A method and device for early warning of abnormal positioning of liquefied gas cylinders

Abstract

The present invention provides a method and device for warning of abnormal positioning of liquefied gas cylinders, which can solve the problem that traditional static thresholds cannot adapt to complex scenarios (such as traffic congestion and changes in population density), and improve the warning accuracy by dynamically adjusting the safety distance and time thresholds; perform multi-dimensional anomaly identification, for example, by integrating positioning data, environmental perception data and distribution path verification, it can achieve all-round monitoring from location offset to environmental risks; perform graded warning and intelligent response, for example, it can adaptively adjust the alarm intensity according to the day and night time and pedestrian density, and automatically push standardized emergency procedures to relevant departments to improve emergency efficiency; at the same time, it has an anti-disturbance design, reduces the intensity of sound and light alarms in high-density areas, avoids accidentally triggering public safety incidents, and plans evacuation routes through MAC address distribution to enhance safety.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things and intelligent security technology, and in particular to a method and device for early warning of abnormal positioning of a liquefied gas cylinder. Background Art

[0002] Liquefied petroleum gas cylinders are widely used in both civilian and commercial sectors, providing energy for daily life and business operations. However, with increasing usage and increasing complexity, safety management issues have become prominent. Currently, cylinder management primarily focuses on regular physical inspections, such as those for external integrity and valve sealing. However, there are shortcomings in real-time positioning and anomaly warning. Traditional methods struggle to accurately and continuously track cylinder locations, making it impossible to promptly detect whether they have strayed from their normal areas. Unauthorized transfers of civilian cylinders and deviations from commercial delivery routes are difficult to detect in a timely manner. Furthermore, there is a lack of effective, comprehensive monitoring and early warning mechanisms for illegal transfers, violations, and abnormal environmental hazards. These issues pose a serious threat to life and property, necessitating the urgent need for accurate cylinder positioning and anomaly warning methods and systems to enhance urban smart gas management and public safety systems. Summary of the Invention

[0003] The present invention aims to provide a method and device for early warning of abnormal positioning of liquefied gas cylinders that overcome the above-mentioned problems or at least partially solve the above-mentioned problems.

[0004] To achieve the above object, the technical solution of the present invention is specifically implemented as follows:

[0005] One aspect of the present invention provides a method for early warning of abnormal positioning of a liquefied gas cylinder, comprising:

[0006] Obtaining installation configuration parameters of the target liquefied gas cylinder, wherein the installation configuration parameters at least include a deployment area type, a delivery and extraction mode, and an authorized activity area range;

[0007] When it is identified that the deployment area type is a civilian residential area and the delivery and collection mode is autonomous collection, continuously collecting the real-time spatial coordinates of the cylinder;

[0008] When it is identified that the deployment area type is a commercial residential area and the delivery and extraction mode is delivery by a delivery person, the delivery time of the cylinder is continuously collected;

[0009] Constructing a geo-fence boundary model, dynamically comparing the real-time spatial coordinates with the scope of the authorized activity area, and generating an early warning instruction when it is detected that the spatial offset exceeds a preset safety distance threshold;

[0010] In response to the early warning instruction, the surrounding environment perception data of the current location of the target liquefied gas cylinder is collected, and multi-source data fusion analysis is performed through abnormal behavior recognition to generate a graded early warning signal.

[0011] Optionally, constructing a geo-fence boundary model includes:

[0012] Establishing a polygonal geo-fence boundary based on the geographic coordinate dataset of the authorized activity area;

[0013] Set dynamic traffic management coefficient;

[0014] The actual distance between the real-time spatial coordinates and the two points closest to the fence boundary is calculated, and the preset safety distance threshold is determined in combination with the traffic management coefficient.

[0015] Optionally, setting the dynamic traffic management coefficient includes:

[0016] The traffic management coefficient is dynamically adjusted based on regional population density and road grade parameters.

[0017] Optionally, determining the preset safety distance threshold in combination with the traffic management coefficient includes:

[0018] Obtaining preset reference values, the preset reference values ​​including: minimum safety distance and standard safety distance;

[0019] Loading dynamic parameters, the dynamic parameters including: real-time population density and road grade;

[0020] Construct coefficient calculation model;

[0021] The safety distance threshold is dynamically adjusted.

[0022] Optionally, the continuously collecting the delivery time of the cylinder includes:

[0023] Get the planned time window [T1, T2] in the delivery task electronic waybill;

[0024] Calculate the time deviation Δt between the current time and T1 in real time;

[0025] The system initially sets the ΔTmax value and dynamically modifies the time threshold ΔTmax based on real-time traffic data;

[0026] When Δt>ΔTmax, a delivery abnormality warning is generated.

[0027] Optionally, collecting the surrounding environment perception data of the current location of the target liquefied gas cylinder includes:

[0028] With the current position as the center, collect temperature sensor data in a circular area within a preset radius;

[0029] Through the gas concentration sensor, detect the concentration value and change gradient of combustible gas in the environment;

[0030] Collect MAC address distribution characteristics of surrounding mobile electronic devices and plan emergency evacuation routes based on real-time MAC distribution.

