An RFID and Bluetooth fusion positioning method and system for material storage site navigation

Abstract

The application relates to the field of data fusion, in particular to an RFID and Bluetooth fusion positioning method and system for material storage site navigation, which acquires RFID tag information of target materials; according to the RFID tag information, a preset material storage area mapping relationship is inquired, according to the inquiry result, a target storage area where the target materials are located and target shelf coordinates where the target materials are located are determined; according to the determination result of the target storage area, a Bluetooth scanning instruction is generated; broadcast signals from at least three Bluetooth beacons in the target storage area are received, and signal strength parameters of the broadcast signals are analyzed; based on known position coordinates of the at least three Bluetooth beacons and the corresponding signal strength parameters, the current accurate coordinates of a mobile terminal are calculated through a positioning algorithm; according to the current accurate coordinates and the target shelf coordinates, a navigation path from the current position of the mobile terminal to the target shelf is generated and displayed in real time. The optimal navigation path is dynamically generated and displayed on a digital map, and intuitive visual guidance is provided for users.

Description

Technical Field

[0001] This application relates to the field of data fusion technology, and in particular to an RFID and Bluetooth fusion positioning method and system for material storage location navigation. Background Technology

[0002] In large-scale warehousing and logistics management, quickly and accurately locating materials and guiding personnel to their target storage locations is crucial for improving operational efficiency. Traditional indoor navigation and positioning technologies, such as Wi-Fi positioning, pure Bluetooth positioning, or pure RFID positioning, all have certain limitations in practical applications. Among them, RSSI (Received Signal Strength Indication) positioning technology based on Bluetooth beacons is widely used due to its moderate deployment cost and relatively high accuracy.

[0003] However, existing Bluetooth positioning solutions face significant challenges in complex warehouse environments. First, warehouses typically consist of multiple storage areas of varying sizes, layouts, and shelving densities. The physical dimensions of these areas differ greatly; large storage areas require Bluetooth scanning with a wider signal reception range to capture a sufficient number of beacons, while smaller areas do not. More importantly, the signal interference environment varies significantly across different storage areas. In areas with dense shelving and numerous metal items, Bluetooth signals experience severe multipath effects and attenuation, resulting in drastic signal strength fluctuations (i.e., large signal variance). Second, current common implementations use a fixed set of global scanning parameters (such as signal reception strength thresholds and scanning frequency) for the entire warehouse. This strategy struggles to achieve optimal performance in all scenarios and has inherent flaws. First, in large storage areas, the fixed threshold may be too strict, preventing the reception of long-range beacon signals and causing positioning failures. Second, in areas with dense beacons and strong interference, the fixed threshold may be too lenient, resulting in the reception of a large amount of noise and neighboring interference signals, leading to signal confusion, increased computational complexity, and ultimately reduced positioning accuracy and real-time performance.

[0004] Therefore, existing technologies have shortcomings and need to be improved. Summary of the Invention

[0005] In order to solve one or more problems in the prior art, the main objective of this application is to provide an RFID and Bluetooth fusion positioning method and system for material storage location navigation.

[0006] To achieve the aforementioned objectives, this application proposes an RFID and Bluetooth fusion positioning method for material storage location navigation, the method comprising:

[0007] Obtain RFID tag information of target materials;

[0008] Based on the RFID tag information, the pre-set material warehouse area mapping relationship is queried, and based on the query result, the target warehouse area where the target material is located and the coordinates of the target shelf where it is located are determined;

[0009] Based on the determination result of the target library area, a Bluetooth scanning command is generated;

[0010] Receive broadcast signals from at least three Bluetooth beacons within the target storage area, and parse the signal strength parameters of each broadcast signal;

[0011] Based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters, the current precise coordinates of the mobile terminal are calculated using a positioning algorithm.

[0012] Based on the current precise coordinates and the target shelf coordinates, a navigation path from the current location of the mobile terminal to the target shelf is generated and displayed in real time.

[0013] This application also provides an RFID and Bluetooth fusion positioning system for material storage location navigation, including:

[0014] The acquisition module is used to acquire the RFID tag information of the target materials;

[0015] The query module is used to query the preset material warehouse area mapping relationship based on the RFID tag information, and determine the target warehouse area where the target material is located and the coordinates of the target shelf based on the query results.

[0016] The first generation module is used to generate Bluetooth scanning instructions based on the determination result of the target library area;

[0017] The receiving module is used to receive broadcast signals from at least three Bluetooth beacons within the target storage area and to parse the signal strength parameters of each broadcast signal.

