vector of the terminal device at time t - 1, and P(t - 2) is the three-dimensional coordinate vector of the terminal device at time t - 2.

[0027] As a preferred solution of the low-power alarm method based on hybrid positioning according to the present invention, wherein: combining a dual-threshold mechanism and a delay confirmation to detect abnormal behaviors of the terminal device and generate an encrypted trigger instruction packet, the specific steps are as follows:

[0028] Based on the statistical analysis of the historical motion data of the terminal device, define a standard displacement threshold L1 and a standard acceleration change rate threshold a1;

[0029] When a(t) > a1 and L > L1, it is preliminarily determined that the terminal device has abnormal behaviors;

[0030] After preliminarily determining that the terminal device has abnormal behaviors, define a delay time window, and continuously monitor the displacement and acceleration change rate within the time window. If the abnormal behaviors of the terminal device persist within the delay time window, it is finally determined that the terminal device has abnormal behaviors;

[0031] Pack the timestamp, displacement data, and acceleration change rate of the abnormal behaviors through MessagePack to generate a trigger instruction packet, and use AES to encrypt the trigger instruction packet to generate an encrypted trigger instruction packet.

[0032] As a preferred solution of the low-power alarm method based on hybrid positioning according to the present invention, wherein: performing three-layer security verification on the encrypted trigger instruction packet to generate an alarm data packet, the specific steps are as follows,

[0033] Define a noise deviation benchmark Q1 based on historical environmental noise data, and define a historical timestamp benchmark T1 based on historical timestamp deviation data;

[0034] The first layer of verification is through a microphone sensor to collect in real time the environmental noise data at the moment when the abnormal behaviors of the terminal device are detected;

[0035] Use the sliding window mean algorithm to obtain the historical benchmark noise value, compare the environmental noise data with the historical benchmark noise value, and obtain the noise deviation value Q;

[0036] When Q ≤ Q1, enter the second layer of verification. Otherwise, discard the encrypted trigger instruction packet and record an error log;

[0037] The second layer of verification uses a hash algorithm to obtain the hash value of the encrypted trigger instruction packet;

[0038] Compare the hash value with the original hash value stored in the encrypted trigger instruction packet;

[0039] If the hash values are the same, enter the third - level verification; otherwise, discard the encrypted trigger instruction packet and record the error log.

[0040] In the third - level verification, through the data parsing algorithm, extract the timestamp T of the abnormal behavior from the encrypted trigger instruction packet.

[0041] Compare the timestamp T with the current time of the local clock of the terminal device to obtain the timestamp deviation.

[0042] When T ≤ T1, the third - level verification is passed; otherwise, discard the encrypted trigger instruction packet and record the error log.

[0043] Take the encrypted trigger instruction packet that passes the three - level verification as the alarm data packet.

[0044] When the verification fails, feedback the error log to the circular buffer queue and re - detect the abnormal behavior of the terminal device.

[0045] As a preferred scheme of the low - power alarm method based on hybrid positioning according to the present invention, wherein: the step of selecting the communication method with the lowest power consumption according to the current communication power consumption data and sending the alarm data packet is as follows;

[0046] Collect communication power consumption data through the network interface and hardware sensors of the terminal device; the communication power consumption data includes transmission power, the data volume in the alarm data packet, transmission distance, and the hardware efficiency of the terminal device.

[0047] Take the transmission power and data volume as positive contribution factors, and the transmission distance and hardware efficiency as negative penalty factors. Combine the hyperbolic tangent function to non - linearly enhance the transmission power and construct a communication power consumption evaluation function. The expression is:

[0048]

[0049] where S is the communication power consumption, D is the data volume in the alarm data packet, G is the transmission power, Z is the transmission distance, G max is the maximum transmission power, K is the hardware efficiency of the terminal device, r is the weight coefficient of the transmission power, y is the weight coefficient of the data volume in the alarm data packet, f is the weight coefficient of the transmission distance, and g is the weight coefficient of the hardware efficiency of the terminal device;

[0050] Through the communication power consumption evaluation function, calculate the communication power consumption of 5G and UWB networks respectively, select the network with the lowest communication power consumption as the communication method, and send the alarm data packet to the monitoring center.

[0051] In a second aspect, the present invention provides a low-power alarm system based on hybrid positioning, including a data acquisition module, a coordinate generation module, an anomaly detection module, and an alarm data packet sending module; Data acquisition module: used to dynamically allocate the time slots of 5G signals and the transmission frequencies of UWB pulses through the heterogeneous network time-frequency resource coordination mechanism, and collect 5G signal strength data and UWB arrival time measurement values in real time; Coordinate generation module: used to calculate the three-dimensional coordinates of the terminal device in real time based on the 5G signal strength data and UWB arrival time measurement values by using the dynamic weight fusion algorithm, and store them in a circular buffer queue; Anomaly detection module: used to extract continuous three-dimensional coordinate data from the circular buffer queue, calculate the displacement integral and acceleration change rate, and combine the dual-threshold mechanism and delay confirmation to detect the abnormal behavior of the terminal device, and generate an encrypted trigger instruction packet; Alarm data packet sending module: used to perform three-layer security verification on the encrypted trigger instruction packet, generate an alarm data packet, select the communication method with the lowest power consumption according to the current communication power consumption data, and send the alarm data packet.