[0031] Optionally, the method further comprises: delivery route verification;

[0032] The delivery route verification includes:

[0033] Analyze the GPS trajectory data of the delivery person's handheld terminal and obtain the delivery person's location coordinate sequence in real time;

[0034] Calculate the distance between the actual path and the planned path. When the distance deviation exceeds the path tolerance value, a trajectory anomaly warning is triggered, and the track is verified in combination with the electronic fence data.

[0035] Optionally, in response to the warning instruction, collecting the surrounding environment perception data of the current location of the target liquefied gas cylinder, performing multi-source data fusion analysis through abnormal behavior recognition, and generating a graded warning signal includes:

[0036] The surrounding environment perception data includes: abnormal operation behavior detected by the camera, metal collision / gas leakage sound captured by the microphone, data collected by the gas concentration sensor and data collected by the motion sensor;

[0037] Performing data preprocessing on the surrounding environment perception data to extract key features;

[0038] Perform fusion analysis based on the data level of the surrounding environment perception data, including: fusion analysis based on the basic information of abnormal operation behavior captured by the camera and the physical status of the cylinder provided by the motion sensor data; distinguishing operation risks through the voiceprint characteristics of metal collision and cross-verifying with visual data; locating gas leakage sound through voiceprint and identifying concentration through concentration sensor data;

[0039] Determine the degree of urgency based on the fusion analysis results, generate graded warning signals, and trigger corresponding response measures, including:

[0040] When the analysis result meets the low risk requirement, a low-level response is triggered: only the geo-fence record is updated;

[0041] When the analysis results meet the medium risk, a medium-level response is triggered: a warning message is pushed and standardized operation instructions are provided;

[0042] When the analysis results meet the high risk requirement, a high-level response is triggered: remotely locking the liquefied gas cylinder valve and simultaneously sending an alarm;

[0043] When the analysis results meet the requirements of a critical state, a special response is triggered: all operations corresponding to low risk, medium risk, and high risk are executed; the emergency management platform is automatically reported; continuous positioning and tracking is initiated; and the sound and light alarm device on the equipment itself is activated.

[0044] Optionally, generating a graded warning signal includes:

[0045] Generate an early warning when the ambient temperature is greater than the preset temperature value and the position offset is greater than the preset distance;

[0046] Determine the day and night status and trigger the sound and light alarm during the preset night time period;

[0047] Calculate the real-time flow of people. If it meets the high-density area rules, the sound and light alarm intensity will be enhanced. If it meets the low-density area rules, the sound and light alarm intensity will be enhanced at the same level.

[0048] Through the API interface, the emergency department system sends early warnings within the preset range and automatically pushes standard response processes for different types of disposal.

[0049] Another aspect of the present invention provides a liquefied gas cylinder positioning abnormality warning device, comprising a processor and a memory;

[0050] The memory is used to store computer programs;

[0051] The processor is used to execute the above-mentioned liquefied gas cylinder positioning abnormality early warning method by calling the computer program.

[0052] It can be seen that the liquefied gas cylinder positioning abnormality warning method and device provided by the present invention can solve the problem that traditional static thresholds cannot adapt to complex scenarios (such as traffic congestion, population density changes), and improve the warning accuracy by dynamically adjusting the safety distance and time thresholds; perform multi-dimensional abnormality identification, for example, by integrating positioning data, environmental perception data (temperature, combustible gas, MAC address distribution) and delivery path verification, it can achieve all-round monitoring from location offset to environmental risks; perform graded warning and intelligent response, for example, the alarm intensity can be adaptively adjusted according to the day and night time and pedestrian flow density, and standardized emergency procedures can be automatically pushed to relevant departments to improve emergency efficiency; at the same time, it has an anti-disturbance design, reduces the intensity of sound and light alarms in high-density areas, avoids accidental triggering of public safety incidents, and plans evacuation routes through MAC address distribution to enhance safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 A flowchart of a method for early warning of abnormal positioning of a liquefied gas cylinder provided in an embodiment of the present invention;

[0055] Figure 2 A schematic diagram of the structure of the liquefied gas cylinder positioning hardware provided in an embodiment of the present invention;

[0056] Figure 3 A diagram of the server-side data processing function module provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0058] Figure 1 A flowchart of the abnormal early warning method for positioning a liquefied gas cylinder according to an embodiment of the present invention is shown. Figure 1 The embodiment of the present invention provides a method for early warning of abnormal positioning of a liquefied gas cylinder, comprising:

[0059] S1, obtaining the installation configuration parameters of the target liquefied gas cylinder, which at least include the deployment area type, delivery and extraction mode, and authorized activity area range;

[0060] S2, when the deployment area type is identified as a civilian residential area and the delivery and collection mode is autonomous collection, the real-time spatial coordinates of the cylinder are continuously collected;

[0061] S3, when the deployment area type is identified as a commercial residential area and the delivery and pickup mode is delivery by delivery person, the delivery time of the cylinder is continuously collected;

[0062] S4, builds a geo-fence boundary model, dynamically compares the real-time spatial coordinates with the scope of the authorized activity area, and generates an early warning instruction when it is detected that the spatial offset exceeds the preset safety distance threshold;

[0063] S5, in response to the warning instruction, collects the surrounding environment perception data of the current location of the target liquefied gas cylinder, performs multi-source data fusion analysis through abnormal behavior recognition, and generates a graded warning signal.

