A hospital equipment positioning and tracking method based on a medical internet of things terminal

Abstract

The present application relates to the technical field of equipment management tracking, and discloses a hospital equipment positioning tracking method based on a medical Internet of Things terminal. The present application realizes optimal balance between positioning accuracy and power consumption by means of dynamic scheduling of positioning resources driven by management events, so that the positioning accuracy and refresh frequency are upgraded or downgraded in real time according to the equipment management state. The two-stage early warning mechanism of trajectory semantic intention prediction and residence duration confirmation moves the abnormal early warning to before the equipment enters the forbidden area, and takes into account the timeliness of response and the accuracy of alarm. The barometer and landmark beacon double-checking effectively eliminates the cross-floor false alarm. Combined with secondary identity verification and usage duration statistics, the present application guarantees the safe management and control of equipment information and provides data support for procurement decisions, and comprehensively improves the real-time performance, reliability and management automation level of hospital equipment positioning tracking.

Description

Technical Field

[0001] This invention relates to the field of equipment management and tracking technology, and in particular to a method for locating and tracking in-hospital equipment based on a medical Internet of Things (IoT) terminal. Background Technology

[0002] With the rapid development of medical IoT technology, the location tracking of medical equipment within hospitals has become an important means of refined equipment management. Existing hospital equipment location tracking systems typically use a unified positioning technology to collect the location of all devices. The positioning refresh frequency and wake-up strategy are statically configured once during equipment deployment, which cannot adapt to the time-varying needs of equipment management. For critical emergency equipment such as ventilators and defibrillators, a unified low-frequency positioning cannot meet the real-time tracking requirements in resuscitation scenarios; while for conventional equipment such as infusion pumps and electrocardiographs, a unified high-frequency positioning leads to rapid tag battery depletion and excessive system power consumption, resulting in a serious mismatch between positioning resources and equipment management needs.

[0003] Meanwhile, existing positioning systems only output positioning results in coordinate form, creating a gap between positioning data and equipment management decisions. Managers need to manually observe the coordinates and determine whether the equipment is idle or has mistakenly entered an unauthorized area, resulting in a delayed response and reliance on human experience. Furthermore, existing systems rely heavily on wireless signal penetration or single barometer criteria for floor determination, making them susceptible to wall reflections and environmental pressure fluctuations, leading to false alarms across floors. When equipment enters non-medical areas such as waste rooms, existing systems only detect it after it has actually entered, failing to provide early warnings before the equipment enters restricted areas, resulting in a delayed window for theft prevention and accidental loss handling.

[0004] Therefore, how to improve the real-time performance of equipment location tracking and the level of automation in management decision-making has become a problem to be solved. Summary of the Invention

[0005] This invention provides a method for locating and tracking equipment within hospitals based on medical IoT terminals. Its main purpose is to solve the problems of mismatch between location resources and equipment management needs, and delayed abnormal early warning in the location and tracking of equipment within hospitals.

[0006] To achieve the above objectives, the present invention provides a method for locating and tracking in-hospital equipment based on a medical Internet of Things terminal, comprising: S1, acquiring equipment management attribute information and real-time management events of each medical device in the hospital, constructing an equipment management state machine, and obtaining the equipment management status of each medical device.

[0007] S2. Configure the positioning and acquisition strategy based on the device management status, and collect positioning signal data to obtain the real-time location coordinates of each medical device.

[0008] S3. Based on the real-time location coordinates of each medical device, perform map constraint correction and floor / room affiliation determination to obtain the corrected device location information.

[0009] S4. Based on the corrected device location information, generate trajectory intention prediction results, then generate advance warning instructions and confirmation warning instructions, and transmit the confirmation warning instructions to the device management state machine.

[0010] S5. Obtain the device search request and the identity card information of the search initiator. Verify the permissions of the identity card information of the search initiator. If the verification is successful, generate the device search scheduling result.

[0011] In a preferred embodiment, the step of acquiring the equipment management attribute information and real-time management events of each medical device in the hospital, constructing an equipment management state machine, and obtaining the equipment management status of each medical device includes: S201, acquiring equipment management attribute information, which includes equipment identification, emergency response timeliness score, mobility frequency score, and asset control level score.

[0012] S202, Obtain real-time management events, including equipment usage registration events, usage end events, emergency call events, emergency end events, warning trigger events, and warning cancellation events.

[0013] S203. Initialize the equipment management status of each medical device based on the equipment management attribute information, and construct the equipment management state machine. The equipment management status includes normal state, standby state, use state, emergency state and early warning state.