[0018] The calculation module is used to calculate the current precise coordinates of the mobile terminal based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters, using a positioning algorithm.

[0019] The second generation module is used to generate and display in real time the navigation path from the current location of the mobile terminal to the target shelf based on the current precise coordinates and the target shelf coordinates.

[0020] This application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0021] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0022] This application presents an RFID and Bluetooth fusion positioning method and system for material storage location navigation. The method, through the organic synergy of these two technologies, firstly utilizes the non-contact and rapid identification characteristics of RFID technology to accurately acquire the identity information of the target material, thereby determining its macro-level storage area and precise shelf coordinates, successfully solving the problems of navigation process initiation efficiency and destination guidance. Secondly, guided by the storage area information, the Bluetooth scanning module is intelligently triggered to operate within a specific area. By receiving multiple Bluetooth beacon signals within the area and analyzing their strength parameters, an advanced positioning algorithm is used to calculate the meter-level precise positioning of the mobile terminal, overcoming the shortcomings of insufficient accuracy in RFID positioning alone. Finally, based on the real-time updated current location and preset target shelf coordinates, the optimal navigation path is dynamically generated and displayed on a digital map, providing users with intuitive and real-time visual guidance. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating an embodiment of the RFID and Bluetooth fusion positioning method for material storage location navigation according to this application.

[0024] Figure 2 This is a flowchart illustrating an embodiment of the RFID and Bluetooth fusion positioning method for material storage location navigation according to this application.

[0025] Figure 3 This is a schematic block diagram of an embodiment of the RFID and Bluetooth fusion positioning system for material storage location navigation according to this application;

[0026] Figure 4 This is a schematic block diagram of the structure of a computer device according to an embodiment of this application.

[0027] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0029] Reference Figure 1 This application provides an RFID and Bluetooth fusion positioning method for material storage location navigation, the method comprising:

[0030] S1. Obtain the RFID tag information of the target material;

[0031] S2. Based on the RFID tag information, query the preset material warehouse area mapping relationship, and determine the target warehouse area where the target material is located and the coordinates of the target shelf it is located based on the query result.

[0032] S3. Generate a Bluetooth scanning command based on the determination result of the target library area;

[0033] S4. Receive broadcast signals from at least three Bluetooth beacons within the target storage area, and parse the signal strength parameters of each broadcast signal;

[0034] S5. Based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters, calculate the current precise coordinates of the mobile terminal using a positioning algorithm;

[0035] S6. Based on the current precise coordinates and the target shelf coordinates, generate and display in real time the navigation path from the current location of the mobile terminal to the target shelf.

[0036] As described in steps S1-S3 above, operators use mobile terminals (such as RFID handheld readers or industrial PDAs with built-in RFID modules) to approach or scan RFID tags attached to the target materials. The RFID reader activates the tag via radio waves and reads its stored unique electronic code (EPC) and other identification information. This achieves contactless, rapid, and automatic identification of materials. Compared to manually entering material numbers, this greatly improves the efficiency and accuracy of initial information acquisition, avoids human input errors, and serves as an efficient starting point for the entire navigation process. After receiving the RFID tag ID, the mobile terminal or backend server uses it as a key index to query a pre-set "material-location mapping database." This database records the association between each RFID tag ID and the current storage location of the material it is attached to. This location information includes at least two levels: first, a macroscopic storage area code (such as "Area A"), and second, precise shelf coordinates (such as coordinate values ​​(X,Y) or shelf number + shelf level). This is the key transformation from "finding the item" to "navigating to the location." It binds physical objects (materials) to precise coordinates in the information world, providing a clear target for subsequent precise positioning and path planning. Upon learning the target warehouse area, the system triggers control logic, sending a command to the Bluetooth module of the mobile terminal, instructing it to begin operation. This command may include scanning parameters (such as the adaptive parameters detailed in the dependent claims), and its core function is to control the timing of the Bluetooth module's activation. This demonstrates the guiding and triggering role of RFID on Bluetooth, representing one aspect of "convergence." It implements a strategy of on-demand activation and area-specific operation, avoiding continuous scanning of the Bluetooth module throughout the entire warehouse, thereby significantly reducing the power consumption of the mobile terminal and extending the device's battery life.