[0064] Specifically, if Figure 2 and Figure 3 As shown, first, a power supply module, a positioning module, an environmental perception module, a communication module and a main control chip are set at the liquefied gas cylinder of the present invention, and a data receiving module, a data storage module, a data processing module, a configuration parameter management module, an early warning generation module and a geographic fence model module are set at the server.

[0065] in:

[0066] (1) Each module on the liquefied gas cylinder has the following functions:

[0067] Positioning module: used to obtain the real-time spatial coordinates of the liquefied gas cylinder in real time. The real-time spatial coordinates can be obtained by combining Beidou positioning and WIFI positioning technology.

[0068] Environmental Perception Module: This module collects environmental data about the LPG cylinder's current location, including but not limited to temperature, gas concentration sensors, motion sensors, and other sensors. It can also include cameras, microphones, and other devices. This environmental perception data is used for subsequent abnormal behavior identification and multi-source data fusion analysis.

[0069] Main control chip: As the core of the entire terminal hardware subsystem installed on the liquefied gas cylinder, it coordinates the operations of various modules. It receives data from the positioning module and environmental perception module, and performs preliminary processing and analysis on the data. Simultaneously, the main control chip controls the communication module to transmit the data to the server.

[0070] Communication module: This module enables data communication between the terminal hardware subsystem and the server. It uses NB-IoT wireless communication technology to send collected positioning data and environmental perception data to the server.

[0071] Power module: Provides power to the positioning module, environmental perception module, main control chip, and communication module. It can be powered by batteries or an external power supply to ensure stable operation of the terminal hardware subsystem.

[0072] (2) Each module on the server has the following functions:

[0073] Data Receiving Module: This module is responsible for receiving positioning data and environmental perception data sent by the terminal hardware subsystem on the liquefied gas cylinder. This module communicates with the communication module to ensure accurate data reception.

[0074] Data storage module: stores the received data in a database for subsequent query and analysis. Data storage can be done using either a relational or non-relational database.

[0075] Data Processing Module: This module processes and analyzes stored data. Based on installation configuration parameters and the geofence boundary model, it dynamically compares real-time spatial coordinates to determine whether cylinders have shifted spatially. This module also identifies abnormal behavior and conducts multi-source data fusion analysis, integrating surrounding environmental perception data to uncover potential anomalies.

[0076] The Warning Generation Module generates warning signals based on the analysis results of the Data Processing Module. When the spatial offset exceeds the preset safety distance threshold, a warning instruction is generated. After multi-source data fusion analysis, a graded warning signal is generated. The warning signal can be notified to relevant personnel through system prompts.

[0077] The Geofence Model Module is responsible for building and managing the geofence boundary model. Based on the geographic coordinate dataset of the authorized activity area, it establishes polygonal geofence boundaries and sets parameters such as the dynamic traffic management coefficient. This module provides the data processing module with the basis for geofencing decisions.

[0078] Configuration parameter management module: manages the installation configuration parameters of the target liquefied gas cylinders, including deployment area type, distribution and extraction mode, and authorized activity area range.

[0079] As an optional implementation of an embodiment of the present invention, constructing a geofence boundary model includes: establishing a polygonal geofence boundary based on a geographic coordinate dataset of an authorized activity area; setting a dynamic traffic management coefficient; calculating the actual distance between two points closest to the fence boundary and the real-time spatial coordinates, and determining a preset safety distance threshold based on the traffic management coefficient. Setting the dynamic traffic management coefficient includes dynamically adjusting the traffic management coefficient based on regional population density and road grade parameters.

[0080] In specific implementation, the present invention has the following advantages by setting the dynamic traffic management coefficient:

[0081] 1. Dynamic risk adaptation:

[0082] Achieve intelligent matching of safety distance thresholds with regional traffic environments, solving the problem that traditional fixed thresholds cannot adapt to complex scenarios. For example:

[0083] Commercial area (population density> 8000 people / km 2 ) coefficient is adjusted to 1.3-1.5, and safety redundancy is increased in high-traffic scenarios. The coefficient can be refined according to peak hours.

[0084] The population density parameter P is directly connected to the real-time value of the municipal data platform. When P>10000, it is calculated as P=10000.

