Position positioning and environment monitoring method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a position positioning and environment monitoring method and device, electronic equipment and a storage medium, and is applied to the technical field of communication, and the method comprises the steps: collecting an observation index of a terminal in a wireless network; obtaining a pre-constructed positioning fingerprint database; and determining the target position of the terminal by using a particle filtering algorithm, particles and / or the position of the particles in the particle filtering algorithm being updated based on the observation index, and the particle weight of the particles in the particle filtering algorithm being determined by the distance between the particles and the first reference terminal. By adopting the technical scheme, a high-precision positioning scheme can be provided based on a wireless network in an area where satellite signals cannot be received.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus, electronic device and storage medium for location positioning and environmental monitoring. Background Technology

[0002] Satellite positioning is commonly used in related technologies, such as GPS (Global Positioning System). However, there are also many scenarios where positioning is needed in areas where satellite signals cannot be received, such as in coal mine production where workers need to be located to improve safety.

[0003] Among related technologies, there is a lack of technical solutions to provide accurate positioning in areas where satellite signals cannot be received. Summary of the Invention

[0004] The purpose of one embodiment of this specification is to provide a method, apparatus, electronic device, and storage medium for location positioning, and the purpose of another embodiment of this specification is to provide a method, apparatus, electronic device, and storage medium for environmental monitoring.

[0005] To solve the above-mentioned technical problems, one embodiment of this specification is implemented as follows: Firstly, one embodiment of this specification provides a method for location positioning, the method comprising: Observational indicators of the data acquisition terminal in the wireless network; Obtain a pre-built location fingerprint database, which includes multiple preset reference indicators of reference terminals in the wireless network; The target position of the terminal is determined by a particle filtering algorithm. In the particle filtering algorithm, the position of the particles and / or the particle position is updated based on the observation index. The particle weight of the particles in the particle filtering algorithm is determined by the distance between the particles and the first reference terminal. The first reference terminal is at least one reference terminal whose distance from the particles is less than a preset distance threshold. The observation metrics and the reference metrics have the same dimension, including at least one wireless performance metric.

[0006] Secondly, another embodiment of this specification provides a method for environmental monitoring, the method comprising: Acquire environmental data reported by at least one reference terminal in the environment; If there is a security risk in the environmental data reported by any target reference terminal, the location positioning method described in any of the first aspects above shall be used to determine the first target location of the terminal. A security warning is sent to the target terminal whose first target location is within the range corresponding to the target reference terminal.

[0007] Thirdly, in another embodiment of this specification, a positioning device is provided, the device comprising: The data acquisition module is used to collect observation indicators of the terminal in the wireless network; The acquisition module is used to acquire a pre-built location fingerprint database, which includes multiple preset reference indicators of reference terminals in the wireless network. The determination module is used to determine the target position of the terminal using a particle filtering algorithm. In the particle filtering algorithm, the position of the particle and / or the particle is updated based on the observation index. In the particle filtering algorithm, the particle weight is determined by the distance between the particle and the first reference terminal. The first reference terminal is at least one reference terminal whose distance from the particle is less than a preset distance threshold. The observation metrics and the reference metrics have the same dimension, including at least one wireless performance metric.

[0008] Fourthly, in another embodiment of this specification, an environmental monitoring device is provided, the device comprising: The acquisition module is used to acquire environmental data reported by at least one reference terminal in the environment; The determination module is used to determine the first target location of the terminal by the location positioning method as described in any one of claims 1 to 6, in the event that there is a security risk in the environmental data reported by any target reference terminal; The early warning module is used to send a security warning to the target terminal whose first target location is within the range corresponding to the target reference terminal.

[0009] Fifthly, in another embodiment of this specification, an electronic device is provided, including a processor, a memory, and a communication bus; The communication bus is used to enable communication between the processor and the memory; The processor is configured to execute one or more programs stored in the memory to implement the steps of the location positioning method described in the first aspect above, or to implement the steps of the location positioning method described in the second aspect above.

[0010] In a sixth aspect, this specification provides a computer-readable storage medium in another embodiment for storing computer-executable instructions that, when executed by a processor, can implement the steps of the location positioning method described in the first aspect, or implement the steps of the location positioning method described in the second aspect.

[0011] In a seventh aspect, this specification provides a computer program product in another embodiment, the computer program product including a processing program, the processing program being executed by a processor to implement the steps of the location positioning method described in the first aspect and the steps of the location positioning method described in the second aspect.

[0012] This embodiment of the disclosure collects observation indicators of a terminal in a wireless network; acquires a pre-constructed positioning fingerprint database; and uses a particle filtering algorithm to determine the target location of the terminal. In the particle filtering algorithm, the positions of particles and / or particles are updated based on the observation indicators, and the particle weights are determined by the distance between the particles and a first reference terminal. Using the above technical solution, a high-precision positioning scheme based on a wireless network can be provided in areas where satellite signals cannot be received.