[0037] As described in steps S4-S6 above, the mobile terminal's Bluetooth module listens for radio signals periodically broadcast by Bluetooth beacons within the target storage area. Each beacon's signal contains its unique ID (e.g., UUID). After receiving the signal, the terminal measures its Received Signal Strength Indication (RSSI), the value of which is related to the distance between the terminal and the beacon (the closer the distance, the stronger the signal). Raw data is collected for accurate positioning. By limiting the location to the "target storage area," Bluetooth signal interference from other irrelevant storage areas is effectively filtered out, reducing the amount of data computation and laying the foundation for subsequent improvements in positioning accuracy and speed. After the positioning engine (which can run on the terminal or server) obtains the known physical coordinates and corresponding RSSI values ​​of multiple (≥3) beacons, it uses a specific positioning algorithm (e.g., triangulation or fingerprint positioning) for calculation. Triangulation estimates the distance using RSSI and then calculates the coordinates by geometrically determining the intersection point; fingerprint positioning matches the real-time RSSI with a pre-collected "location-signal" database. The key to overcoming the insufficient accuracy of RFID positioning lies in narrowing down the user's location from "a certain warehouse area" to "a specific point within the warehouse area," providing an accurate current location for ultimately achieving shelf-level navigation. After acquiring the current location (S5 output) and destination location (S2 output), the path planning engine calculates an optimal walking path based on pre-stored warehouse electronic map information (including vector data of aisles, shelves, obstacles, etc.). The mobile terminal APP then overlays this path onto the warehouse floor plan, updating in real time as the user moves (current location updates). This provides intuitive, real-time visual navigation guidance. It transforms abstract coordinate data into graphical instructions that are easy for users to understand, greatly reducing the difficulty of finding a way and the reliance on human experience, and significantly improving the efficiency of material retrieval and picking.

[0038] As described above, the provided RFID and Bluetooth fusion positioning method for material storage location navigation, through the organic synergy of the two technologies, firstly utilizes the non-contact and rapid identification characteristics of RFID technology to accurately obtain the identity information of the target material, and based on this, determines its macro-level storage area and precise shelf coordinates, successfully solving the problems of navigation process initiation efficiency and destination guidance. Then, guided by the storage area information, the Bluetooth scanning module is intelligently triggered to operate within a specific area. By receiving multiple Bluetooth beacon signals within the area and analyzing their strength parameters, an advanced positioning algorithm is used to calculate the meter-level precise positioning of the mobile terminal, overcoming the shortcomings of insufficient positioning accuracy of RFID alone. Finally, based on the real-time updated current location and preset target shelf coordinates, the optimal navigation path is dynamically generated and displayed on a digital map, providing users with intuitive and real-time visual guidance.

[0039] Reference Figure 2In one embodiment, prior to the step of receiving broadcast signals from at least three Bluetooth beacons within the target storage area, the method further includes:

[0040] S41. Based on the identification information of the target storage area, obtain its corresponding preset environmental parameters and range parameters, wherein the environmental parameters include the Bluetooth beacon deployment density and historical signal strength variance in the storage area, and the range parameters include the geometric center coordinates and area of ​​the storage area.

[0041] S42. Calculate the initial signal reception strength threshold and scanning frequency based on the range parameters;

[0042] S43. Correct the initial signal reception strength threshold and scanning frequency according to the environmental parameters to determine the final Bluetooth scanning parameters;

[0043] S44. Perform a Bluetooth scan and filter the received broadcast signals according to the determined final Bluetooth scan parameters.