[0052] In a third aspect, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and: when the computer program is executed by the processor, any step of the low-power alarm method based on hybrid positioning as described in the first aspect of the present invention is implemented.

[0053] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and: when the computer program is executed by the processor, any step of the low-power alarm method based on hybrid positioning as described in the first aspect of the present invention is implemented.

[0054] The beneficial effects of the present invention are as follows: Through the heterogeneous network time-frequency resource coordination mechanism, the time slots of 5G signals and the transmission frequencies of UWB pulses are dynamically allocated, significantly improving the resource utilization rate and the positioning data acquisition efficiency; at the same time, based on the 5G signal strength data and UWB arrival time measurement values, the three-dimensional coordinates of the terminal device are calculated in real time by using the dynamic weight fusion algorithm, integrating the advantages of 5G and UWB positioning data, realizing centimeter-level high-precision positioning, and further improving the anomaly behavior detection accuracy, security and low-power performance through the dual-threshold mechanism, delay confirmation detection, three-layer security verification and communication power consumption optimization. Description of the Drawings

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0056] Figure 1Flowchart of the low-power alarm method based on hybrid positioning in Embodiment 1.

[0057] Figure 2 Schematic diagram of the low-power alarm system based on hybrid positioning in Embodiment 1. Detailed implementation manners

[0058] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific implementation manners of the present invention will be given in conjunction with the accompanying drawings of the specification.

[0059] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art can make similar generalizations without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0060] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation manner of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that excludes other embodiments.

[0061] Embodiment 1, referring to Figure 1 and Figure 2 , is the first embodiment of the present invention. This embodiment provides a low-power alarm method based on hybrid positioning, including the following steps:

[0062] S1. Through the heterogeneous network time-frequency resource coordination mechanism, dynamically allocate the time slots of 5G signals and the transmission frequencies of UWB pulses, and collect 5G signal strength data and UWB time-of-arrival measurement values in real time.

[0063] Based on historical signal interference data and resource utilization statistics, define the coordination requirements of the 5G and UWB networks.

[0064] Based on the coordination requirements of the 5G and UWB networks, construct a conflict graph through a graph coloring algorithm. Define the time slots of 5G signals and the transmission frequencies of UWB pulses as nodes in the conflict graph, define the signal interference relationship as edges, and assign a unique time slot and transmission frequency to each node to generate a time slot and transmission frequency allocation table, and synchronize the time of 5G signals and UWB pulses.

[0065] It should be noted that based on historical signal interference data and resource utilization statistics, first analyze the interference situation between 5G and UWB networks and their respective resource utilization efficiencies in different past time periods, so as to determine the specific requirements when the two networks work in coordination. By evaluating these data, identify high-interference time periods and inefficient resource utilization patterns, and then define a set of cooperation rules for the time slots of 5G signals and the transmission frequencies of UWB pulses. This process involves constructing a conflict graph, regarding the time slots of 5G signals and the transmission frequencies of UWB pulses as nodes, and setting edges according to the signal interference relationship, ensuring that each node is assigned a unique time slot and transmission frequency, thereby generating a time slot and transmission frequency allocation table to achieve synchronous coordination in time between the two, with the aim of optimizing resource utilization efficiency and reducing signal interference.

[0066] According to the time slot allocation table and time synchronization results, dynamically allocate the time slots of 5G signals and the transmission frequencies of UWB pulses, and adjust the transmission power of 5G signals and the frequencies of UWB pulses in real time.

[0067] For example, at a specific moment, if it is detected that the interference of 5G signals in the current area increases, according to the time slot allocation table, appropriately reduce the transmission power of 5G signals in this area, and adjust the transmission frequency of UWB pulses according to the relationship defined in the conflict graph to ensure that there is no interference between the two. Specifically, if a high interference is expected for 5G signals in a certain time slot, reduce the transmission power of 5G signals in this time period to a predetermined level, and at the same time improve the transmission frequency accuracy of UWB pulses. In this way, the signal transmission quality is optimized. This dynamic adjustment mechanism ensures that even under changing network conditions, high positioning accuracy and communication reliability can be maintained while minimizing energy consumption. Further ensure the accuracy of data collection by capturing the angle of arrival of the adjusted 5G signals and the reference signal received power through a multi-antenna array, and using a high-precision clock to measure the time difference of arrival of UWB pulses.

[0068] According to the transmission power of the 5G signals adjusted in real time, capture the angle of arrival of the 5G signals and the reference signal received power through a multi-antenna array.

[0069] According to the frequency of the UWB pulses adjusted in real time, measure the time difference of arrival of the UWB pulses through a high-precision clock.