[0013] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.

[0014] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in one or more embodiments of this specification, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a block diagram illustrating an implementation of a location positioning method according to one embodiment of this specification. Figure 2 A flowchart illustrating another location positioning method provided in one embodiment of this specification; Figure 3 A flowchart illustrating yet another location positioning method provided in one embodiment of this specification; Figure 4 A flowchart illustrating an environmental monitoring method provided in one embodiment of this specification; Figure 5 A flowchart illustrating another environmental monitoring method provided in one embodiment of this specification; Figure 6 A block diagram of a positioning device provided in one embodiment of this specification; Figure 7 A block diagram of another positioning device provided in one embodiment of this specification; Figure 8 A block diagram of an environmental monitoring device provided in one embodiment of this specification; Figure 9 This is a schematic diagram of the hardware structure of an electronic device provided in one embodiment of this specification. Detailed Implementation

[0017] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments.

[0018] It is worth noting that the technologies described in this application are not limited to Long Term Evolution (LTE) / LTE-Advanced (LTE-A) systems, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA), or other systems. The terms "system" and "network" in this application are often used interchangeably, and the described technologies can be used in the systems and radio technologies mentioned above, as well as in other systems and radio technologies. The following description describes New Radio (NR) systems for illustrative purposes, and the term NR is used in most of the following description; however, these technologies can also be applied to systems other than NR systems, such as 6th Generation (6G) communication systems.

[0019] This application embodiment can be executed by a server in a wireless communication system, which includes a terminal and network-side devices. The terminal 11 can also be referred to as User Equipment (UE), and can be a mobile phone, tablet personal computer, personal digital assistant (PDA), handheld computer, netbook, mobile internet device (MID), wearable device, IoT terminal, or other terminal-side devices. It should be noted that this application embodiment does not limit the specific type of terminal. Network-side devices can include access network devices or core network devices, wherein access network devices can also be referred to as Radio Access Network (RAN) devices, radio access network functions, or radio access network units. Access network devices can include base stations. The base station may be referred to as Node B (NB), Evolved Node B (eNB), Next Generation Node B (gNB), New Radio Node B (NR Node B), Access Point, Relay Base Station (RBS), Serving Base Station (SBS), Base Transceiver Station (BTS), or any other suitable term in the relevant field, as long as the same technical effect is achieved. The base station is not limited to specific technical terms. It should be noted that the embodiments of this application only use the base station in the NR system as an example for introduction, and do not limit the specific type of base station.

[0020] This specification provides an embodiment of a location positioning method, referring to... Figure 1 The flowchart shown in this embodiment illustrates a location positioning method. This method can run on a server, specifically, it can be executed by software in the server. The location positioning method provided in this embodiment specifically includes the following steps.

[0021] In step S101, the observation indicators of the acquisition terminal in the wireless network are collected.

[0022] The observation metrics may include at least one wireless performance metric. Specifically, at least one wireless performance metric may include at least one of the following: received signal strength indication, time of arrival, and time difference of arrival.

[0023] For example, the terminal can be an Internet of Things (IoT) terminal. In a mining scenario, the terminal could be an IoT terminal installed on a worker's headlamp, and the server could collect the observation indicators of the IoT terminal through a base station in a wireless network.

[0024] Taking NR as an example, the Received Signal Strength Indicator (RSSI) can be collected by a base station. The Time of Arrival (TOA) can be used. In one possible implementation, a base station can send a probe signal to the terminal and receive a response signal from the terminal in response to the probe signal. The arrival time is determined based on the time difference between the response signal and the probe signal. In another possible implementation, the arrival time can be obtained by subtracting a preset terminal processing delay from the time difference between the response signal and the probe signal. Alternatively, the arrival time can be obtained by subtracting the preset terminal processing delay from the time difference between the response signal and the probe signal and then dividing by 2.

[0025] The time difference of arrival (TDOA) can be used. In one possible implementation, two base stations can receive the same signal sent by the terminal, and the time difference between the two base stations receiving the signal can be used as the time difference of arrival.

[0026] It is understandable that the observation indicators may include one or more of the above indicators, and other wireless performance indicators may be added as appropriate, as long as the differences in the wireless performance indicators have a certain degree of distinguishability for terminal location positioning.

[0027] In step S102, a pre-built location fingerprint database is obtained.

[0028] The location fingerprint database includes multiple preset reference indicators for reference terminals in the wireless network.

[0029] To assist in terminal positioning, multiple reference terminals at fixed locations can be pre-defined in the wireless network, and reference indicators for each reference terminal in the wireless network can be pre-acquired. The observed indicators and reference indicators have the same dimension; that is, the reference indicators are similar to the observed indicators and also include at least one wireless performance indicator with the same dimension. The positioning fingerprint database is constructed based on the reference indicators of each reference terminal and its corresponding pre-defined fixed location, which can be represented by coordinates (x, y).