[0085] Association rules between road grade R and vehicle speed: The default match is R=2 (road speed within the area ≤40km / h), and the main roads in the core business district can be upgraded to R=3 (speed 40-60km / h).

[0086] For expressways, road grade A, speed ≥ 60 km / h, the coefficient is adjusted to 1-1.5, and dynamic adaptation is implemented in sections according to vehicle speed, using the road grade parameter R:

[0087] For Class A roads (speed ≥ 60 km / h), R = 4, and the coefficient calculation range is 1.45-1.65 (the higher the speed, the larger R, and the coefficient increases linearly with R)

[0088] For Class B roads (40km / h≤speed<60km / h), R=3, and the coefficient calculation range is 1.3-1.5

[0089] Sensitive areas around schools use mandatory coefficient correction rules based on different school start and end times:

[0090] School commute (7:00-9:00, 16:00-18:00): Directly apply the correction factor K′ = K × 1.5 (ensure the final factor is ≥ 2.0)

[0091] During non-school hours: Correction coefficient K′ = K × 1.2 (the coefficient is adjusted to 1.5-1.98)

[0092] 2. Improve early warning accuracy

[0093] By correcting traffic parameters in real time, the false alarm rate is reduced. The main influencing factors include:

[0094] Road speed (km / h)

[0095] Traffic flow during the period (vehicles / hour)

[0096] Special events (construction / large events)

[0097] Among them: Determining the preset safety distance threshold in combination with the traffic management coefficient includes:

[0098] Obtain preset reference values, which include: minimum safety distance and standard safety distance;

[0099] Load dynamic parameters, including real-time population density and road grade;

[0100] Construct a coefficient calculation model; dynamically adjust the safety distance threshold.

[0101] In specific implementation, the safety distance threshold generation process of the present invention may include:

[0102] (1) Basic parameter input

[0103] Get the preset baseline value:

[0104] Minimum safety distance D 最小值 =50m (suitable for high-density scenarios in urban core areas)

[0105] Standard safety distance D 标准值 =150m (applicable to ordinary urban areas, suburbs and other areas)

[0106] Load dynamic parameters:

[0107] Real-time population density P (unit: person / km 2 , from the municipal data platform, with an upper limit cutoff of 10,000)

[0108] Road grade R (1-4, mapped by speed: R = 1 corresponds to speed < 20 km / h, R = 2 corresponds to 20-40 km / h, R = 3 corresponds to 40-60 km / h, R = 4 corresponds to ≥ 60 km / h)

[0109] (2) Coefficient calculation model

[0110] K=1+0.2×(P / 10000)+0.15×(R-1)

[0111] Coefficient range: 1.0≤K≤1.65 (maximum value when P≥10000 and R=4)

[0112] (3) Dynamic adjustment of threshold

[0113] Calculate the final safety distance:

[0114] D 安全 =D 最小值 ×K (city core area)

[0115] D 安全 =D 标准值 ×K(other areas)

[0116] Special scene corrections:

[0117] A mandatory 20% buffer distance is required around schools and hospitals

[0118] During the night time (22:00-6:00), the sensitivity is reduced by 15%.

[0119] As an optional implementation of an embodiment of the present invention, continuously collecting the delivery time of the cylinder includes: obtaining the planned time window [T1, T2] in the electronic waybill of the delivery task; calculating the time deviation Δt between the current time and T1 in real time; the system initially sets the ΔTmax value, and dynamically corrects the time threshold ΔTmax based on real-time traffic data; and generating a delivery abnormality warning when Δt>ΔTmax.

[0120] In specific implementation, the following operations are performed when collecting delivery time: obtain the planned time window [T1, T2] in the electronic waybill of the delivery task; calculate the time deviation Δt between the current time and T1 in real time; the system initially sets the ΔTmax value, and dynamically adjusts the time threshold ΔTmax based on real-time traffic data. When congestion is severe, ΔTmax is extended, and when traffic is smooth, ΔTmax is shortened; when Δt>ΔTmax, a delivery abnormality warning is generated.

[0121] As an optional implementation of an embodiment of the present invention, collecting the surrounding environment perception data of the current location of the target liquefied gas cylinder includes: collecting temperature sensor data of a circular area within a preset radius centered on the current location; detecting the concentration value and change gradient of combustible gas in the environment through a gas concentration sensor; collecting the MAC address distribution characteristics of surrounding mobile electronic devices, and planning emergency evacuation routes based on the real-time MAC distribution.

[0122] In specific implementation, the present invention can collect temperature sensor data in a circular area within a radius of 50 meters with the current location as the center; detect the concentration value and change gradient of combustible gas in the environment through a gas concentration sensor; collect the MAC address distribution characteristics of surrounding mobile electronic devices, and plan emergency evacuation routes based on real-time MAC distribution.