[0070] S2. Based on the 5G signal strength data and UWB arrival time measurement values, use the dynamic weight fusion algorithm to calculate the three-dimensional coordinates of the terminal device in real time and store them in a circular buffer queue.

[0071] Identify the reference signal received power and the signal-to-noise ratio of UWB pulses through PSD.

[0072] It should be noted that first, a frequency-domain analysis is performed on the 5G signals received from the multi-antenna array to calculate the power levels at various frequency components, thereby determining the reference signal received power. Next, within the same time period, a similar frequency-domain analysis process is executed for the UWB pulse signals to evaluate their distribution across the entire spectrum and extract the signal-to-noise ratio information therefrom. Specifically, for each captured UWB pulse, based on its performance in the frequency domain, the signal-to-noise ratio is quantified by calculating the ratio of the signal power to the noise power, ensuring that the impact of environmental noise is fully considered during this process. Through the precise measurement of these two key parameters, reliable data support is provided for dynamically allocating weights and fusing the 5G signal strength data with the UWB arrival time measurements in the subsequent steps, thereby enabling the accurate calculation of the three-dimensional coordinates of the terminal device.

[0073] Based on the time difference of arrival of UWB pulses, high-precision distances between the terminal device and multiple anchors are calculated by minimizing the error to generate a first set of preliminary coordinates. Meanwhile, based on the angle of arrival and reference signal received power of the 5G signal, the distance and direction between the terminal device and the base station are calculated to generate a second set of preliminary coordinates.

[0074] It should be noted that first, the timestamps of the same UWB pulse received by each UWB anchor are collected, and the time difference of arrival relative to each anchor is calculated. Using these time differences of arrival and the known anchor coordinates, the actual distances from the terminal device to each anchor are determined through a least-error algorithm, thereby generating a first set of preliminary coordinates. At the same time, based on the angle of arrival and reference signal received power of the 5G signal, the data received from the multi-antenna array is processed to calculate the distance and direction between the terminal device and the base station. The specific steps include analyzing the angle-of-arrival information of the 5G signal and evaluating the reference signal received power intensity, and then estimating the exact positional relationship of the terminal device relative to the base station to form a second set of preliminary coordinates. These two sets of preliminary coordinates respectively rely on the precise time of UWB pulses and the spatial characteristics of 5G signals, providing a basis for dynamically allocating weights and fusing the data of both in the subsequent steps to more accurately calculate the three-dimensional coordinates of the terminal device in real time.

[0075] According to the reference signal received power and the signal-to-noise ratio of the UWB pulse, weights are dynamically allocated, and the two sets of preliminary coordinates are weighted and fused to calculate the three-dimensional coordinates of the terminal device in real time. The expression is:

[0076]

[0077] where P(t) is the three-dimensional coordinate vector of the terminal device at time t, w 1 (t) is the dynamic weight of the UWB pulse, w 2 (t) is the dynamic weight of the G signal, A i is the coordinate of the i-th UWB anchor, Δti is the time difference of arrival of UWB pulses, c is the speed of light, B is the coordinate of the 5G base station, u is the direction vector obtained based on the angle of arrival of 5G, d is the predicted distance between the terminal device and the base station obtained based on the received power of the 5G reference signal, P is the three-dimensional coordinate vector of the terminal device, N is the total number of UWB anchors, i is the index variable of the anchor, and t represents the current time.

[0078] It should be noted that according to the received power of the reference signal and the signal-to-noise ratio of the UWB pulse, the dynamic weights of the UWB pulse and the 5G signal are first determined. Based on these weights, the first set of preliminary coordinates obtained from the UWB anchors and the second set of preliminary coordinates obtained from the 5G base stations are weighted and fused. Using historical data and real-time measurement values, the distance between each UWB anchor and the terminal device is calculated, and combined with the direction vector and predicted distance of the 5G base station, the position information of the terminal device is comprehensively evaluated. By fusing the two sets of preliminary coordinates according to their respective weights, the precise three-dimensional coordinates of the terminal device at the current time point are updated and calculated in real time.

[0079] The three-dimensional coordinate data and timestamp data of the terminal device are stored in a circular buffer queue.

[0080] It should be noted that a circular buffer queue is a data structure that organizes the data storage space in a circular manner in memory, enabling data writing and reading operations to be carried out according to the first-in, first-out principle, while effectively utilizing limited storage resources. When data is written into the circular buffer queue, it starts filling from a fixed starting point until the end of the queue is reached, and then starts overwriting the old data from the head of the queue, thus achieving continuous data processing capabilities without having to frequently allocate and release memory.

[0081] S3. Extract continuous three-dimensional coordinate data from the circular buffer queue, calculate the displacement integral and the acceleration change rate, and combine the dual-threshold mechanism and time-delay confirmation to detect the abnormal behavior of the terminal device and generate an encrypted trigger instruction packet.

[0082] Extract continuous three-dimensional coordinate data and the corresponding timestamps from the circular buffer queue through the read pointer.

[0083] According to the continuous three-dimensional coordinate data, identify the displacement of the terminal device between adjacent time points, and integrate the displacement to obtain the total displacement L of the terminal device.