[0030] In this embodiment of the application, both the observation index and the reference index include the received signal strength indication, the time of arrival, and the time difference of arrival.

[0031] In step S103, the target location of the terminal is determined using a particle filter algorithm.

[0032] In the particle filtering algorithm, the position of particles and / or particles is updated based on observation indicators. The particle weight of a particle in the particle filtering algorithm is determined by the distance between the particle and the first reference terminal. The first reference terminal is at least one reference terminal whose distance from the particle is less than a preset distance threshold.

[0033] In this embodiment, the particle filtering algorithm is a Bayesian filtering algorithm. It uses a series of random samples (called "particles") to represent the posterior probability distribution of the position of the terminal to be located. It can use the observation indicators corresponding to multiple time moments as the motion model of the terminal. The algorithm can predict the position of the next time moment based on the current position of the particle and the motion model, thereby updating the position of the particle. The above process is called prediction in the particle filtering algorithm.

[0034] The particle filtering algorithm can also update particles based on their current position and a first position determined by observation metrics. For example, particles whose current position is greater than or equal to a first threshold from the first position are deleted, while particles whose current position is less than a second threshold (the second threshold being less than the first threshold) can be randomly generated, thus updating the particles. Simultaneously, the weight of each particle can be determined so that the terminal position can be determined based on the position of each particle and its corresponding weight. This process is called the update and resampling process in the particle filtering algorithm. Through the above prediction, update, and resampling processes, the particle filtering algorithm continuously converges the particle swarm to the vicinity of the true terminal position. Based on the positions of the converged particles and their corresponding weights, the target position of the terminal can be determined.

[0035] By adopting the above technical solution, a high-precision positioning solution can be provided based on wireless networks in areas where satellite signals cannot be received.

[0036] Figure 2 A flowchart illustrating another location positioning method provided in one embodiment of this specification is shown below. Figure 2 As shown, step S103 may specifically include the following steps.

[0037] Step S1031 is step 1, which determines the first location of the terminal based on the observation indicators and the positioning fingerprint database.

[0038] In some embodiments, the observation index can be normalized and used as the observation index vector, and the reference index of each reference terminal in the positioning fingerprint data can be normalized and used as the reference index vector. Based on the cosine similarity between the observation index vector and the reference index vector, a first preset number (e.g., 3) of second reference terminals closest to the terminal can be determined, and the first position can be obtained according to the preset fixed position and corresponding weight of the first preset number (e.g., 3) of second reference terminals.

[0039] For example, step 1 may specifically include the following steps: In step 11, a first preset number of second reference terminals are determined from the reference terminals. The second reference terminals are the first preset number of reference terminals whose cosine similarity between the first vector composed of the corresponding reference indicators and the second vector composed of the observation indicators is the highest.

[0040] For example, the cosine similarity between the first vector composed of the corresponding reference indicators in each reference terminal and the second vector composed of the observation indicators can be calculated, and the cosine similarity can be sorted in descending order to obtain the first preset number of reference terminals at the top of the sorted order as the second reference terminals.

[0041] In step 12, the positions of the first preset number of second reference terminals are weighted and summed using cosine similarity as the weight to determine the first position of the terminal.

[0042] For example, the first position of the terminal can be determined by the following formula.

[0043] (Formula 1) in,( , () represents the first position of the terminal. Let be the weight corresponding to the i-th second reference terminal, that is, the cosine similarity between the first vector composed of reference indicators corresponding to the second reference terminal and the second vector composed of observation indicators. , ) represents the preset fixed position corresponding to the i-th second reference terminal, and k represents the number of second reference terminals, for example, 3.

[0044] Step S1032 is step 2, which updates the positions of particles and / or particles in the particle filtering algorithm based on the first positions corresponding to multiple time points.

[0045] In some embodiments, particles can be updated using a particle filtering algorithm. For example, particles whose distance from the current position to the first position is greater than or equal to a first threshold are deleted, thereby eliminating particles with large errors. Particles whose distance from the current position to the first position is less than a second threshold (the second threshold is less than the first threshold) can be randomly generated as new particles, and the initial position of the newly generated particles is determined based on the particles whose distance from the current position to the first position is less than the second threshold.

[0046] In some embodiments, for particles whose distance is less than a first threshold, the predicted position at the next moment can be predicted based on the particle's current position and the motion model represented by the first position corresponding to multiple moments, and the current position of these particles can be updated to the predicted position, thereby realizing the updating of the particle's position.

[0047] For a more detailed implementation of updating the positions of particles and / or particles in the particle filter algorithm, please refer to the relevant documentation on the particle filter algorithm, which will not be elaborated here.

[0048] Step S1033 is step 3, which updates the particle weights of the updated particles based on the observed indicators.

[0049] For example, step 3 may specifically include the following steps: In step 31, at least one first reference terminal corresponding to the particle is obtained.