[0014] S204, based on real-time management events, drives the device management state machine to perform state transitions through state transition functions to obtain the device management status of each medical device.

[0015] In a preferred embodiment, the step of configuring a positioning acquisition strategy based on the device management status and acquiring positioning signal data includes: S301, determining the positioning mode, positioning refresh frequency, and wake-up strategy corresponding to each medical device according to the device management status through a positioning strategy mapping function to obtain the positioning acquisition strategy; the positioning strategy mapping function includes: when the device management status is in emergency state, the positioning mode is ultra-wideband time difference of arrival mode, and the positioning refresh frequency is 10 times per second; when the device management status is in use state, the positioning mode is Bluetooth angle of arrival mode, and the positioning refresh frequency is once every 2 seconds; when the device management status is in normal state, the positioning mode is Bluetooth signal strength mode, and the positioning refresh frequency is once every 5 minutes; when the device management status is in standby state, the device tag enters deep sleep, and the positioning refresh frequency is once every 10 minutes; when the device management status is in warning state, the positioning mode is ultra-wideband time difference of arrival mode, the positioning refresh frequency is 10 times per second, and the wake-up strategy is continuous locking packet transmission; the positioning mode also includes ultra-high frequency radio frequency identification access control mode.

[0016] S302 collects positioning signal data of each medical device based on the wake-up strategy and positioning refresh frequency; among them, the UHF RFID access control mode is passively triggered by the access control reader when the device tag passes through the reading range, and is not constrained by the positioning refresh frequency and wake-up strategy.

[0017] In a preferred embodiment, obtaining the real-time location coordinates of each medical device includes: S401, performing location analysis based on the positioning signal data using a location analysis method corresponding to the positioning mode to obtain the real-time location coordinates of each medical device; the location analysis method includes at least one of location analysis based on time difference of arrival measurement, location analysis based on angle of arrival measurement, and location analysis based on signal strength measurement; wherein the UHF RFID access control mode only records the discrete location points when the device passes through the access control and does not participate in continuous location analysis.

[0018] S402, When the device management state changes, the positioning strategy mapping function is re-executed to update the positioning acquisition strategy.

[0019] In a preferred embodiment, the step of performing map constraint correction and floor / room affiliation determination based on the real-time location coordinates of each medical device to obtain the corrected device location information includes: S501, acquiring the rasterized map of the hospital building information model, landmark beacon signals, and barometer data.

[0020] S502 performs Kalman filtering on the real-time position coordinates to obtain the filtered position coordinates and velocity estimates.

[0021] S503, based on the rasterized map of the building information model, applies validity constraints to the filtered location coordinates, removes invalid location points that fall inside the walls or unreachable partitions, and obtains the constrained location coordinates.

[0022] S504, the floor and room assignment determination is based on a dual verification of landmark beacon signals and barometer data to obtain the floor and room assignment result; wherein the floor and room assignment determination includes: obtaining the room assignment result by room adsorption based on landmark beacon signals, calculating the air pressure height difference based on barometer data and triggering floor switching only when the absolute value of the air pressure height difference is greater than a preset floor switching threshold to obtain the floor assignment result, and verifying the room assignment result with the floor assignment result to obtain the floor and room assignment result.

[0023] S505 combines the constrained position coordinates, velocity estimates, and floor / room assignment results to obtain the corrected equipment location information; the corrected equipment location information includes corrected coordinates, velocity estimates, floor identifiers, and room identifiers.

[0024] In a preferred embodiment, generating trajectory intention prediction results based on the corrected device location information includes: S601, acquiring building space label data, the building space label data including the area type of each area, the area type including normal medical area, corridor, sewage room and non-medical area.

[0025] S602, based on the corrected coordinates and velocity estimation in the corrected equipment position information, extrapolate the trajectory of the equipment's future position to obtain the predicted position coordinates.

[0026] S603, determine the region type of the area into which the predicted position coordinates fall, and obtain the trajectory intention prediction result.

[0027] In a preferred embodiment, the generation of the advance warning instruction and the confirmation warning instruction includes: S701, generating the advance warning instruction based on the trajectory intent prediction result.

[0028] S702: Based on the corrected equipment location information, determine the dwell time of the equipment after it actually enters the restricted area, confirm the advance warning command, and generate a confirmation warning command; specifically, based on the corrected coordinates and speed estimation in the corrected equipment location information, perform trajectory extrapolation to obtain the predicted position coordinates, determine whether the area where the predicted position coordinates fall belongs to the restricted area, the restricted area includes the waste room and non-medical area, if so, generate the advance warning command; when the equipment actually enters the restricted area and the dwell time is greater than or equal to the preset dwell time confirmation threshold, upgrade the advance warning command to a confirmation warning command.