[0044] As described above, after identifying the target storage area via RFID, the system does not immediately begin Bluetooth scanning. Instead, it first uses the unique identifier of the storage area (e.g., "Area A") as a key to retrieve the unique environmental and geographical attributes of that area from a pre-set parameter database. The center coordinates are used as a reference for subsequent possible positioning calculations, and the area is the direct basis for determining the size of the space. Large storage areas require wider signal coverage, while small storage areas do the opposite; this is the foundation for adjusting the scanning strategy. Environmental parameters (beacon deployment density, historical signal strength variance): define the signal environment complexity of the storage area. Deployment density: High density means numerous beacons per unit area, complex signal sources, and a high risk of mutual interference. Historical signal strength variance: A large value indicates severe signal fluctuations in the area (possibly due to multipath effects such as metal shelves and personnel movement), resulting in poor signal stability. Different storage areas not only differ in size but also in their "signal topography," requiring differentiated treatment. This achieves a shift from "blind scanning" to "knowing before acting." It provides precise data input for subsequent intelligent parameter adjustments and is the cornerstone of the entire adaptive scanning strategy. The system calculates the initial RSSI threshold and scan frequency based on the reservoir area. The relationship between the threshold and area is as follows: the larger the reservoir area, the lower the initial threshold is set. A lower threshold means a lower reception threshold, allowing the system to "hear" beacons from further away (with weaker signals), thus meeting the need for wider coverage in large spaces. A larger reservoir area also results in a lower initial scan frequency (i.e., a longer scan interval). Larger scans take longer, so the frequency needs to be appropriately reduced to avoid overloading the RF front-end and causing a surge in power consumption. A basic scanning strategy based on geographic size is provided, ensuring sufficient beacons are found in large reservoir areas and avoiding over-scanning in small areas, achieving initial optimization. The system fine-tunes these initial values ​​using environmental parameters to generate the final scan parameters best suited to the current reservoir environment. If the density is high, the final RSSI threshold is increased. In high-density areas, numerous beacons and strong nearby beacons are sufficient for positioning. Increasing the threshold can filter out a large number of weak signals from long distances and interference signals caused by reflection and diffraction, significantly reducing data noise, avoiding signal confusion, and improving positioning accuracy and calculation speed. Historical signal strength variance correction: If the variance is large (signal instability), the final scan frequency is increased. In environments with severe signal fluctuations, the reliability of RSSI values ​​acquired in a single scan is low. By increasing the scan frequency, multiple samplings can be performed, and fluctuations can be smoothed through averaging or filtering algorithms to obtain more stable and reliable signal data, improving positioning stability. Secondary optimization based on the signal environment is achieved. It solves the signal interference and stability problems that "range parameters" cannot address, enabling the scan parameters to dynamically adapt to the "signal terrain" of different reservoir areas. The Bluetooth module of the mobile terminal no longer uses the default fixed parameters, but operates according to the "final Bluetooth scan parameters" calculated in the above steps.During or after scanning, the received broadcast signals are filtered directly based on a set final signal reception strength threshold, retaining only signals with strengths above the threshold for subsequent calculations. This filtering process eliminates most unreliable interference signals, resulting in higher-quality data input to the positioning algorithm. The amount of data to be processed is reduced, leading to faster positioning calculations. Ineffective signal reception and processing are avoided, and a reasonable scanning frequency setting prevents excessive workload on the radio frequency module.

[0045] In one embodiment, the step of performing Bluetooth scanning and filtering of received broadcast signals includes:

[0046] The parsed signal strength parameters are compared and analyzed with the final signal reception strength threshold.

[0047] Based on the comparative analysis results, the broadcast signals of the three Bluetooth beacons with the strongest signal strength parameters are selected for subsequent positioning coordinate calculation; and / or, the broadcast signals of Bluetooth beacons with signal strength parameters lower than the threshold are discarded.

[0048] As described above, after the Bluetooth module scans and receives a series of Bluetooth beacon broadcast signals according to the determined "final Bluetooth scanning parameters," the system parses the strength parameter (RSSI value) of each signal. Subsequently, the system compares each parsed RSSI value with the calculated final signal reception strength threshold. This is a judgment process aimed at performing a preliminary, strength-based "quality sorting" of all received signals. An objective, quantitative standard (i.e., the threshold calculated adaptively by the environment) is provided to classify all signals into two categories: "potentially useful signals" and "signaled noise," preparing for subsequent precise screening. Based on the comparative analysis results, the broadcast signals of the three Bluetooth beacons with the strongest signal strength parameters are selected for subsequent location coordinate calculation; and / or, broadcast signals of Bluetooth beacons with signal strength parameters below the threshold are discarded. This is a step involving two parallel or optional strategies. Strategy 1: The system sorts all received signals in descending order of their signal strength parameters. Regardless of the number of signals received, it only locks the three with the highest strength values ​​and outputs the IDs and RSSI values ​​of these three beacons to the positioning algorithm for calculation. The reason for setting "three" is determined by the mathematical principles of Bluetooth triangulation. In a two-dimensional plane, to calculate the coordinates of a unique point, distance information from at least three reference points is required. Choosing the three strongest points means selecting the three closest and most reliable beacons to the mobile terminal. The signals from the three closest beacons are least affected by environmental interference such as multipath reflection and obstacle obstruction, providing distance information closest to the true value, thus enabling the calculation of more accurate position coordinates. Forcing the use of the three strongest points directly excludes all other weaker or potentially interfering signals, ensuring the purity of the data input to the positioning algorithm from the data source. Regardless of the number of beacons in the environment, the positioning algorithm processes only the data from three signals each time, keeping computational resource consumption constant and ensuring the real-time performance and response speed of the positioning calculation. Strategy Two: The system directly discards all signals that are below the final signal reception strength threshold after comparison. These signals are no longer involved in any subsequent processing. This is the most direct noise filtering method. These weak signals are likely from distant reservoirs or signals that have undergone severe attenuation and reflection, and their RSSI values ​​are extremely unreliable. Discarding them greatly reduces the amount of invalid data processed, reduces the CPU computational burden, thereby reducing power consumption and speeding up system processing. Synergy with Strategy 1: This strategy can work in conjunction with Strategy 1. First, it quickly filters out a large amount of noise by "discarding signals below a threshold," and then "selects the three strongest signals" from the remaining high-quality signals, forming a two-stage filtering mechanism that balances efficiency and accuracy.