[0050] In some embodiments, a second preset number (e.g., 5) of reference terminals closest to the particle's current position can be obtained as the first reference terminal.

[0051] In some possible implementations, the Euclidean distance between the preset fixed position of each reference terminal and the current position of the particle can be obtained, and the reference terminals can be sorted in ascending order according to the Euclidean distance, with the second preset number of reference terminals at the top of the sort as the first reference terminals.

[0052] In step 32, the first similarity between the first reference index corresponding to at least one first reference terminal and the observation index is determined respectively.

[0053] Each first similarity corresponds to a target weight, and the target weight is related to the distance between the corresponding first reference terminal and the particle.

[0054] For example, the similarity between each wireless performance indicator in the observed indicator and the first reference indicator can be obtained, and the similarity between each wireless performance indicator can be weighted and summed based on a preset weight to obtain the first similarity between the first reference indicator and the observed indicator.

[0055] In some possible implementations, the similarity between each wireless performance index in the observation index and the first reference index can be determined using the following formula 2.

[0056] (Formula 2) in, The similarity is indicated by the received signal strength of the observed index and the j-th first reference index. The similarity of arrival times between the observed index and the j-th first reference index. Let exp() be the similarity of the arrival time difference between the observed index and the j-th first reference index, and let exp() be the natural exponential function. This refers to the received signal strength indicator in the observation metrics. This is the received signal strength indication in the j-th first reference index. For arrival time in the observed indicators, For the j-th first reference indicator, the arrival time is... The arrival time difference in the observed indicators. Let j be the arrival time difference in the first reference index. , , These are preset adjustment coefficients for received signal strength indication, arrival time, and time difference of arrival, respectively.

[0057] After determining the similarity of each wireless performance index in the observation index and the first reference index, the first similarity can be obtained by weighted summation of each similarity according to the following formula 3.

[0058] (Formula 3) in, The first similarity between the first reference index and the observed index corresponding to the j-th first reference terminal. , , These are preset weights for received signal strength indication, time of arrival, and time difference of arrival, respectively. Optionally, this... , , Each can be 1 / 3.

[0059] In step 33, the first similarity is weighted and summed based on the target weight to obtain the second similarity.

[0060] For example, the target weight can be determined by Formula 4 below, and the second similarity can be obtained by weighted summation of the first similarity based on the target weight by Formula 5 below.

[0061] (Formula 4) in, Let the target weight be the j-th first reference terminal. Indicates the position of the k-th particle The preset fixed position of the j-th first reference terminal European distance, Indicates the position of the k-th particle The preset fixed position of the m-th first reference terminal European distance, Let be the set of the first reference terminals corresponding to the k-th particle. It is understandable that the sets of the first reference terminals corresponding to different particles can be different.

[0062] (Formula 5) in, This represents the second similarity score corresponding to the k-th particle.

[0063] In step 33, the particle weights of the particles are updated based on the second similarity.

[0064] In some embodiments, the particle weights of the particles can be updated based on the second similarity using Formula Six.

[0065] (Formula 6) in, The particle weights before the k-th particle is updated. The updated particle weights for the k-th particle.

[0066] Step S1034 is step 4, which involves collecting the latest observation indicators of the terminal in the wireless network and repeating steps 1 to 3 until the preset conditions are met.

[0067] For example, the preset condition could be that the number of iterations is greater than a preset threshold.

[0068] Step S1035 is step 5, which determines the target position based on the particle position and corresponding particle weight of each particle.

[0069] The position of each particle is a random sample, and its weight reflects the probability that the terminal is at that particle's position. The target position can be obtained by calculating the weighted average of the positions of each particle. In some possible implementations, the target position can be determined using the following formula (Formula 7).

[0070] (Formula 7) in,( , () represents the target location of the terminal. Let L be the particle weight corresponding to the Lth particle. , ) represents the position of the Lth particle, and N represents the number of particles, for example, 5000.

[0071] By adopting the above technical solution, a high-precision positioning solution can be provided based on wireless networks in areas where satellite signals cannot be received.

[0072] Figure 4 A flowchart illustrating yet another location positioning method provided in one embodiment of this specification is shown below. Figure 4 As shown, the method may also include the following steps.

[0073] In step S104, reference indicators of multiple preset reference terminals are obtained.

[0074] In some embodiments, the preset reference terminal can be a terminal that is fixedly installed in the wireless network to mark a preset fixed location. For example, in mine positioning, the mine roadway can be abstracted into a topological map similar to a subway line map, and key location points such as intersections, turns, working faces, equipment locations, personnel rest areas, escape passages, etc. can be marked on the map. Reference terminals can be deployed at key location points. In order to improve the convenience of deployment, the reference terminal can be a passive Internet of Things terminal.

[0075] Reference indicators of multiple preset reference terminals can be obtained through one or more base stations. The specific method is similar to the technical solution for collecting the observation indicators of the terminal in the wireless network in step S101, and will not be elaborated here.