[0084] It should be noted that according to the continuous three-dimensional coordinate data, the coordinate information of the terminal device at adjacent time points is first extracted from the circular buffer queue. For example, assume that within an observation period, the coordinates of the terminal device are obtained at three consecutive time points: the coordinate at the first time point is A, the coordinate at the second time point is B, and the coordinate at the third time point is C. By comparing these coordinates, the displacement of the terminal device within each time period can be identified. Specifically, within the first time period (from time point A to time point B), calculate the distance that the terminal device moves from position A to position B; then, within the second time period (from time point B to time point C), calculate the distance that the terminal device moves from position B to position C. For each time period, identify and record the position change of the terminal device to determine the displacement within that period. Then, accumulate the displacements within all time periods in sequence to obtain the total displacement L of the terminal device during the entire observation period.

[0085] Based on the total displacement of the terminal device and the timestamp data, obtain the change rate of the acceleration of the terminal device. The expression is:

[0086]

[0087] where a(t) is the change rate of the acceleration of the terminal device at time point t, P(t - 1) is the three-dimensional coordinate vector of the terminal device at time t - 1, and P(t - 2) is the three-dimensional coordinate vector of the terminal device at time t - 2.

[0088] Based on the statistical analysis of the historical motion data of the terminal device, define the standard displacement threshold L1 and the standard acceleration change rate threshold a1.

[0089] It should be noted that based on the statistical analysis of the historical motion data of the terminal device, first collect and organize a dataset of the displacements and acceleration change rates of the terminal device over a period of time. By analyzing these historical data, determine the displacement pattern and acceleration change law under normal operating conditions, and thus define the standard displacement threshold L1 and the standard acceleration change rate threshold a1. For example, in a typical daily usage scenario, if the terminal device usually moves no more than 50 meters per day and the acceleration change rate remains at a certain low level, then L1 can be set to 50 meters and a1 to the specific value of that low level according to these normal data. Once the real-time monitored displacement exceeds L1 or the acceleration change rate exceeds a1, it can be preliminarily determined that the terminal device has abnormal behavior.

[0090] When a(t) > a1 and L > L1, it is preliminarily determined that the terminal device has abnormal behavior.

[0091] After initially determining that the terminal device has abnormal behavior, a delay time window is defined, and the change rates of displacement and acceleration are continuously monitored within the time window. If the abnormal behavior of the terminal device persists within the delay time window, it is finally determined that the terminal device has abnormal behavior.

[0092] It should be noted that after initially determining that the terminal device has abnormal behavior, a delay time window is defined, for example, set to 30 seconds. During this period, the change rates of displacement and acceleration of the terminal device are continuously monitored. If within this delay time window, the displacement of the terminal device continuously exceeds the standard displacement threshold L1, or the change rate of acceleration continuously exceeds the standard acceleration change rate threshold a1, then it is finally determined that the terminal device indeed has abnormal behavior. This process allows for the confirmation of initially detected abnormal situations and avoids false alarms caused by short-term or instantaneous interferences. By setting a specific time window and conducting continuous monitoring, it is ensured that further actions, such as generating an encrypted trigger instruction packet, are only triggered when the abnormal behavior persists throughout the time period.

[0093] The timestamp, displacement data, and acceleration change rate of the abnormal behavior are packed through MessagePack to generate a trigger instruction packet, and the trigger instruction packet is encrypted using AES to generate an encrypted trigger instruction packet.

[0094] S4. Conduct three-layer security verification on the encrypted trigger instruction packet to generate an alarm data packet, and select the communication method with the lowest power consumption based on the current communication power consumption data to send the alarm data packet.

[0095] Define a noise deviation benchmark Q1 based on historical environmental noise data and a historical timestamp benchmark T1 based on historical timestamp deviation data.

[0096] It should be noted that relevant noise measurement values are extracted from a long-term accumulated database, and the average and standard deviation of these values are calculated to serve as the criteria for determining whether the subsequently real-time collected environmental noise is abnormal. At the same time, based on historical timestamp deviation data, the time synchronization errors between different devices in the past are sorted out and analyzed to determine a typical time synchronization error range, and then the historical timestamp benchmark T1 is defined. This step involves selecting data at multiple time points from log files or databases, evaluating the timestamp differences between these time points, calculating the average deviation and the maximum acceptable deviation value, and using them as the criteria for measuring the accuracy of newly generated timestamps. These two benchmarks are respectively used in the first-layer and third-layer security verification steps to compare the real-time collected environmental noise data and timestamp data to ensure that they are within the expected range.

[0097] In the first-layer verification, environmental noise data at the moment when the abnormal behavior of the terminal device is detected in real time is collected through a microphone sensor.

[0098] Use the sliding window mean algorithm to obtain the historical reference noise value, compare the environmental noise data with the historical reference noise value, and obtain the noise deviation value Q.

[0099] The environmental noise data includes detailed information such as the noise intensity value (in decibels dB), frequency distribution, and noise peak at each time point recorded within a specific time period. These data reflect the changes in the background noise in the environment.