[0049] In one embodiment, after the step of generating a Bluetooth scanning command based on the determination result of the target library area, the method further includes:

[0050] If the Bluetooth scanning command fails to receive signals from at least three Bluetooth beacons or the calculation fails, a downgrade processing strategy will be implemented.

[0051] As described above, a trigger mechanism for an exception handling process is defined. During the Bluetooth precise positioning phase, the system continuously monitors the status of two key nodes: Signal reception phase: The Bluetooth module scans according to instructions, but fails to detect broadcast signals from at least three Bluetooth beacons within a preset timeout period. Data calculation phase: Although three or more signals are received, the positioning algorithm cannot output a valid coordinate result due to extremely poor signal quality, low strength, or severe interference (e.g., all signals' RSSI values ​​are far below a reasonable range, or the coordinates calculated by triangulation are significantly beyond the physically possible range). Once the system detects any of these situations, it determines that the Bluetooth precise positioning process has failed and triggers the subsequent degradation handling strategy. This trigger condition clarifies the precise criteria for the system to switch from "normal mode" to "degraded mode," reflecting the system's integrity and self-diagnostic capabilities. It ensures that the system can promptly identify positioning failures, rather than continuously attempting or returning an erroneous and meaningless result, providing a prerequisite for subsequent graceful degradation. The "degraded handling strategy" refers to a pre-designed backup plan activated when the primary function (Bluetooth precise positioning) fails. Its core idea is to provide the best possible valuable service under the current conditions when high-precision services are unavailable. This ensures basic system availability and prevents the system from being completely paralyzed due to the failure of a local technology (Bluetooth positioning). Instead, it can still rely on previously successful RFID positioning results to provide crucial location information and guide users, rather than simply reporting a "positioning failure" error.

[0052] In one embodiment, the steps of executing the degradation processing strategy include:

[0053] Maintain and output the target warehouse area information last determined by RFID positioning;

[0054] On the displayed warehouse floor plan, the location of the mobile terminal is blurred and shown in the geometric center area or main passage of the target warehouse area;

[0055] Based on the target warehouse area information and warehouse layout data, generate one or more inferred navigation paths;

[0056] Based on the inferred navigation path, a prompt message is generated to indicate that the user has entered an area with poor Bluetooth signal coverage and suggests referring to the inferred path for address finding.

[0057] As mentioned above, when the system determines that Bluetooth positioning has failed, i.e., the "target storage area" information previously successfully obtained and identified by RFID scanning, the system continuously displays this crucial information to the user on the UI interface (such as the APP screen) in the form of text, voice, or a prominent icon (e.g., "Current Target: Area A"). In a fault state, this ensures that the user is not completely "out of contact" and always knows their macroscopic operating area, providing crucial context for subsequent manual location finding. This demonstrates the robustness and practicality of the system design, gracefully downgrading the function from "precise navigation" to "area guidance." The system intelligently switches the way the user's current location is presented on the electronic map. Since precise coordinates are unavailable, it no longer displays a specific "point," but instead highlights an area (such as a circular coverage area) or a passage (such as a highlighted line segment) based on the target storage area's preset geographical information, placing the user's icon within this area. Accurately conveying uncertainty: Using a "fuzzy display," the system scientifically and intuitively reveals the true state of the current location accuracy to the user ("You are roughly in this area"), avoiding the serious misleading effect of displaying an incorrectly precise point. Route planning is based on still available data—the geographical boundaries of the target warehouse area and vector map data of warehouse aisles. Since the starting point (the user's current location) is uncertain, a path to the target shelf is planned starting from the warehouse entrance or center. Multiple possible paths covering the main aisles of the warehouse area are generated. This provides the highest value decision support when real-time navigation is unavailable. It shifts the user's attention from "my precise location" to "how do I get to the target," providing clear action suggestions and directional guidance for user self-location, greatly improving operational efficiency in degraded mode. An automatic message combining status prompts and operation guidelines (e.g., "Warning: Weak signal, location may be inaccurate. You are currently in area A. We suggest you first proceed east along the main aisle, then refer to the map path on the right.") is announced to the user via screen or voice.