[0076] To improve the robustness of the fingerprint database, in some embodiments, the reference index is the average value of the wireless performance index obtained by each reference terminal at multiple times. Taking the reference index including received signal strength indication, time of arrival, and time difference of arrival as an example, the received signal strength indication, time of arrival, and time difference of arrival in the reference index obtained by a certain reference terminal through M measurements can be averaged respectively, and the average value of the received signal strength indication, time of arrival, and time difference of arrival can be used as the reference index of the reference terminal. Specifically, it can be expressed by the following formula eight.

[0077] (Formula 8) in, Let be the feature vector composed of the reference indicators of the j-th reference terminal. Let M be the average of the M received signal strength indicators corresponding to the j-th reference terminal. Let M be the average of the M arrival times corresponding to the j-th reference terminal. It is the average of the M arrival time differences corresponding to the j-th reference terminal.

[0078] In step S105, the reference indicators are associated with the locations of the corresponding reference terminals and stored in the database to obtain the location fingerprint database.

[0079] By adopting the above technical solution, an accurate positioning fingerprint database can be established, providing a data foundation for a high-precision positioning solution based on wireless networks in areas where satellite signals cannot be received.

[0080] Based on the location positioning embodiment provided in the first aspect, this location positioning method can be applied to environmental monitoring. Taking mine environmental monitoring as an example, an IoT terminal capable of acquiring the sensing results of environmental monitoring sensors can be used as a reference terminal. In addition to assisting in the construction of location fingerprint data to facilitate terminal location positioning, it can also monitor environmental conditions. Combining environmental monitoring and location positioning helps reduce deployment costs and maintenance difficulties.

[0081] Figure 4 A flowchart illustrating an environmental monitoring method provided in one embodiment of this specification is shown below. Figure 4 As shown, the method may include the following steps.

[0082] In step S201, environmental data reported by at least one reference terminal in the environment is obtained.

[0083] Taking mine environmental monitoring as an example, environmental data may include the identifier of a reference terminal so that the server can determine the impact range corresponding to abnormal environmental data based on the identifier of the reference terminal. It may also include at least one of gas concentration, temperature, and humidity. In some possible implementations, the reference terminal may be connected to at least one environmental monitoring sensor to collect environmental data. The at least one environmental monitoring sensor may include at least one of a hazardous gas sensor, a temperature sensor, and a humidity sensor. The at least one environmental monitoring sensor may be deployed independently or integrated into the reference terminal; this application does not impose any limitations on this.

[0084] In some embodiments, the deployment density of reference terminals can be determined based on the regional risk level. For example, in a mining scenario, no less than one terminal can be deployed per 10 square meters in densely populated coal mining areas; at least three terminals can be deployed within 2 meters of each device in areas prone to equipment failure; no less than one terminal per 5 square meters in poorly ventilated areas; and for areas with water seepage or fire hazards, or areas where gas tends to accumulate, the terminal deployment density can be appropriately increased to improve monitoring sensitivity.

[0085] In step S202, if there is a security risk in the environmental data reported by any target reference terminal, the first target location of the terminal is determined.

[0086] For example, in a mining scenario, the terminal may be a mobile terminal installed in the worker's headlamp. In some embodiments, the environmental data reported by the reference terminal may be compared with a preset safety threshold range. If at least one piece of environmental data exceeds the safety threshold range, it is determined that the environmental data poses a safety risk.

[0087] For example, environmental data can be the concentration of harmful gases. If the concentration of harmful gases in the environmental data reported by any target reference terminal exceeds a preset concentration threshold, the first target location of the terminal can be determined.

[0088] The environmental data can be temperature. The first target location of the terminal can be determined if the temperature in the environmental data reported by any target reference terminal is greater than or equal to a preset first temperature threshold, or if the temperature is less than a preset second temperature threshold (the second temperature threshold is less than the first temperature threshold).

[0089] The environmental data can be humidity. The first target location of the terminal can be determined if the humidity in the environmental data reported by any target reference terminal is greater than or equal to a preset first humidity threshold, or if the temperature is less than a preset second humidity threshold (the second humidity threshold is less than the first humidity threshold).

[0090] In step S203, a security warning is sent to the target terminal whose first target location is within the range corresponding to the target reference terminal.

[0091] In some embodiments, the identification information of reference terminals and the corresponding preset fixed positions can be stored in the database. If there is a security risk in the environmental data reported by any target reference terminal, the first target position of the terminal can be determined. The Euclidean distance between the first target position of each terminal and the preset fixed position corresponding to the target reference terminal can be calculated. If the Euclidean distance is less than a preset distance threshold, it can be determined that the first target position of the terminal is within the range corresponding to the target reference terminal, thereby sending a security warning to the target terminal.