[0100] When Q ≤ Q1, it enters the second - layer verification. Otherwise, discard the encryption trigger instruction packet and record the error log.

[0101] The second - layer verification uses the hash algorithm to obtain the hash value of the encryption trigger instruction packet.

[0102] Compare the hash value with the original hash value stored in the encryption trigger instruction packet.

[0103] When the hash values are the same, it enters the third - layer verification. Otherwise, discard the encryption trigger instruction packet and record the error log.

[0104] It should be noted that, first, all the data in the encryption trigger instruction packet is extracted and passed as input to the selected hash algorithm. Through a series of calculation steps of the hash algorithm, these data are converted into a unique hash value of a fixed length. This hash value is then used to compare with the original hash value pre - stored in the encryption trigger instruction packet. If the two are the same, it indicates that the encryption trigger instruction packet has not been tampered with, thus passing the second - layer verification; otherwise, if the hash values do not match, it indicates that there may be data tampering, resulting in the encryption trigger instruction packet being discarded and the error log being recorded.

[0105] The third - layer verification extracts the timestamp T of the abnormal behavior from the encryption trigger instruction packet through the data parsing algorithm.

[0106] Compare the timestamp T with the current time of the local clock of the terminal device to obtain the timestamp deviation;

[0107] When T ≤ T1, it passes the third - layer verification. Otherwise, discard the encryption trigger instruction packet and record the error log.

[0108] Use the encryption trigger instruction packet that has passed the three - layer verification as the alarm data packet.

[0109] It should be noted that first, the AES decryption algorithm is applied to decrypt the encrypted trigger instruction packet, restoring it from the ciphertext state to the plaintext form, so as to obtain the content of the original trigger instruction packet. In the decrypted data, according to the predefined data structure and format, the information segment containing the timestamp T of the abnormal behavior is located and extracted. Specifically, using the identifier or offset of the data field, the data part of the timestamp T is accurately separated from the decrypted trigger instruction packet. This process ensures that the required timestamp information can be correctly and efficiently obtained for subsequent comparison with the current time of the local clock of the terminal device to complete the third-layer verification.

[0110] When the verification fails, the error log is fed back to the circular buffer queue, and the abnormal behavior of the terminal device is detected again.

[0111] It should be noted that when the verification fails, the error log is fed back to the circular buffer queue, and steps S2 and S3 are re-executed to generate a new encrypted trigger instruction packet.

[0112] Collect communication power consumption data through the network interface and hardware sensors of the terminal device; the communication power consumption data includes transmission power, the amount of data in the alarm data packet, transmission distance, and the hardware efficiency of the terminal device.

[0113] Taking the transmission power and the amount of data as positive contribution factors, and the transmission distance and hardware efficiency as negative penalty factors, a communication power consumption evaluation function is constructed by combining the hyperbolic tangent function to nonlinearly enhance the transmission power. The expression is:

[0114]

[0115] where S is the communication power consumption, D is the amount of data in the alarm data packet, G is the transmission power, Z is the transmission distance, G max is the maximum transmission power, K is the hardware efficiency of the terminal device, r is the weight coefficient of the transmission power, y is the weight coefficient of the amount of data in the alarm data packet, f is the weight coefficient of the transmission distance, and g is the weight coefficient of the hardware efficiency of the terminal device.

[0116] It should be noted that the transmission power and data volume are first identified as positive contribution factors, which means that an increase in these factors will directly improve the effectiveness and speed of communication. On the contrary, the transmission distance and hardware efficiency are regarded as negative penalty factors because an increase in them will lead to an increase in communication costs or signal attenuation. To more accurately simulate the impact of transmission power, a hyperbolic tangent function is used to perform non-linear enhancement processing on it, so that the power consumption changes at different transmission power levels can more accurately reflect the actual situation. By combining these factors and according to the preset weight relationship, a comprehensive evaluation value is calculated to measure the power consumption of different communication methods. This process ensures that when selecting the optimal communication path, the impacts of various factors can be comprehensively considered, so as to achieve data transmission with the lowest power consumption. The entire process strictly follows the collaborative requirements of 5G and UWB networks defined based on historical signal interference data and resource utilization statistics, ensuring the accuracy and reliability of the evaluation results. Through this method, the sending strategy of alarm data packets can be effectively optimized, and the overall communication energy consumption can be reduced.

[0117] Through the communication power consumption evaluation function, the communication power consumptions of 5G and UWB networks are calculated respectively, and the network with the lowest communication power consumption is selected as the communication method to send the alarm data packet to the monitoring center.

[0118] It should be noted that the alarm data packet contains the abnormal behavior information of the terminal device, the time stamp, and the relevant data for encryption verification, ensuring the integrity and security of the information.