[0058] In one embodiment, the step of generating one or more inferred navigation paths based on the target warehouse area information and warehouse layout data includes:

[0059] Obtain the first accurate positioning coordinates successfully calculated by the Bluetooth positioning algorithm before Bluetooth positioning fails;

[0060] The optimal path between the first precise positioning coordinates and the entrance of all walkable passages within the target storage area is determined as the first type of inferred path;

[0061] Determine the theoretically optimal path between the first precise positioning coordinates and the target shelf coordinates, as the second type of inferred path;

[0062] Based on the generated first-type and second-type speculative paths, they are displayed on the warehouse floor plan in a style different from the real-time navigation path.

[0063] As mentioned above, the system continuously caches the most recently successfully located and reliable coordinates calculated via Bluetooth in memory or logs. When a degradation condition is triggered, the system does not start from scratch, but first retrieves and calls this last known good location. This coordinate point serves as the sole reliable physical starting point for all subsequent inferred path calculations. This step is the logical foundation and value premise for the entire inferred path generation. It ensures that the inference is not aimless guessing, but is deduced based on a previously accurate and physically reliable anchor point. This greatly improves the rationality and reference value of the inferred path, avoiding complete misleading results caused by using a location that the user may never have reached as the starting point. The system calculates the shortest or optimal path from the "last known good coordinates" to all main entrances of the target storage area (usually 1-3 main entrances). This is a conservative but extremely reliable strategy. Its implicit logic is to guide the user to first move safely and unambiguously to a known and easily found "landmark" location (storage area entrance). Regardless of where the user is in the storage area at the time, guiding them to the main road or entrance is almost always feasible and easy to execute. Once a user reaches the warehouse entrance, their location is clear even without restored Bluetooth positioning. Finding the target shelf based on internal warehouse signage is significantly easier. The strategy cleverly avoids the difficulties of route planning in areas with poor signal coverage, providing the most reliable fallback solution. The system ignores the current signal failure state, assuming an ideal environment, and directly calculates the shortest path from the "last known precise coordinates" to the "target shelf coordinates" based on map data. This provides the user with the theoretically fastest route. If the signal interruption is temporary (e.g., passing through a signal blind spot), the user is likely to quickly regain positioning and receive continuous guidance by following this path. For operators familiar with the warehouse layout, this path provides the most direct action reference; they can combine their own judgment, ignore potentially non-existent obstacles, and quickly approach the target. The system offers both conservative and optimistic options, covering the needs of different user preferences and different site conditions, demonstrating the flexibility of the solution. The generated multiple hypothetical paths are plotted on an electronic map, but must use different visual styles, such as using dashed lines instead of solid lines, and using a different color (e.g., gray or blue) instead of the green or red of the navigation path. Reduce the transparency of the route. A differentiated display method clearly indicates to users that this route is speculative, for reference only, and not real-time precise navigation. This prevents users from mistakenly believing that system functionality has been fully restored and blindly following it.

[0064] In one embodiment, after the step of generating and displaying in real time the navigation path from the current location of the mobile terminal to the target shelf, the method further includes:

[0065] Continuously monitor the deviation between the current precise coordinates and the pre-planned path;

[0066] If the deviation continues to exceed the preset threshold for a predetermined time, it is determined that there is a dynamic obstacle on the path;

[0067] Based on the results of the judgment, path generation is performed again to plan a new path that avoids obstacles between the current location and the target shelf coordinates.

[0068] As described above, during the user's journey along the pre-planned path, a monitoring process continuously runs in the system background. It periodically acquires the latest accurate coordinates calculated by Bluetooth positioning and calculates the shortest vertical distance (i.e., deviation) from that point to the pre-planned path. This calculation is typically based on geometric algorithms (such as the distance formula from a point to a line segment). This enables real-time, quantitative monitoring of whether the user has "gone astray." This is the data foundation for dynamic path replanning. Through continuous monitoring, the system can promptly detect anomalies, rather than waiting until the user is completely disoriented. If the deviation continues to exceed a preset threshold for a predetermined time, a decision is made. This is an intelligent logic with dual judgment conditions, designed to distinguish between "active deviation" and "passive obstruction." The preset threshold sets a reasonable distance tolerance (e.g., 1.5 meters). Briefly exceeding this threshold (e.g., due to slight fluctuations in the positioning signal or the user briefly detouring) will not trigger a judgment. The predetermined time sets a time window (e.g., 5 consecutive seconds). Only when the deviation continues to exceed the threshold for this duration will the system make a final judgment. The inherent error in positioning accuracy (signal fluctuations causing coordinates to fluctuate within a small range) also plays a role. The user actively and briefly takes a reasonable detour (e.g., to avoid oncoming pedestrians). Ultimately, the system infers that the user did not intentionally deviate, but rather that dynamic obstacles (such as temporarily parked forklifts or stacked goods) prevented them from passing through the pre-planned path. This avoids frequent and unnecessary path replanning caused by positioning noise or normal user behavior, ensuring system stability and user experience. Only when a continuous anomaly is detected is it determined that the environment has changed (obstacles exist), ensuring reliable decision-making. Once a dynamic obstacle is detected, the system immediately initiates real-time path replanning. The path planning engine will: use the user's latest current location as the starting point; use the original target shelf coordinates as the ending point; mark the sections of the initially planned path that were determined to be "obstructed" as temporarily impassable areas; invoke the path planning algorithm to search for a new optimal path in the warehouse map data that can bypass the temporary obstacle area; then, the system will replace the original pre-planned path with this new path and immediately update the display on the terminal interface, guiding the user to the new route. This allows the system to evolve from "static navigation" to "dynamic navigation," enabling it to cope with unexpected and unpredictable situations in real-world environments and ensuring the ultimate reachability of navigation tasks.