[0123] As an optional implementation of the embodiment of the present invention, the liquefied gas cylinder positioning abnormality warning method provided by the embodiment of the present invention further includes: delivery path verification;

[0124] Delivery route verification includes:

[0125] Analyze the GPS trajectory data of the delivery person's handheld terminal and obtain the delivery person's location coordinate sequence in real time;

[0126] Calculate the distance between the actual path and the planned path. When the distance deviation exceeds the path tolerance value, a trajectory anomaly warning is triggered, and the track is verified in combination with the electronic fence data.

[0127] As an optional implementation of the embodiment of the present invention, in response to the warning instruction, the surrounding environment perception data of the current location of the target liquefied gas cylinder is collected, and multi-source data fusion analysis is performed through abnormal behavior recognition to generate a graded warning signal, including:

[0128] Surrounding environment perception data includes: abnormal operation behavior detected by cameras, metal collision / gas leakage sound captured by microphones, data collected by gas concentration sensors, and data collected by motion sensors;

[0129] Preprocess the surrounding environment perception data and extract key features;

[0130] Perform fusion analysis based on the data level of the surrounding environment perception data, including: fusion analysis based on the basic information of abnormal operation behavior captured by the camera and the physical status of the cylinder provided by the motion sensor data; distinguishing operation risks through the voiceprint characteristics of metal collision and cross-verifying with visual data; locating gas leakage sound through voiceprint and identifying concentration through concentration sensor data;

[0131] Determine the degree of urgency based on the fusion analysis results, generate graded warning signals, and trigger corresponding response measures, including:

[0132] When the analysis result meets the low risk requirement, a low-level response is triggered: only the geo-fence record is updated;

[0133] When the analysis results meet the medium risk, a medium-level response is triggered: a warning message is pushed and standardized operation instructions are provided;

[0134] When the analysis results meet the high risk requirement, a high-level response is triggered: remotely locking the liquefied gas cylinder valve and simultaneously sending an alarm;

[0135] When the analysis results meet the requirements of a critical state, a special response is triggered: all operations corresponding to low risk, medium risk, and high risk are executed; the emergency management platform is automatically reported; continuous positioning and tracking is initiated; and the sound and light alarm device on the equipment itself is activated.

[0136] Specifically, the present invention can divide the surrounding perception data into three levels: primary data: providing the physical status of the cylinder as a judgment based on the basic information of abnormal operation behavior captured by the camera and the motion sensor data; intermediate data: distinguishing operation risks through the voiceprint characteristics of metal collision, and cross-validating with visual data to improve the judgment accuracy; advanced data: locating the sound of gas leakage through voiceprints and identifying the concentration through concentration sensor data to achieve judgment.

[0137] The present invention can determine the degree of urgency based on the fusion analysis results, and thus can generate four levels of early warning responses according to the degree of urgency, including low-level response, medium-level response, high-level response and special-level response.

[0138] When the analysis result meets the low risk requirement, a low-level response is triggered: only the geo-fence record is updated;

[0139] When the analysis results meet the medium risk, a medium-level response is triggered: a warning message is pushed and standardized operation instructions are provided;

[0140] When the analysis results meet the high risk requirement, a high-level response is triggered: remotely locking the liquefied gas cylinder valve and simultaneously sending an alarm;

[0141] When the analysis results meet the requirements of a critical state, a special response is triggered: ① Execute all operations corresponding to low risk, medium risk, and high risk; ② Automatically report to the emergency management platform; ③ Start continuous positioning and tracking; ④ Activate the sound and light alarm device on the equipment itself.

[0142] In a specific implementation, the data processing flow after responding to the warning instruction of the present invention includes:

[0143] (1) Rapid collection of environmental data:

[0144] Start the sensor group around the positioning point, including:

[0145] The camera detects abnormal operating behavior;

[0146] The microphone captures the sound of metal collision / gas leakage;

[0147] Gas concentration detectors and motion sensors.

[0148] (2) Data preprocessing:

[0149] Unify time and coordinate benchmarks and filter invalid data;

[0150] Extract key features: position offset, gas concentration, and abnormal sound identification.

[0151] (3) Comprehensive judgment of abnormality:

[0152] Cross-validation of visual and voiceprint data:

[0153] If abnormal handling and metal collision sounds are detected at the same time, it is marked as high risk;

[0154] Only when the gas concentration exceeds the standard, a second confirmation is required in conjunction with the motion sensor.

[0155] (4) Graded warning triggering

[0156] There are four levels of response according to the degree of urgency:

[0157] Low risk (blue): electronic fence update record;

[0158] Medium risk (yellow): push alerts to enterprises;

[0159] High risk (orange): remote locking of cylinder valves;

[0160] Critical (red): Automatically report to the emergency platform and continuously locate.

[0161] As an optional implementation of the embodiment of the present invention, generating a graded warning signal includes:

[0162] Generate an early warning when the ambient temperature is greater than the preset temperature value and the position offset is greater than the preset distance;

[0163] Determine the day and night status and trigger the sound and light alarm during the preset night time period;

[0164] Calculate the real-time flow of people. If it meets the high-density area rules, the sound and light alarm intensity will be increased. If it meets the low-density area rules, the basic sound and light alarm intensity will be maintained.