[0119] This embodiment also provides a low-power alarm system based on hybrid positioning, including: a data acquisition module, a coordinate generation module, an anomaly detection module, and an alarm data packet sending module; the data acquisition module: used to dynamically allocate the time slots of 5G signals and the transmission frequencies of UWB pulses through the heterogeneous network time-frequency resource coordination mechanism, and collect 5G signal strength data and UWB arrival time measurement values in real time; the coordinate generation module: used to calculate the three-dimensional coordinates of the terminal device in real time based on the 5G signal strength data and UWB arrival time measurement values by using the dynamic weight fusion algorithm, and store them in the circular buffer queue; the anomaly detection module: used to extract continuous three-dimensional coordinate data from the circular buffer queue, calculate the displacement integral and the acceleration change rate, and combine the double-threshold mechanism and the delay confirmation to detect the abnormal behavior of the terminal device and generate an encrypted trigger instruction packet; the alarm data packet sending module: used to perform three-layer security verification on the encrypted trigger instruction packet, generate an alarm data packet, select the communication method with the lowest power consumption according to the current communication power consumption data, and send the alarm data packet.

[0120] This embodiment also provides a computer device applicable to the situation of the low-power alarm method based on hybrid positioning, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the low-power alarm method based on hybrid positioning as proposed in the above embodiment.

[0121] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the outer shell of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0122] This embodiment also provides a storage medium on which a computer program is stored, and when the program is executed by a processor, it implements the low-power alarm method based on hybrid positioning as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM for short), Electrically Erasable Programmable Read-Only Memory (EEPROM for short), Erasable Programmable Read Only Memory (EPROM for short), Programmable Read-Only Memory (PROM for short), Read-Only Memory (ROM for short), magnetic memory, flash memory, a magnetic disk, or an optical disc.

[0123] In summary, the present invention achieves the following: through an heterogeneous network time-frequency resource coordination mechanism, it dynamically allocates the time slots of 5G signals and the transmission frequencies of UWB pulses, significantly improving resource utilization and positioning data acquisition efficiency; meanwhile, based on 5G signal strength data and UWB time-of-arrival measurements, it uses a dynamic weight fusion algorithm to calculate the three-dimensional coordinates of the terminal device in real time, integrating the advantages of 5G and UWB positioning data, achieving centimeter-level high-precision positioning, and further enhancing the abnormal behavior detection accuracy, security, and low-power performance through a dual-threshold mechanism, delayed confirmation detection, three-layer security verification, and communication power consumption optimization.

[0124] Embodiment 2, referring to Table 1, is the second embodiment of the present invention. To further verify the technical solution of the present invention, experimental simulation data of a low-power alarm method based on hybrid positioning is given.

[0125] To verify the effectiveness of a low-power alarm method based on hybrid positioning, a three-story office building was selected as the test environment for this experiment. Multiple 5G base stations and UWB anchors were set up in this environment to ensure coverage and positioning accuracy. The experimental equipment included several terminal devices equipped with multi-antenna arrays to simulate the movement of users on different floors. Each terminal device was pre-installed with the software algorithm described in the present invention, which could dynamically adjust the 5G signal time slots and UWB pulse frequencies, and collect signal strength data and time-of-arrival measurements in real time.

[0126] First, the coordination requirements of the 5G and UWB networks are defined through historical signal interference data and resource utilization statistics, which lays the foundation for the subsequent application of the graph coloring algorithm. Next, a conflict graph is constructed using the graph coloring algorithm, with the time slots of 5G signals and the transmission frequencies of UWB pulses defined as nodes, and the signal interference relationship defined as edges. After optimized allocation, each node obtains a unique time slot and transmission frequency, thereby generating a detailed time slot and transmission frequency allocation table. These steps ensure the time synchronization of 5G signals and UWB pulses, improving positioning accuracy while reducing communication power consumption.

[0127] Subsequently, based on the above allocation results, the transmission power of the 5G signal and the frequency of the UWB pulse are adjusted in real time. The arrival angle and reference signal received power of the 5G signal are captured through a multi-antenna array, and at the same time, the time difference of arrival of the UWB pulse is measured using a high-precision clock. These data are input into the dynamic weight fusion algorithm, which identifies the reference signal received power and the signal-to-noise ratio of the UWB pulse according to the PSD, and then calculates the three-dimensional coordinates of the terminal device and stores them in the circular buffer queue. Then, continuous three-dimensional coordinate data are extracted from the circular buffer queue, the displacement integral and the acceleration change rate are calculated, and the abnormal behavior of the terminal device is detected by combining the dual-threshold mechanism and delay confirmation, and an encrypted trigger instruction packet is generated. Finally, three-layer security verification is performed on the encrypted trigger instruction packet, and the communication method with the lowest power consumption is selected according to the current communication power consumption data to send the alarm data packet to the monitoring center.

[0128] The prior art adopts fixed signal transmission frequency and power settings, and improves the positioning accuracy by enhancing the 5G signal strength or increasing the UWB pulse frequency, but this method results in high energy consumption. In addition, the abnormal behavior detection only relies on simple threshold judgment and lacks comprehensive analysis of multi-dimensional parameters such as displacement integral and acceleration change rate.