[0029] In a preferred embodiment, transmitting the confirmation warning instruction to the device management state machine includes: transmitting the confirmation warning instruction as a device management instruction to the device management state machine; the advance warning instruction is only pushed to the management personnel and is not transmitted to the device management state machine.

[0030] In a preferred embodiment, the step of obtaining the device search request and the identity card information of the search initiator, and verifying the permissions of the identity card information of the search initiator, includes: S901, obtaining the device search request and the identity card information of the search initiator, wherein the device search request includes the target device identifier and the search initiation location.

[0031] S902 verifies the identity card information to obtain the identity verification result.

[0032] S903: When the authentication result is successful, the target device location and target device status corresponding to the target device identifier are determined based on the confirmation warning instruction and the corrected device location information.

[0033] In a preferred embodiment, generating the device search and scheduling result includes: S1001, based on the search initiation location and the target device location, performing path planning in the hospital navigation map to generate a navigation path.

[0034] S1002, merge the navigation path with the target device status to generate the device search and scheduling result.

[0035] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention constructs a device management state machine to drive the migration of device management states through real-time management events. It dynamically configures the positioning mode, positioning refresh frequency, and wake-up strategy based on the device management state, enabling positioning resources to be upgraded or downgraded in real-time according to management needs. When an emergency call occurs, the target device can automatically upgrade to the highest precision positioning and high-frequency positioning refresh rate, ensuring real-time tracking in emergency scenarios. When the device is idle, the tag can enter a deep sleep state to extend battery life, achieving an optimal dynamic balance between positioning accuracy and power consumption. Simultaneously, device management commands are fed back to the device management state machine as early warning trigger events, driving abnormal devices to automatically enter a continuous locking and packet-sending early warning state. This forms a two-way linkage between management events and positioning strategies, shortening the response process from device anomaly detection to locking and tracking from manual intervention to automatic setting, significantly improving the automation level and response speed of device anomaly handling.

[0036] 2. This invention extrapolates the trajectory based on the corrected coordinates and velocity estimation in the modified device location information, predicts the device's future position, and determines whether it has fallen into a restricted area. A pre-warning command is generated before the device actually enters non-medical areas such as waste rooms. This is combined with a confirmation warning command based on dwell time confirmation, shifting the trigger point for anti-theft and accidental loss warnings from "anomaly already occurred" to "anomaly about to occur," providing managers with a window of opportunity for proactive intervention. Simultaneously, the two-tiered mechanism of pre-warning and dwell time confirmation effectively filters false alarms caused by location jitter and short-term passing, improving both response timeliness and alarm accuracy. Furthermore, the floor assignment determination through dual verification using barometers and landmark beacons effectively avoids cross-floor false alarms caused by environmental pressure fluctuations, further enhancing the reliability and continuity of location tracking. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating an in-hospital equipment location and tracking method based on a medical Internet of Things terminal, as provided in an embodiment of the present invention. Figure 2 This is a planar view of the landmark beacon adsorption part in this invention; Figure 3 This is a schematic diagram of the floor cross-section perspective of the air pressure height difference determination part in this invention. Figure 4 This is a schematic diagram of the barometric pressure-landmark dual verification logic in this invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0038] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0039] This application provides a method for locating and tracking equipment within a hospital based on a medical IoT terminal. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc.

[0040] In this embodiment, the in-hospital equipment location tracking method based on medical IoT terminals includes: S1, acquiring equipment management attribute information and real-time management events of each medical device in the hospital, constructing an equipment management state machine, and obtaining the equipment management status of each medical device.

[0041] In this embodiment of the invention, the step of acquiring the equipment management attribute information and real-time management events of each medical device in the hospital, constructing an equipment management state machine, and obtaining the equipment management status of each medical device includes...

[0042] S201, Obtain equipment management attribute information, which includes equipment identification, emergency response timeliness score, mobility frequency score, and asset control level score.

[0043] S202, Obtain real-time management events, including equipment usage registration events, usage end events, emergency call events, emergency end events, warning trigger events, and warning cancellation events.

[0044] S203. Initialize the equipment management status of each medical device based on the equipment management attribute information, and construct the equipment management state machine. The equipment management status includes normal state, standby state, use state, emergency state and early warning state.

[0045] S204, based on real-time management events, drives the device management state machine to perform state transitions through state transition functions to obtain the device management status of each medical device.