[0165] Through the API interface, the emergency department system sends early warnings within the preset range and automatically pushes standard response processes for different types of disposal.

[0166] In specific implementation, the generation rules of the hierarchical warning signals of the present invention include:

[0167] Real-time monitoring through temperature sensors and positioning sensors generates an early warning when the ambient temperature is greater than 50°C and the deviation from the initial position is greater than 100 meters;

[0168] The light sensor determines the day and night status and triggers a high-decibel beep and red flashing light sound and light alarm during the night time (20:00-6:00);

[0169] Connecting to the city's big data platform or using terminal cameras to identify pedestrians, the system calculates real-time pedestrian flow based on the acquired data. In high-density areas, the intensity of the audible and visual alarms is reduced to avoid disturbing residents; in low-density areas, the intensity of the alarms is increased to improve legibility.

[0170] An early warning is sent to the emergency department system within 5 kilometers through the API interface, and the corresponding standard response process is automatically pushed according to the type of warning, including on-site disposal guidelines, contact information, material lists, etc.

[0171] The liquefied gas cylinder positioning abnormality warning method provided by the embodiment of the present invention can solve the problem that traditional static thresholds cannot adapt to complex scenarios (such as traffic congestion and changes in population density), and improve the warning accuracy by dynamically adjusting the safety distance and time thresholds; perform multi-dimensional abnormality identification, for example, by integrating positioning data, environmental perception data (temperature, combustible gas, MAC address distribution) and delivery path verification, it can achieve all-round monitoring from location offset to environmental risks; perform graded warning and intelligent response, for example, it can adaptively adjust the alarm intensity according to the day and night time and pedestrian density, and automatically push standardized emergency procedures to relevant departments to improve emergency efficiency; at the same time, it has an anti-disturbance design, reducing the sound and light alarm intensity in high-density areas at night to avoid accidentally triggering public safety incidents, and at the same time planning evacuation routes through MAC address distribution to enhance safety.

[0172] The present invention uses dynamic geo-fencing: dynamically adjusting the safety threshold based on the area type (civilian / commercial), population density, and road grade, rather than a fixed value; a multi-module collaborative mechanism: the positioning monitoring module and the duration monitoring module are activated according to the scene to avoid resource waste; environmental perception fusion: temperature, combustible gas, MAC address distribution data and positioning offset are jointly analyzed to achieve a progressive judgment from "location anomaly" to "environmental risk"; graded warning rules: triggering alarm modes based on day and night conditions and pedestrian density (such as high-decibel buzzers + flashing lights at night), taking into account both safety and non-disturbing issues. This can promptly detect users who illegally carry cylinders to unauthorized areas, and combine high-temperature warnings to prevent explosion risks; prevent delivery personnel from time-outs due to incorrect routes, and combine route verification to optimize routes; while ensuring a good rest environment for residents at night, ensure the visibility of alarm information in remote areas, thereby improving the efficiency of emergency response.

[0173] The present invention can be applied to the distribution and use scenarios of liquefied gas cylinders in civil residential areas (such as homes) and commercial residential areas (such as restaurants and hotels), covering the entire life cycle of cylinder transportation, storage, and use, especially for abnormal positioning, overtime delivery, and environmental safety risk warnings in autonomous extraction mode and delivery personnel delivery mode.

[0174] The specific application scenarios are as follows, but the present invention is not limited thereto:

[0175] Scenario 1: Abnormal movement of cylinders in a residential area

[0176] After the user independently retrieves the cylinder, the positioning monitoring module detects that the cylinder deviates from the authorized activity area (such as entering a non-residential area), with an offset of 120 meters (exceeding the preset threshold of 100 meters), triggering an early warning.

[0177] The system collects surrounding environmental data in a coordinated manner: if it detects a sudden temperature rise to 55°C within a 50-meter radius and an abnormal flammable gas concentration gradient, it will generate an early warning, activate an audible and visual alarm, and push the emergency process to the fire department.

[0178] Scenario 2: Commercial Area Delivery Timeout Verification

[0179] The delivery driver's planned time window is [14:00,15:00]. Due to traffic congestion, ΔTmax is dynamically extended from 30 minutes to 40 minutes.

[0180] At 3:25 PM, Δt = 85 minutes > ΔTmax, triggering a delivery anomaly warning. GPS trajectory data also verifies that the path deviation exceeds the tolerance limit, and after confirming the anomaly, the distribution center is notified for review.

[0181] Scenario 3: Optimizing alarms in low-density areas at night

[0182] The cylinder shifted 150 meters at 2:00 a.m., and the light sensor determined it was nighttime, triggering a high-decibel buzzer and a red flashing light.