[0129] Specifically, it is shown in Table 1 below:

[0130] Table 1 Performance comparison table of low-power alarm method based on hybrid positioning

[0131]

[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A low-power alarm method based on hybrid positioning, characterized in that: include, Through the coordination mechanism of heterogeneous network time and frequency resources, the time slots of 5G signals and the transmission frequencies of UWB pulses are dynamically allocated, and 5G signal strength data and UWB arrival time measurements are collected in real time; Based on 5G signal strength data and UWB arrival time measurement values, the dynamic weight fusion algorithm is used to calculate the three-dimensional coordinates of the terminal device in real time and store them in the ring cache queue; Extract continuous three-dimensional coordinate data from the ring buffer queue, calculate the displacement integral and acceleration change rate, and combine the dual threshold mechanism and delay confirmation to detect abnormal behavior of the terminal device, and generate an encrypted trigger instruction packet; Perform three-layer security verification on the encrypted trigger instruction packet, generate an alarm data packet, select the communication method with the lowest power consumption according to the current communication power consumption data, and send the alarm data packet.

2. The low-power alarm method based on hybrid positioning according to claim 1, characterized in that: The time slots of 5G signals and the transmission frequencies of UWB pulses are dynamically allocated through the heterogeneous network time-frequency resource coordination mechanism, and 5G signal strength data and UWB arrival time measurement values ​​are collected in real time. The specific steps are as follows: Define the coordination requirements between 5G and UWB networks based on historical signal interference data and resource utilization statistics; Based on the collaborative needs of 5G and UWB networks, a conflict graph is constructed through a graph coloring algorithm. The time slots of 5G signals and the transmission frequencies of UWB pulses are defined as nodes in the conflict graph, and the signal interference relationships are defined as edges. A unique time slot and transmission frequency are assigned to each node, and a time slot and transmission frequency allocation table is generated. In addition, the time of 5G signals and UWB pulses is synchronized; According to the time slot allocation table and time synchronization results, dynamically allocate the time slot of the 5G signal and the transmission frequency of the UWB pulse, and adjust the transmission power of the 5G signal and the frequency of the UWB pulse in real time; According to the real-time adjusted 5G signal transmission power, the arrival angle and reference signal reception power of the 5G signal are captured through a multi-antenna array; According to the frequency of the UWB pulse adjusted in real time, the arrival time difference of the UWB pulse is measured by a high-precision clock.

3. The low-power alarm method based on hybrid positioning according to claim 2, characterized in that: Based on the 5G signal strength data and the UWB arrival time measurement value, the three-dimensional coordinates of the terminal device are calculated in real time using a dynamic weight fusion algorithm and stored in a ring cache queue. The specific steps are as follows: Identify the reference signal received power and the signal-to-noise ratio of the UWB pulse through PSD; Based on the arrival time difference of UWB pulses, the high-precision distance between the terminal device and multiple anchor points is calculated by minimizing the error to generate the first set of preliminary coordinates. At the same time, based on the arrival angle of the 5G signal and the reference signal received power, the distance and direction between the terminal device and the base station are calculated to generate the second set of preliminary coordinates. According to the reference signal receiving power and the signal-to-noise ratio of the UWB pulse, the weights are dynamically allocated, and the two sets of preliminary coordinates are weighted fused to calculate the three-dimensional coordinates of the terminal device in real time. The expression is: Where P(t) is the three-dimensional coordinate vector of the terminal device at time t, w1(t) is the dynamic weight of the UWB pulse, w2(t) is the dynamic weight of the G signal, and A i is the coordinate of the i-th UWB anchor point, Δt i is the arrival time difference of the UWB pulse, c is the speed of light, B is the coordinate of the 5G base station, u is the direction vector obtained based on the 5G arrival angle, d is the predicted distance between the terminal device and the base station based on the 5G reference signal received power, P is the three-dimensional coordinate vector of the terminal device, N is the total number of UWB anchor points, i is the index variable of the anchor point, and t represents the current time; The three-dimensional coordinate data and timestamp data of the terminal device are stored in the circular buffer queue.

4. The low power consumption alarm method based on hybrid positioning as claimed in claim 3, characterized in that: The steps of extracting continuous three-dimensional coordinate data from the circular buffer queue and calculating the displacement integral and the acceleration change rate are as follows: Extract continuous three-dimensional coordinate data and corresponding timestamps from the circular buffer queue by reading the pointer; According to the continuous three-dimensional coordinate data, the displacement of the terminal device between adjacent time points is identified, and the displacement is integrated to obtain the total displacement L of the terminal device; According to the total displacement and timestamp data of the terminal device, the rate of change of the acceleration of the terminal device is obtained, and the expression is: Among them, a(t) is the acceleration change rate of the terminal device at time point t, P(t-1) is the three-dimensional coordinate vector of the terminal device at time t-1, and P(t-2) is the three-dimensional coordinate vector of the terminal device at time t-2.