[0069] Reference Figure 3 This application also provides an RFID and Bluetooth fusion positioning system for material storage location navigation, including:

[0070] Module 1 is used to acquire RFID tag information of the target material;

[0071] The query module 2 is used to query the preset material warehouse area mapping relationship based on the RFID tag information, and determine the target warehouse area where the target material is located and the coordinates of the target shelf based on the query result.

[0072] The first generation module 3 is used to generate a Bluetooth scanning command based on the determination result of the target library area;

[0073] The receiving module 4 is used to receive broadcast signals from at least three Bluetooth beacons within the target storage area and to parse the signal strength parameters of each broadcast signal.

[0074] Calculation module 5 is used to calculate the current precise coordinates of the mobile terminal based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters, using a positioning algorithm.

[0075] The second generation module 6 is used to generate and display in real time a navigation path from the current location of the mobile terminal to the target shelf based on the current precise coordinates and the target shelf coordinates.

[0076] As described above, it is understood that each component of the RFID and Bluetooth fusion positioning system for material storage location navigation proposed in this application can realize the function of any of the RFID and Bluetooth fusion positioning methods for material storage location navigation described above, and the specific structure will not be repeated.

[0077] Reference Figure 4 This application also provides a computer device, which may be a server, and its internal structure may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores monitoring data and other data. The network interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements an RFID and Bluetooth fusion positioning method for material storage location navigation.

[0078] The processor described above executes the RFID and Bluetooth fusion positioning method for material storage location navigation, including: acquiring RFID tag information of the target material; querying a preset material storage area mapping relationship based on the RFID tag information, and determining the target storage area where the target material is located and the coordinates of the target shelf based on the query result; generating a Bluetooth scanning command based on the determination result of the target storage area; receiving broadcast signals from at least three Bluetooth beacons in the target storage area and parsing the signal strength parameters of each broadcast signal; calculating the current precise coordinates of the mobile terminal based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters using a positioning algorithm; and generating and displaying in real time a navigation path from the current location of the mobile terminal to the target shelf based on the current precise coordinates and the target shelf coordinates.

[0079] One embodiment of this application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements an RFID and Bluetooth fusion positioning method for material storage location navigation, including the following steps: acquiring RFID tag information of a target material; querying a preset material storage area mapping relationship based on the RFID tag information, and determining the target storage area where the target material is located and the coordinates of the target shelf based on the query result; generating a Bluetooth scanning command based on the determination result of the target storage area; receiving broadcast signals from at least three Bluetooth beacons in the target storage area and parsing the signal strength parameters of each broadcast signal; calculating the current precise coordinates of a mobile terminal based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters using a positioning algorithm; and generating and displaying in real time a navigation path from the current location of the mobile terminal to the target shelf based on the current precise coordinates and the target shelf coordinates.