[0183] The system detects that the distribution of MAC addresses in the surrounding area is sparse (low traffic flow) and automatically increases the alarm intensity to ensure identifiability.

[0184] As an optional implementation of an embodiment of the present invention, the liquefied gas cylinder positioning abnormality warning method provided by the embodiment of the present invention also includes: dynamically adjusting the path tolerance value. Specifically, by dynamically adjusting the path tolerance value, resource waste can be reduced: by dynamically adjusting the path tolerance value, unnecessary route changes caused by overly strict path restrictions can be avoided, reducing vehicle mileage, time, and energy consumption, and lowering delivery costs; and delivery efficiency can be improved: by allowing delivery personnel to flexibly select routes within a certain range, adapt to real-time traffic conditions and emergencies, ensure that delivery tasks are completed on time, and improve customer satisfaction.

[0185] The dynamic calculation of the path tolerance value can be performed using the following methods:

[0186] Statistical analysis based on historical data: This involves collecting route data for the same or similar delivery tasks over a period of time, analyzing the relationship between route deviations and various influencing factors, and building statistical models. For example, regression analysis can be used to determine the linear relationship between traffic congestion levels and route tolerances, allowing for the prediction of appropriate route tolerances based on real-time traffic data.

[0187] Real-time data analysis: Traffic sensors, GPS positioning systems, and other systems are used to obtain real-time road traffic information and delivery vehicle locations. This information is then combined with delivery time requirements and other factors to dynamically calculate route tolerances. For example, based on real-time traffic flow and vehicle speeds, the estimated travel time for the current road section is calculated, and then the route tolerance is determined based on the delivery time window.

[0188] Machine learning algorithms: Use machine learning algorithms, such as decision trees and neural networks, to train and analyze large amounts of historical and real-time data to establish a path tolerance value prediction model.

[0189] The process of dynamically calculating the path tolerance value may include:

[0190] Data collection: Real-time data collection of various influencing factors, including traffic conditions, weather information, vehicle location and status, delivery time windows, etc.

[0191] Data preprocessing: Clean, convert and normalize the collected data for subsequent analysis and calculation.

[0192] Model selection and training: Select appropriate calculation methods and models based on actual conditions, and use historical data to train and optimize the models.

[0193] Real-time calculation: Input the real-time collected data into the trained model to calculate the path tolerance value of the current delivery task.

[0194] Result update and feedback: The path tolerance value is updated in a timely manner according to the calculation results, and is fed back to the delivery path verification module to determine whether the delivery path is within an acceptable range.

[0195] It can be seen that the liquefied gas cylinder positioning abnormality warning method provided by the embodiment of the present invention has the following beneficial effects:

[0196] Accurate early warning: Dynamic geo-fencing combined with traffic management coefficients adapts the safety distance threshold to regional characteristics and reduces false alarm rates.

[0197] Fast response: Generate graded warning signals through multi-source data fusion (such as temperature + positioning offset + combustible gas gradient), which improves response speed.

[0198] Resource optimization: The delivery path verification module reduces resource waste caused by delivery anomalies, and the dynamic calculation of path tolerance values ​​improves delivery efficiency.

[0199] Intelligent collaboration: Linked with the city's big data platform, it enables emergency departments within 5 kilometers to receive early warning information simultaneously, shortening emergency response time.

[0200] The present invention also provides a liquefied gas cylinder positioning abnormality warning device, comprising: a processor, a memory;

[0201] memory for storing computer programs;

[0202] The processor is used to execute the above-mentioned liquefied gas cylinder positioning abnormality early warning method by calling a computer program.

[0203] It can be seen that the liquefied gas cylinder positioning abnormality warning device provided by the embodiment of the present invention has the following beneficial effects:

[0204] Accurate early warning: Dynamic geo-fencing combined with traffic management coefficients adapts the safety distance threshold to regional characteristics and reduces false alarm rates.

[0205] Fast response: Generate graded warning signals through multi-source data fusion (such as temperature + positioning offset + combustible gas gradient), which improves response speed.

[0206] Resource optimization: The delivery path verification module reduces resource waste caused by delivery anomalies, and the dynamic calculation of path tolerance values ​​improves delivery efficiency.

[0207] Intelligent collaboration: Linked with the city's big data platform, it enables emergency departments within 5 kilometers to receive early warning information simultaneously, shortening emergency response time.

[0208] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for early warning of abnormal positioning of liquefied gas cylinders, characterized in that: include: Obtaining installation configuration parameters of the target liquefied gas cylinder, wherein the installation configuration parameters at least include a deployment area type, a delivery and extraction mode, and an authorized activity area range; When it is identified that the deployment area type is a civilian residential area and the delivery and collection mode is autonomous collection, continuously collecting the real-time spatial coordinates of the cylinder; When it is identified that the deployment area type is a commercial residential area and the delivery and extraction mode is delivery by a delivery person, the delivery time of the cylinder is continuously collected; Constructing a geo-fence boundary model, dynamically comparing the real-time spatial coordinates with the scope of the authorized activity area, and generating an early warning instruction when it is detected that the spatial offset exceeds a preset safety distance threshold; In response to the early warning instruction, the surrounding environment perception data of the current location of the target liquefied gas cylinder is collected, and multi-source data fusion analysis is performed through abnormal behavior recognition to generate a graded early warning signal.