[0092] In some embodiments, different safety warnings can be sent according to the specific type of safety risk. For example, in a mining scenario, if the concentration of a certain gas exceeds the corresponding concentration threshold, a gas concentration exceeding the limit safety warning can be sent. If the temperature exceeds the temperature threshold, a temperature exceeding the limit or fire risk safety warning can be sent. If the humidity exceeds the humidity threshold, a humidity exceeding the limit or water seepage risk safety warning can be sent.

[0093] When issuing safety alerts, the content of different alerts can vary. For example, in a mining scenario, if the concentration of a certain gas exceeds a corresponding concentration threshold, the safety alert could include the location of the reference terminal that detected the gas leak, the gas type, the concentration value, and the time the limit was exceeded. If the temperature exceeds a temperature threshold, the safety alert could include the location of the reference terminal that detected the temperature exceedance, the temperature value, and the time the exceedance was exceeded. If the humidity exceeds a humidity threshold, the safety alert could include the location of the reference terminal that detected the humidity exceedance, the humidity value, and the time the exceedance was exceeded. Furthermore, all safety alerts can include timestamps for easy recording and analysis.

[0094] In some examples, audible and visual alarms can be broadcast to alert relevant staff. In another example, safety warnings can be sent to relevant managers and / or rescue personnel via SMS, app push notifications, or other means.

[0095] By adopting the above technical solution, early warning information can be sent to nearby terminals in a timely manner based on environmental data, improving safety. Using passive IoT terminals as reference terminals, which also function as environmental monitoring and positioning reference terminals, eliminates the need for complex calibration and adjustment of numerous sensors, simplifying system deployment and maintenance and significantly reducing hardware and maintenance costs. Furthermore, integrating location positioning and environmental monitoring into a single system enables comprehensive monitoring and early warning of the environment (e.g., in mines), avoiding information silos and improving the efficiency of safety assurance.

[0096] Figure 5 A flowchart illustrating another environmental monitoring method provided in one embodiment of this specification, such as... Figure 5 As shown, step S201 may specifically include the following steps: In step S2011, a wake-up signal is periodically broadcast to wake up passive IoT terminals in the environment.

[0097] In some embodiments, the reference terminal is a passive IoT terminal, which can be powered by the radio frequency signal of the base station without the need for battery power, thus achieving low power consumption and maintenance-free operation. The reference terminal can periodically report environmental data, and can enter a sleep state during reporting intervals to save energy.

[0098] In some embodiments, the server can periodically broadcast a wake-up signal via a base station to wake up a reference terminal that is in a dormant state.

[0099] In step S2012, environmental data reported by the passive IoT terminal is received.

[0100] Because the passive IoT terminal used does not require batteries, it achieves low power consumption and maintenance-free operation, greatly extending the terminal's lifespan, avoiding the safety hazard of system failure due to battery depletion, and further reducing maintenance costs and workload.

[0101] Figure 6 A block diagram of a positioning device provided in one embodiment of this specification, such as... Figure 6 As shown, the positioning device 100 includes: The acquisition module 110 is used to collect the observation indicators of the terminal in the wireless network; The acquisition module 120 is used to acquire a pre-built location fingerprint database, which includes multiple preset reference indicators of reference terminals in the wireless network. The determination module 130 is used to determine the target position of the terminal using a particle filtering algorithm. In the particle filtering algorithm, the position of the particle and / or the particle is updated based on the observation index. In the particle filtering algorithm, the particle weight is determined by the distance between the particle and the first reference terminal. The first reference terminal is at least one reference terminal whose distance from the particle is less than a preset distance threshold. The observation metrics and reference metrics have the same dimensions, including at least one wireless performance metric.

[0102] Optionally, the determining module 130 is also used for: Step 1: Determine the terminal's primary location based on the observed indicators and the positioning fingerprint database; Step 2: Update the positions of particles and / or particles in the particle filtering algorithm using the first positions corresponding to multiple time points; Step 3: Update the particle weights of the updated particles based on the observed indicators; Step 4: Collect the latest observation indicators of the terminal in the wireless network, and repeat steps 1 to 3 until the preset conditions are met; Step 5: Determine the target position based on the particle position and corresponding particle weight of each particle.

[0103] Optionally, the determining module 130 is also used for: A first preset number of second reference terminals are determined from the reference terminals. The second reference terminals are the first preset number of reference terminals whose cosine similarity between the first vector composed of the corresponding reference indicators and the second vector composed of the observation indicators is the highest. Using cosine similarity as the weight, the positions of a first preset number of second reference terminals are summed to determine the first position of the terminal.

[0104] Optionally, the determining module 130 is also used for: Obtain at least one first reference terminal corresponding to the particle; Determine the first similarity between the first reference index corresponding to at least one first reference terminal and the observation index respectively. Each first similarity corresponds to a target weight, and the target weight is related to the distance between the corresponding first reference terminal and the particle. The second similarity is obtained by weighted summation of the first similarity based on the target weight; The particle weights are updated based on the second similarity.