[0080] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media provided in this application and in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0081] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method 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, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0082] The above description is only a preferred embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural changes made based on the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A fusion positioning method using RFID and Bluetooth for material storage location navigation, characterized in that, The method includes: Obtain RFID tag information of target materials; Based on the RFID tag information, the pre-set material warehouse area mapping relationship is queried, and based on the query result, the target warehouse area where the target material is located and the coordinates of the target shelf where it is located are determined; Based on the determination result of the target library area, a Bluetooth scanning command is generated; Receive broadcast signals from at least three Bluetooth beacons within the target storage area, and parse the signal strength parameters of each broadcast signal; Based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters, the current precise coordinates of the mobile terminal are calculated using a positioning algorithm. Based on the current precise coordinates and the target shelf coordinates, a navigation path from the current location of the mobile terminal to the target shelf is generated and displayed in real time. Prior to the step of receiving broadcast signals from at least three Bluetooth beacons within the target storage area, the method further includes: Based on the identification information of the target storage area, obtain its corresponding preset environmental parameters and range parameters. The environmental parameters include the Bluetooth beacon deployment density and historical signal strength variance within the storage area, and the range parameters include the geometric center coordinates and area of ​​the storage area. The initial signal reception strength threshold and scanning frequency are calculated based on the range parameters. The initial signal reception strength threshold and scanning frequency are corrected based on the environmental parameters to determine the final Bluetooth scanning parameters; Based on the determined final Bluetooth scanning parameters, perform a Bluetooth scan and filter the received broadcast signals.

2. The RFID and Bluetooth fusion positioning method for material storage location navigation according to claim 1, characterized in that, The steps of performing Bluetooth scanning and filtering the received broadcast signals include: The parsed signal strength parameters are compared and analyzed with the final signal reception strength threshold. Based on the comparative analysis results, the broadcast signals of the three Bluetooth beacons with the strongest signal strength parameters are selected for subsequent positioning coordinate calculation; and / or, the broadcast signals of Bluetooth beacons with signal strength parameters lower than the threshold are discarded.

3. The RFID and Bluetooth fusion positioning method for material storage location navigation according to claim 1, characterized in that, After the step of generating a Bluetooth scanning command based on the determination result of the target library area, the method further includes: If the Bluetooth scanning command fails to receive signals from at least three Bluetooth beacons or the calculation fails, a downgrade processing strategy will be implemented.

4. The RFID and Bluetooth fusion positioning method for material storage location navigation according to claim 3, characterized in that, The steps for implementing the degradation processing strategy include: Maintain and output the target warehouse area information last determined by RFID positioning; On the displayed warehouse floor plan, the location of the mobile terminal is blurred and shown in the geometric center area or main passage of the target warehouse area; Based on the target warehouse area information and warehouse layout data, generate one or more inferred navigation paths; Based on the inferred navigation path, a prompt message is generated to indicate that the user has entered an area with poor Bluetooth signal coverage and suggests referring to the inferred navigation path for address finding.

5. The RFID and Bluetooth fusion positioning method for material storage location navigation according to claim 4, characterized in that, The step of generating one or more inferred navigation paths based on the target warehouse area information and warehouse layout data includes: Obtain the first accurate positioning coordinates successfully calculated by the Bluetooth positioning algorithm before Bluetooth positioning fails; The optimal path between the first precise positioning coordinates and the entrance of all walkable passages within the target storage area is determined as the first type of inferred path; Determine the theoretically optimal path between the first precise positioning coordinates and the target shelf coordinates, as the second type of inferred path; Based on the generated first-type and second-type speculative paths, they are displayed on the warehouse floor plan in a style different from the real-time navigation path.

6. The RFID and Bluetooth fusion positioning method for material storage location navigation according to claim 1, characterized in that, After the step of generating and displaying in real time the navigation path from the current location of the mobile terminal to the target shelf, the method further includes: Continuously monitor the deviation between the current precise coordinates and the pre-planned path; If the deviation continues to exceed the preset threshold for a predetermined time, it is determined that there is a dynamic obstacle on the path; Based on the results of the judgment, path generation is performed again to plan a new path that avoids obstacles between the current location and the target shelf coordinates.

7. An RFID and Bluetooth fusion positioning system for material storage location navigation, used to execute an RFID and Bluetooth fusion positioning method for material storage location navigation as described in any one of claims 1 to 6, characterized in that, include: The acquisition module is used to acquire the RFID tag information of the target materials; The query module is used to query the preset material warehouse area mapping relationship based on the RFID tag information, and determine the target warehouse area where the target material is located and the coordinates of the target shelf based on the query results. The first generation module is used to generate Bluetooth scanning instructions based on the determination result of the target library area; The receiving module is used to receive broadcast signals from at least three Bluetooth beacons within the target storage area and to parse the signal strength parameters of each broadcast signal. The calculation module is used to calculate the current precise coordinates of the mobile terminal based on the known location coordinates of the at least three Bluetooth beacons and their corresponding signal strength parameters, using a positioning algorithm. The second generation module is used to generate and display in real time the navigation path from the current location of the mobile terminal to the target shelf based on the current precise coordinates and the target shelf coordinates.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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