5. The low power consumption alarm method based on hybrid positioning as claimed in claim 4, characterized in that: The combination of the dual threshold mechanism and delayed confirmation detects abnormal behavior of the terminal device and generates an encrypted trigger instruction packet. The specific steps are as follows: Based on the statistical analysis of the historical motion data of the terminal device, a standard displacement threshold L1 and a standard acceleration change rate threshold a1 are defined; When a(t)>a1 and L>L1, it is preliminarily determined that the terminal device has abnormal behavior; After initially determining that the terminal device has abnormal behavior, define a delay time window, and continuously monitor the displacement and acceleration change rate within the time window. If the abnormal behavior of the terminal device persists within the delay time window, it is finally determined that the terminal device has abnormal behavior; The timestamp, displacement data, and acceleration change rate of the abnormal behavior are packaged through MessagePack to generate a trigger instruction package, and the trigger instruction package is encrypted using AES to generate an encrypted trigger instruction package.

6. The low power consumption alarm method based on hybrid positioning as claimed in claim 5, characterized in that: The three-layer security verification is performed on the encrypted trigger instruction packet to generate an alarm data packet. The specific steps are as follows: A noise deviation benchmark Q1 is defined based on historical environmental noise data, and a historical timestamp benchmark T1 is defined based on historical timestamp deviation data; The first level of verification uses microphone sensors to collect real-time environmental noise data when abnormal behavior of the terminal device is detected; Use the sliding window average algorithm to obtain the historical benchmark noise value, compare the environmental noise data with the historical benchmark noise value, and obtain the noise deviation value Q; When Q≤Q1, the second level of verification is entered. In any case, the encrypted trigger instruction packet is discarded and the error log is recorded; The second layer of verification uses a hash algorithm to obtain the hash value of the encrypted trigger instruction packet; Comparing the hash value with the original hash value stored in the encrypted trigger instruction packet; If the hash values ​​are consistent, the third verification is started. Otherwise, the encrypted trigger instruction packet is discarded and the error log is recorded. The third layer of verification uses a data parsing algorithm to extract the timestamp T of the abnormal behavior from the encrypted trigger instruction packet; Compare the timestamp T with the current time of the local clock of the terminal device to obtain the timestamp deviation; When T≤T1, the third layer verification is passed, otherwise the encrypted trigger instruction packet is discarded and the error log is recorded; The encrypted trigger instruction packet that has passed the three-layer verification is used as the alarm data packet; When the verification fails, the error log is fed back to the ring buffer queue to re-detect abnormal behavior of the terminal device.

7. The low power consumption alarm method based on hybrid positioning according to claim 6, characterized in that: The specific steps of selecting the lowest power consumption communication mode according to the current communication power consumption data and sending the alarm data packet are as follows: Collect communication power consumption data through the network interface and hardware sensors of the terminal device; the communication power consumption data includes transmission power, data volume in the alarm data packet, transmission distance and hardware efficiency of the terminal device; Taking transmission power and data volume as positive contribution factors, transmission distance and hardware efficiency as negative penalty factors, and combining the hyperbolic tangent function to nonlinearly enhance the transmission power, a communication power consumption evaluation function is constructed, the expression is: Among them, S is the communication power consumption, D is the amount of data in the alarm data packet, G is the transmission power, Z is the transmission distance, G max is the maximum transmission power, K is the hardware efficiency of the terminal device, r is the weight coefficient of the transmission power, y is the weight coefficient of the data volume in the warning data packet, f is the weight coefficient of the transmission distance, and g is the weight coefficient of the hardware efficiency of the terminal device; Through the communication power consumption evaluation function, the communication power consumption of 5G and UWB networks is calculated respectively, and the network with the lowest communication power consumption is selected as the communication mode to send the alarm data packet to the monitoring center.

8. A low-power alarm system based on hybrid positioning, based on the low-power alarm method based on hybrid positioning according to any one of claims 1 to 7, characterized in that: Including, data acquisition module, coordinate generation module, anomaly detection module, alarm data packet sending module; Data acquisition module: used to dynamically allocate the time slots of 5G signals and the transmission frequency of UWB pulses through the coordination mechanism of heterogeneous network time and frequency resources, and collect 5G signal strength data and UWB arrival time measurement values ​​in real time; Coordinate generation module: used to calculate the three-dimensional coordinates of the terminal device in real time based on the 5G signal strength data and the UWB arrival time measurement value using a dynamic weight fusion algorithm and store them in a ring cache queue; Anomaly detection module: used to extract continuous three-dimensional coordinate data from the ring buffer queue, calculate the displacement integral and acceleration change rate, and combine the dual threshold mechanism and delay confirmation to detect abnormal behavior of the terminal device, and generate an encrypted trigger instruction packet; Alarm data packet sending module: used to perform three-layer security verification on the encrypted trigger instruction packet, generate an alarm data packet, select the communication method with the lowest power consumption according to the current communication power consumption data, and send the alarm data packet.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the low-power consumption alarm method based on hybrid positioning are implemented in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the low-power alarm method based on hybrid positioning according to any one of claims 1 to 7 are implemented.

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