[0046] It should be noted that the specific meanings of the equipment management attribute information are as follows: The equipment identifier serves as a unique identifier for each medical device within the hospital, used to distinguish different devices during location tracking; the emergency response timeliness score reflects the timeliness requirements for real-time location tracking in emergency scenarios, with a higher value indicating a higher requirement for location response speed during rescue; the movement frequency score reflects the frequency of device movement during daily use, with a higher value indicating more frequent location changes; and the asset control level score reflects the value level of the equipment and access control requirements, with a higher value indicating higher equipment value and stricter access control requirements. The emergency response timeliness score, movement frequency score, and asset control level score are all normalized to values ​​between 0 and 1, pre-configured by the hospital's equipment management department based on equipment type and actual management needs, and are updated periodically based on the equipment's historical usage records. The hospital equipment management department establishes a scoring benchmark table based on equipment type. Initial values ​​for emergency response timeliness, movement frequency, and asset management level scores are determined and normalized according to the frequency of emergency calls, daily movement frequency, and asset value level corresponding to each equipment type. Historical usage records include emergency call records, equipment movement records, and equipment usage registration records. For example, the emergency response timeliness score for ventilators is configured as 0.9, the movement frequency score as 0.7, and the asset management level score as 0.8; the emergency response timeliness score for infusion pumps is configured as 0.3, the movement frequency score as 0.5, and the asset management level score as 0.4. The default update cycle is one quarter.

[0047] It should be noted that the mobility frequency score is only used for initializing the device management status. After the device completes initialization, subsequent positioning and acquisition strategy configuration, trajectory intent prediction, and search scheduling are all performed based on the device management status and the mobility frequency score is no longer directly read. The mobility frequency score is maintained by the hospital's device management department and is a pre-configured static attribute value that is not automatically written back and updated with each single device usage record. If the actual mobility frequency of the device changes significantly, the management department will reconfigure the score and re-execute the device management status initialization in the next status update cycle. In addition to being used for initialization determination, the asset control level score is also used for enhanced configuration of positioning strategies for high-control standby devices.

[0048] Furthermore, the significance of normalizing the emergency response timeliness score, mobility frequency score, and asset control level score lies in eliminating the dimensional differences between different evaluation dimensions, making the three types of scores comparable within the same numerical space, and providing a unified data benchmark for the initialization of equipment management status.

[0049] It should be noted that the real-time management events are acquired as follows: The hospital's medical equipment management system monitors various business trigger sources in real time, collecting events such as equipment usage registration, usage completion, emergency call, emergency response completion, warning trigger, and warning cancellation. Specifically, the equipment usage registration event is triggered by the equipment registration terminal when medical staff register to use the equipment; the usage completion event is triggered by the equipment registration terminal when medical staff return the equipment; the emergency call event is triggered by the emergency call system when an emergency call is issued; the emergency response completion event is triggered by the emergency call system when the emergency response ends; the warning trigger event is triggered by the confirmation of the warning instruction; and the warning cancellation event is triggered by the administrator confirming the cancellation of the warning.

[0050] It should be noted that the equipment management state machine is constructed as follows: the normal state, standby state, usage state, emergency state, and warning state are used as the state set of the equipment management state machine; the equipment usage registration event, usage end event, emergency call event, emergency end event, warning trigger event, and warning cancellation event are used as the event set of the equipment management state machine; and the state transition function is used as the state transition rule of the equipment management state machine. The equipment management state machine is thus constructed.

[0051] Furthermore, the initialization method for equipment management status is as follows: Based on equipment management attribute information, an initial equipment management status is set for each medical device. For devices with an emergency response timeliness score greater than or equal to a preset emergency response timeliness threshold, or a mobility frequency score greater than or equal to a preset mobility frequency threshold and an asset control level score greater than or equal to a preset asset control level threshold, the initial equipment management status is set to standby; for other devices, the initial equipment management status is set to normal. The default values ​​for the preset emergency response timeliness threshold, the preset mobility frequency threshold, and the preset asset control level threshold are 0.5.

[0052] It should be noted that the standby state corresponds to deep sleep and a lower positioning refresh rate. However, when an emergency call occurs, the network side wakes up the standby device tag through downlink signaling, causing it to immediately switch to ultra-wideband time difference of arrival mode and increase the positioning refresh rate to 10 times per second. Therefore, the initial standby state of emergency rescue devices does not affect the real-time tracking requirements in emergency scenarios.