[0105] Figure 7 This is a block diagram of another location positioning device provided in one embodiment of the present specification. At least one wireless performance indicator includes at least one of the following: received signal strength indication, time of arrival, time difference of arrival. The location positioning device 100 further includes: The fingerprint database construction module 140 is used for: Obtain reference indicators from multiple preset reference terminals; The reference indicators are associated with the locations of the corresponding reference terminals and stored in the database to obtain the location fingerprint database.

[0106] Optionally, the reference metric is the average of the wireless performance metrics obtained by each reference terminal at multiple times.

[0107] The device 100 provided in this application embodiment can execute the methods in the preceding method embodiments and realize the functions and beneficial effects of the methods in the preceding method embodiments, which will not be repeated here.

[0108] Figure 8 A block diagram of an environmental monitoring device provided in one embodiment of this specification, such as... Figure 8 As shown, the environmental monitoring device 200 includes: Monitoring module 210 is used to acquire environmental data reported by at least one reference terminal in the environment; The early warning module is used to determine the first target location of the terminal by employing the location positioning method of any embodiment of the first aspect when there is a security risk in the environmental data reported by any target reference terminal. The early warning module is also used to send security warnings to target terminals whose first target location is within the range corresponding to the target reference terminal.

[0109] Optionally, the reference terminal is a passive IoT terminal, and the monitoring module 210 is also used for: Periodically broadcast wake-up signals to wake up passive IoT terminals in the environment; Receive environmental data reported by passive IoT terminals.

[0110] Optionally, the environmental data includes the identifier of the reference terminal, and also includes at least one of gas concentration, temperature, and humidity. The monitoring module 210 is also used for: The environmental data is compared with a preset safety threshold range. If at least one piece of environmental data exceeds the safety threshold range, it is determined that the environmental data poses a safety risk.

[0111] The device 200 provided in this application embodiment can execute the methods in the preceding method embodiments and realize the functions and beneficial effects of the methods in the preceding method embodiments, which will not be repeated here.

[0112] Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this disclosure, such as... Figure 9 As shown, at the hardware level, the electronic device includes at least one processor, and optionally, an internal bus, a network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or it may also include non-volatile memory, such as at least one disk drive. Of course, the electronic device may also include other hardware required for other business operations.

[0113] The processor, network interface, and memory can be interconnected via an internal bus, which can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be categorized as an address bus, data bus, control bus, etc. For ease of illustration, only a single bidirectional arrow is used in this diagram, but this does not imply that there is only one bus or one type of bus.

[0114] Memory stores programs. Specifically, the program may include program code, which includes at least one computer operation instruction. Memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0115] At least one processor reads a corresponding computer program from non-volatile memory into memory and then runs it, forming a device for locating a target user at the logical level. At least one processor executes the program stored in memory and specifically performs the method disclosed in the embodiments shown in the first aspect or the second aspect, achieving the functions and beneficial effects of the methods described in the foregoing method embodiments, which will not be repeated here.

[0116] The methods disclosed in the embodiments shown in the first aspect of this disclosure can be applied to at least one processor, or implemented by at least one processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the hardware or by instructions in the form of software within at least one processor. The processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure can be implemented or executed. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0117] The electronic device can also execute the methods described in the preceding method embodiments and achieve the functions and beneficial effects of the methods described in the preceding method embodiments, which will not be repeated here.

[0118] Of course, in addition to software implementation, the electronic device disclosed herein does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0119] This disclosure also proposes a computer-readable storage medium that stores one or more programs, which, when executed by at least one processor, implement the methods disclosed in the embodiments of the first aspect or the second aspect and achieve the functions and beneficial effects of the methods described in the foregoing method embodiments, which will not be repeated here.

[0120] The computer-readable storage medium mentioned above includes read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc.

[0121] Furthermore, this disclosure also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions that, when executed by a computer, implement the following process: the method disclosed in the embodiment of the first aspect or the embodiment of the second aspect, and achieve the functions and beneficial effects of the methods described in the foregoing method embodiments, which will not be repeated here.

[0122] In summary, the above description is merely a preferred embodiment of this disclosure and does not limit the scope of protection of this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

[0123] The systems, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0124] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can store information accessible to a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0125] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0126] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

Claims

1. A method for location positioning, characterized in that, The method includes: Observational indicators of the data acquisition terminal in the wireless network; Obtain a pre-built location fingerprint database, which includes multiple preset reference indicators of reference terminals in the wireless network; The target position of the terminal is determined by a particle filtering algorithm. In the particle filtering algorithm, the position of the particles and / or the particle position is updated based on the observation index. The particle weight of the particles in the particle filtering algorithm is determined by the distance between the particles and the first reference terminal. The first reference terminal is at least one reference terminal whose distance from the particles is less than a preset distance threshold. The observation metrics and the reference metrics have the same dimension, including at least one wireless performance metric.