2. The method according to claim 1, characterized in that The construction of the geo-fence boundary model includes: Establishing a polygonal geo-fence boundary based on the geographic coordinate dataset of the authorized activity area; Set dynamic traffic management coefficient; The actual distance between the real-time spatial coordinates and the two points closest to the fence boundary is calculated, and the preset safety distance threshold is determined in combination with the traffic management coefficient.

3. The method according to claim 2, characterized in that The setting of the dynamic traffic management coefficient includes: The traffic management coefficient is dynamically adjusted based on regional population density and road grade parameters.

4. The method according to claim 3, characterized in that Determining the preset safety distance threshold in combination with the traffic management coefficient includes: Obtaining preset reference values, the preset reference values ​​including: minimum safety distance and standard safety distance; Loading dynamic parameters, the dynamic parameters including: real-time population density and road grade; Construct coefficient calculation model; The safety distance threshold is dynamically adjusted.

5. The method according to claim 1, wherein The continuous collection of the delivery time of the cylinder includes: Get the planned time window [T1, T2] in the delivery task electronic waybill; Calculate the time deviation Δt between the current time and T1 in real time; The system initially sets the ΔTmax value and dynamically modifies the time threshold ΔTmax based on real-time traffic data; When Δt>ΔTmax, a delivery abnormality warning is generated.

6. The method according to claim 1, characterized in that The collecting of the surrounding environment perception data of the current location of the target liquefied gas cylinder includes: With the current position as the center, collect temperature sensor data in a circular area within a preset radius; Through the gas concentration sensor, detect the concentration value and change gradient of combustible gas in the environment; Collect MAC address distribution characteristics of surrounding mobile electronic devices and plan emergency evacuation routes based on real-time MAC distribution.

7. The method according to claim 1, characterized in that Also includes: Delivery route verification; The delivery route verification includes: Analyze the GPS trajectory data of the delivery person's handheld terminal and obtain the delivery person's location coordinate sequence in real time; Calculate the distance between the actual path and the planned path. When the distance deviation exceeds the path tolerance value, a trajectory anomaly warning is triggered, and the track is verified in combination with the electronic fence data.

8. The method according to claim 1, characterized in that In response to the warning instruction, collecting the surrounding environment perception data of the current location of the target liquefied gas cylinder, performing multi-source data fusion analysis through abnormal behavior recognition, and generating a graded warning signal includes: The surrounding environment perception data includes: abnormal operation behavior detected by the camera, metal collision / gas leakage sound captured by the microphone, data collected by the gas concentration sensor and data collected by the motion sensor; Performing data preprocessing on the surrounding environment perception data to extract key features; Perform fusion analysis based on the data level of the surrounding environment perception data, including: fusion analysis based on the basic information of abnormal operation behavior captured by the camera and the physical status of the cylinder provided by the motion sensor data; distinguishing operation risks through the voiceprint characteristics of metal collision and cross-verifying with visual data; locating gas leakage sound through voiceprint and identifying concentration through concentration sensor data; Determine the degree of urgency based on the fusion analysis results, generate graded warning signals, and trigger corresponding response measures, including: When the analysis result meets the low risk requirement, a low-level response is triggered: only the geo-fence record is updated; When the analysis results meet the medium risk, a medium-level response is triggered: a warning message is pushed and standardized operation instructions are provided; When the analysis results meet the high risk requirement, a high-level response is triggered: remotely locking the liquefied gas cylinder valve and simultaneously sending an alarm; When the analysis results meet the requirements of a critical state, a special response is triggered: all operations corresponding to low risk, medium risk, and high risk are executed; the emergency management platform is automatically reported; continuous positioning and tracking is initiated; and the sound and light alarm device on the equipment itself is activated.

9. The method according to claim 7, characterized in that Generating a graded warning signal includes: Generate an early warning when the ambient temperature is greater than the preset temperature value and the position offset is greater than the preset distance; Determine the day and night status and trigger the sound and light alarm during the preset night time period; Calculate the real-time flow of people. If it meets the high-density area rules, the sound and light alarm intensity will be increased; if it meets the low-density area rules, the basic sound and light alarm intensity will be maintained. Through the API interface, the emergency department system sends early warnings within the preset range and automatically pushes standard response processes for different types of disposal.

10. A liquefied gas cylinder positioning abnormality warning device, characterized in that: Including processor and memory; The memory is used to store computer programs; The processor is configured to execute the liquefied gas cylinder positioning abnormality warning method according to any one of claims 1 to 9 by calling the computer program.

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