[0053] Furthermore, the specific meanings of the equipment management status are as follows: Normal status indicates that the equipment is in a normal idle state; Standby status indicates that the equipment is in a standby state that can be put into use at any time; Use status indicates that the equipment is being used by medical personnel; Rescue status indicates that the equipment has been activated by a rescue call event for emergency treatment; Warning status indicates that the equipment has malfunctioned and requires management personnel to handle it.

[0054] It should be noted that the mathematical expression of the state transition function is as follows:

[0055] In the formula, Indicates that the device is in Real-time device management status, express Real-time management events that occur constantly. Represents the state transition function. This indicates the next device management status after the event occurs.

[0056] Furthermore, the specific state transition rules of the state transition function are as follows: When the device is in the normal state and a device usage registration event occurs, the device management state is transitioned to the usage state; when the device is in the standby state and a device usage registration event occurs, the device management state is transitioned to the usage state; when the device is in the usage state and a usage end event occurs, the device management state is transitioned to the normal state; when the device is in the normal, standby, or usage state and a rescue call event occurs, the device management state is transitioned to the rescue state; when the device is in the rescue state and a rescue end event occurs, the device management state is transitioned to the standby state; when the device is in any state and a warning trigger event occurs, the device management state is transitioned to the warning state; when the device is in the warning state and a warning cancellation event occurs, the device management state is returned to the device management state before the warning trigger event occurred; for combinations of states and events not listed in the above rules, the device management state remains unchanged, but the event is still recorded for subsequent auditing.

[0057] Furthermore, when the device management state transitions to the warning state, the device management state machine records the original device management state before the transition, so that when the warning cancellation event occurs, the device management state can be restored to the original device management state.

[0058] Furthermore, the state transition function is used as follows: In each state update cycle, the current device management state and the real-time management events that occur in the current cycle are obtained. The current device management state and the real-time management events are used as inputs to the state transition function. The corresponding target state is found according to the state transition rules, and the target state is used as the device management state in the next state update cycle. If no real-time management events occur in the current cycle, the device management state remains unchanged.

[0059] S2. Configure the positioning and acquisition strategy based on the device management status, and collect positioning signal data to obtain the real-time location coordinates of each medical device.

[0060] In this embodiment of the invention, the step of configuring a positioning acquisition strategy based on the device management status and acquiring positioning signal data includes: S301, determining the positioning mode, positioning refresh frequency, and wake-up strategy corresponding to each medical device according to the device management status through a positioning strategy mapping function to obtain the positioning acquisition strategy; the positioning strategy mapping function includes: when the device management status is in emergency state, the positioning mode is ultra-wideband time difference of arrival mode, and the positioning refresh frequency is 10 times per second; when the device management status is in use state, the positioning mode is Bluetooth angle of arrival mode, and the positioning refresh frequency is once every 2 seconds; when the device management status is in normal state, the positioning mode is Bluetooth signal strength mode, and the positioning refresh frequency is once every 5 minutes; when the device management status is in standby state, the device tag enters deep sleep, and the positioning refresh frequency is once every 10 minutes; when the device management status is in warning state, the positioning mode is ultra-wideband time difference of arrival mode, the positioning refresh frequency is 10 times per second, and the wake-up strategy is continuous locking packet transmission; the positioning mode also includes ultra-high frequency radio frequency identification access control mode.

[0061] S302 collects positioning signal data of each medical device based on the wake-up strategy and positioning refresh frequency; among them, the UHF RFID access control mode is passively triggered by the access control reader when the device tag passes through the reading range, and is not constrained by the positioning refresh frequency and wake-up strategy.

[0062] In this embodiment of the invention, obtaining the real-time location coordinates of each medical device includes: S401, based on the positioning signal data, performs position analysis using a position analysis method corresponding to the positioning mode to obtain the real-time position coordinates of each medical device; the position analysis method includes at least one of position analysis based on time difference of arrival measurement, position analysis based on angle of arrival measurement, and position analysis based on signal strength measurement; wherein the UHF RFID access control mode only records the discrete position points when the device passes through the access control and does not participate in continuous position analysis.

[0063] S402, When the device management state changes, the positioning strategy mapping function is re-executed to update the positioning acquisition strategy.

[0064] It should be noted that the mathematical expression of the positioning strategy mapping function is as follows:

[0065] In the formula, Indicates that the device is in The device management state at any given time is consistent with the device management state output by the state transition function. This represents the positioning strategy mapping function; Indicates in Location mode that is always enabled; Indicates in The location refresh rate at any given moment; Indicates in A timely wake-up strategy.