2. The method according to claim 1, characterized in that, The step of using a particle filter algorithm to determine the target location of the terminal includes: Step 1: Determine the first location of the terminal based on the observed indicators and the positioning fingerprint database; Step 2: Update the positions of particles and / or particles in the particle filtering algorithm using the first positions corresponding to multiple time points; Step 3: Update the particle weights of the updated particles according to the observed indicators; Step 4: Collect the latest observation indicators of the terminal in the wireless network, and repeat steps 1 to 3 until the preset conditions are met; Step 5: Determine the target position based on the particle position and corresponding particle weight of each particle.

3. The method according to claim 2, characterized in that, Determining the first location of the terminal based on the observed indicators and the positioning fingerprint database includes: A first preset number of second reference terminals are determined from the reference terminals. The second reference terminals are the first preset number of reference terminals whose cosine similarity between the first vector composed of the corresponding reference indicators and the second vector composed of the observation indicators is the highest. Using the cosine similarity as a weight, the positions of the first preset number of second reference terminals are weighted and summed to determine the first position of the terminal.

4. The method according to claim 2, characterized in that, The step of updating the particle weights of the updated particles based on the observed indicators includes: Obtain at least one first reference terminal corresponding to the particle; Determine the first similarity between the first reference index corresponding to the at least one first reference terminal and the observation index respectively, each first similarity corresponding to a target weight, the target weight being related to the distance between the corresponding first reference terminal and the particle; The second similarity is obtained by weighted summation of the first similarity based on the target weight; The particle weights of the particles are updated based on the second similarity.

5. The method according to any one of claims 1 to 4, characterized in that, The at least one wireless performance metric includes at least one of the following: received signal strength indication, time of arrival, and time difference of arrival; the method further includes: Obtain reference indicators of the plurality of preset reference terminals; The reference indicators are associated with the locations of the corresponding reference terminals and stored in the database to obtain the location fingerprint database.

6. The method according to claim 5, characterized in that, The reference metric is the average value of the wireless performance metric obtained by each reference terminal at multiple times.

7. A method for environmental monitoring, characterized in that, The method includes: Acquire environmental data reported by at least one reference terminal in the environment; If there is a security risk in the environmental data reported by any target reference terminal, the location positioning method as described in any one of claims 1 to 6 shall be used to determine the first target location of the terminal. A security warning is sent to the target terminal whose first target location is within the range corresponding to the target reference terminal.

8. The method according to claim 7, characterized in that, The reference terminal is a passive IoT terminal, and the acquisition of environmental data reported by at least one reference terminal in the environment includes: Periodically broadcast wake-up signals to wake up passive IoT terminals in the environment; Receive environmental data reported by the passive IoT terminal.

9. The method according to claim 7 or 8, characterized in that, The environmental data includes the identifier of the reference terminal, and also includes at least one of gas concentration, temperature, and humidity; the method further includes: The environmental data is compared with a preset safety threshold range. If at least one of the environmental data exceeds the safety threshold range, it is determined that the environmental data poses a security risk.

10. A positioning device, characterized in that, The device includes: The data acquisition module is used to collect observation indicators of the terminal in the wireless network; The acquisition module is used to acquire a pre-built location fingerprint database, which includes multiple preset reference indicators of reference terminals in the wireless network. The determination module is used to determine the target position of the terminal using a particle filtering algorithm. In the particle filtering algorithm, the position of the particle and / or the particle is updated based on the observation index. In the particle filtering algorithm, the particle weight is determined by the distance between the particle and the first reference terminal. The first reference terminal is at least one reference terminal whose distance from the particle is less than a preset distance threshold. The observation metrics and the reference metrics have the same dimension, including at least one wireless performance metric.

11. An environmental monitoring device, characterized in that, The device includes: The monitoring module is used to acquire environmental data reported by at least one reference terminal in the environment; The early warning module is used to determine the first target location of the terminal by using the location positioning method as described in any one of claims 1 to 6 when there is a security risk in the environmental data reported by any target reference terminal. The early warning module is also used to send a security warning to the target terminal within the range corresponding to the target reference terminal at the first target location.

12. An electronic device, characterized in that, Includes processor, memory, and communication bus; The communication bus is used to enable communication between the processor and the memory; The processor is configured to execute one or more programs stored in the memory to implement the steps of the location positioning method as described in any one of claims 1-6, or to implement the steps of the environmental monitoring method as described in any one of claims 7-9.

13. A computer storage medium, characterized in that, The computer storage medium stores one or more programs, which can be executed by one or more processors to implement the steps of the location positioning method as described in any one of claims 1-6, or the steps of the environmental monitoring method as described in any one of claims 7-9.

14. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions that, when executed by a computer, implement the steps of the location positioning method as described in any one of claims 1-6, or the steps of the environmental monitoring method as described in any one of claims 7-9.

Images