[0066] Furthermore, the specific mapping rules of the positioning strategy mapping function are as follows: When the device management state is in emergency mode, the positioning mode is ultra-wideband time difference of arrival mode, the positioning refresh frequency is 10 times per second, and the wake-up strategy is active packet transmission; when the device management state is in use mode, the positioning mode is Bluetooth angle of arrival mode, the positioning refresh frequency is once every 2 seconds, and the wake-up strategy is active packet transmission; when the device management state is in normal mode, the positioning mode is Bluetooth signal strength mode, the positioning refresh frequency is once every 5 minutes, and the wake-up strategy is on-demand wake-up combined with periodic heartbeat; when the device management state is in standby mode, the device tag enters deep sleep, the positioning refresh frequency is once every 10 minutes, and the wake-up strategy is deep sleep combined with accelerometer. The system triggers wake-up via three mechanisms: periodic heartbeat wake-up, downlink signaling wake-up, and activation of Bluetooth signal strength mode to collect location signal data when the accelerometer detects device movement or a periodic heartbeat is detected. Specifically, for standby devices with an asset management level score greater than or equal to a preset high asset management threshold, the device tag does not enter deep sleep mode. The wake-up strategy is adjusted to on-demand wake-up combined with periodic heartbeats, and the location refresh frequency is increased to once per minute to enhance the location tracking strength of high asset management level devices. In the event of an emergency call, the network side wakes up the standby device tag via downlink signaling, immediately waking it from deep sleep and switching it to ultra-wideband time-of-arrival (UWHA) mode, increasing the location refresh frequency to 10 times per second. The preset high asset management threshold is 0.8 by default. When the device management status is in alert mode, the location mode is UWHA mode, the location refresh frequency is 10 times per second, and the wake-up strategy is continuous packet locking. Among them, the UHF RFID access control mode serves as an auxiliary discrete location recording method and is continuously available in any device management state. It does not replace the main positioning mode of the above states, nor does it change the positioning refresh frequency and wake-up strategy already determined for each state.

[0067] Furthermore, the dynamic adjustment method of the positioning strategy mapping function is as follows: When the device management state changes, the positioning strategy mapping function is re-executed to obtain the updated positioning mode, positioning refresh frequency, and wake-up strategy. The device tag adjusts its own working mode according to the updated positioning acquisition strategy. When the device management state changes from standby to emergency state, the positioning refresh frequency is directly increased from deep sleep state to 10 times per second, realizing the dynamic upgrade of positioning resources.

[0068] It should be noted that the specific implementation methods of the wake-up strategy are as follows: Active packet transmission refers to the device tag actively transmitting positioning signals according to the positioning refresh frequency; On-demand wake-up combined with periodic heartbeat refers to the device tag periodically transmitting positioning signals according to the positioning refresh frequency when there is no search request, and immediately waking up and increasing the transmission frequency upon receiving a search request; Deep sleep combined with accelerometer-triggered wake-up and periodic heartbeat wake-up refers to the device tag entering a low-power sleep state, retaining only the accelerometer sensing capability and the periodic heartbeat timed wake-up capability, triggering wake-up and transmitting positioning signals when the accelerometer senses device movement or a periodic heartbeat arrives; Downlink signaling wake-up refers to the network side actively sending a wake-up signal to the deep sleep device tag in standby mode when a rescue call event occurs. After receiving the wake-up signal, the device tag immediately wakes up from deep sleep, switches to ultra-wideband time difference of arrival mode, and transmits positioning signals at a positioning refresh frequency of 10 times per second; Continuous lock packet transmission refers to the device tag continuously transmitting positioning signals at the positioning refresh frequency to ensure continuous locking and tracking of abnormal devices.

[0069] It should be noted that the location analysis process for the UWB (Ultra-Wideband) Time Difference of Arrival (TDOA) mode is as follows: At least four UWB base stations are deployed, one of which serves as a reference base station. The device tag transmits an UWB positioning signal, and each base station records the signal arrival time. The signal arrival time is then recorded. Subtracting the time of signal arrival at the reference base station from the time of arrival at the first base station yields the time difference of arrival; multiplying the time difference of arrival by the speed of light gives the distance from the device tag to the first base station. The distance difference between each base station and the reference base station. Ultra-wideband (UWB) base stations are deployed at intervals of 20 to 30 meters according to the layout of corridors and rooms within the compound. Since UWB signals suffer significant penetration loss through walls, deployment should ensure line-of-sight between the base stations and the area to be located, guaranteeing that at least four base stations are visible in any area. In corridor areas with dense walls or severe non-line-of-sight obstructions, the base station spacing should be shortened or the number of base stations increased. Wired or wireless clock synchronization calibration is used between base stations, with clock synchronization errors controlled within 1 nanosecond. During positioning analysis, residual detection is used to eliminate base station observations significantly affected by non-line-of-sight obstructions. The installation height difference between each base station is pre-measured and height compensation is performed during analysis. The spatial deployment of base stations maintains a non-coplanar geometric configuration, avoiding all base stations being located on the same straight line. When only three base stations are visible in any area to be located, three-dimensional position calculation is not performed; instead, the positioning of this area is degraded to two-dimensional positioning based on barometer data and map constraints, or the positioning observation is marked as unavailable. When fewer than three base stations are visible, real-time position coordinates are not output.

[0070] Furthermore, the formula for the distance difference in ultra-wideband time of arrival is as follows:

[0071] In the formula, This indicates that the device tag signal has arrived at the first... The distance difference between each base station and the reference base station is expressed in meters. ; The speed of light is expressed in meters per second. Indicates the signal has arrived at the first The time of each base station is in seconds; This indicates the time when the signal arrives at the reference base station, in seconds.

[0072] Furthermore, the nonlinear equations constructed based on the distance difference are as follows:

[0073] In the formula, This represents the three-dimensional position coordinates of the device label to be solved, in meters; Indicates the first The coordinates of each base station are in meters; The coordinates of the reference base station are shown in meters. Solving this system of nonlinear equations yields the three-dimensional position coordinates of the device tag. The simultaneous visibility of at least four base stations is a necessary condition for analyzing the elevation coordinates and achieving three-dimensional positioning.

[0074] It should be noted that the location analysis process for Bluetooth Angle of Arrival (AHA) mode is as follows: Two antenna elements in the antenna array of the Bluetooth base station receive the Bluetooth signal transmitted by the device tag, and the phase difference between the received signals is measured; the angle of arrival of the Bluetooth signal to the antenna array is calculated based on the phase difference; the location coordinates of the device tag are analyzed through geometric relationships by combining the angles of arrival of multiple Bluetooth base stations. One Bluetooth AHA base station is deployed for every 50 to 100 square meters, with at least two base stations visible simultaneously in a single positioning area; deployment of three or more is recommended. The center height of the base station antenna array is generally 2.5 to 3 meters, and the normal direction of the antenna array faces the main positioning area; the phase difference is used to suppress measurement errors through multi-frame averaging and antenna element amplitude and phase calibration.

[0075] Furthermore, the angle of arrival formula used for Bluetooth angle of arrival analysis is as follows:

[0076] In the formula, This indicates the angle of arrival of the Bluetooth signal at the antenna array, in radians. It represents the phase difference between the received signals of two antenna elements in an antenna array, and the unit is radians; The speed of light is expressed in meters per second. This indicates the Bluetooth signal carrier frequency, measured in Hertz (Hz). This indicates the distance between two antenna elements, in meters, with the default value being half the Bluetooth signal carrier wavelength.

[0077] It should be noted that the location analysis process in Bluetooth signal strength mode is as follows: The Bluetooth base station receives the positioning signal emitted by the device tag and records the actual received signal strength; the distance estimate from the device tag to the Bluetooth base station is calculated based on the signal strength distance model; and the location coordinates of the device tag are analyzed by triangulation by combining the distance estimates from at least 3 Bluetooth base stations.

[0078] Furthermore, the mathematical expression for the Bluetooth signal strength distance model is as follows:

[0079] In the formula, This represents the estimated distance from the device tag to the Bluetooth base station, in meters. This indicates the reference signal strength at a distance of 1 meter from the Bluetooth base station, measured in decibels and milliwatts. The signal strength received by the Bluetooth base station is expressed in decibels and milliwatts; n represents the path loss exponent, which is dimensionless and pre-calibrated based on the actual environment within the facility, with a value ranging from 2 to 4.

[0080] Furthermore, the path loss index is calibrated as follows: the calibration zones are divided according to the room, corridor and ward environment. Reference points with known distances are set in each calibration zone. The signal strength of the reference points is measured. The path loss index of the zone is obtained by fitting the correspondence between distance and signal strength and stored. When the positioning error in the zone exceeds the preset error threshold or the environmental layout changes, the calibration is re-executed or dynamic correction is performed by deploying reference tags.

[0081] It should be noted that the location recording method for the UHF RFID access control mode is as follows: UHF RFID access control readers are deployed at ward and department entrances. When a device tag passes through the reader's reading range, the reader reads the tag's identity information and generates an access control trigger record. This record includes the reader's installation location and trigger time. The reader's installation location is used as the device's real-time location coordinates when it passes through the access control. This mode does not perform continuous location analysis; it only records the discrete location points when the device passes through the access control. When a device only has an access control trigger record but no continuous location mode analysis coordinates at a certain moment, the reader's installation location is used as the real-time location coordinates at that moment and input into S3. The Kalman filter in S3 treats this as a discrete observation and increases the observation noise variance accordingly. Map constraint correction, floor and room assignment determination, and subsequent trajectory extrapolation can still be performed based on this discrete location point. When both continuous location mode analysis coordinates and access control trigger records exist at the same time, the continuous location mode analysis coordinates are used as the real-time location coordinates, and the access control trigger records are used as verification information.

[0082] S3. Based on the real-time location coordinates of each medical device, perform map constraint correction and floor / room affiliation determination to obtain the corrected device location information.

[0083] In this embodiment of the invention, the corrected device location information includes corrected coordinates, speed estimation, floor identifier, and room identifier.

[0084] In this embodiment of the invention, the step of performing map constraint correction and floor / room affiliation determination based on the real-time location coordinates of each medical device to obtain the corrected device location information includes: S501, acquiring the rasterized map of the hospital building information model, landmark beacon signals, and barometer data.

[0085] S502 performs Kalman filtering on the real-time position coordinates to obtain the filtered position coordinates and velocity estimates.

[0086] S503, based on the rasterized map of the building information model, applies validity constraints to the filtered location coordinates, removes invalid location points that fall inside the walls or unreachable partitions, and obtains the constrained location coordinates.

[0087] S504, the floor and room assignment determination is based on a dual verification of landmark beacon signals and barometer data to obtain the floor and room assignment result; wherein the floor and room assignment determination includes: obtaining the room assignment result by room adsorption based on landmark beacon signals, calculating the air pressure height difference based on barometer data and triggering floor switching only when the absolute value of the air pressure height difference is greater than a preset floor switching threshold to obtain the floor assignment result, and verifying the room assignment result with the floor assignment result to obtain the floor and room assignment result.

[0088] S505 combines the constrained position coordinates, velocity estimates, and floor / room assignment results to obtain the corrected equipment location information; the corrected equipment location information includes corrected coordinates, velocity estimates, floor identifiers, and room identifiers.

[0089] It should be noted that the rasterized map of the building information model (BIM) is map data formed by discretizing the building structures such as walls, inaccessible partitions, and corridors in the hospital's BIM model into raster cells according to a preset raster size. Each raster cell carries a building structure type identifier, which includes walls, inaccessible partitions, and legal access areas. Legal access areas include medical function rooms such as corridors, wards, and examination rooms; inaccessible partitions include non-functional rooms such as pipe shafts and low-voltage electrical rooms, but do not include normal function rooms such as wards and examination rooms. The default preset raster size is 0.5 meters.

[0090] It should be noted that the landmark beacons are low-power beacon devices deployed at the entrances of wards and in the corridors of operating rooms, and each landmark beacon is pre-set with a corresponding room identifier; the barometer data is a sequence of barometer values ​​collected in real time by the barometer built into the device tag.

[0091] It should be noted that the state equation and observation equation upon which Kalman filtering is based are as follows:

[0092]

[0093] In the formula, Indicates the first The state vector at any given time contains position and velocity components; Represents the state transition matrix; Indicates process noise; Indicates the first The observation vector at any given time is composed of real-time position coordinates; Represents the observation matrix; The observation noise is represented by the following: The state vector is defined as a six-dimensional vector, including lateral position, longitudinal position, height position, lateral velocity, longitudinal velocity, and height velocity; the state transition matrix adopts a uniform motion model; the observation matrix maps the three-dimensional position components in the state vector to the real-time position coordinate three-dimensional observation vector; both process noise and observation noise are zero-mean Gaussian white noise, and their covariance matrices are preset according to the dynamic characteristics of the device tag and the observation accuracy of the positioning mode, respectively. When only access control trigger records are used as discrete observation inputs, the observation noise variance is increased.

[0094] Furthermore, the Kalman filter is used as follows: Within each filtering cycle, the current state vector is first predicted based on the state equation, and then the prediction result is updated using the observation vector to obtain the filtered position coordinates and velocity estimate. The filtered position coordinates are used for subsequent map constraint processing, and the velocity estimate is used for trajectory extrapolation.

[0095] It should be noted that the specific method of map constraints is as follows: The filtered location coordinates are mapped onto the rasterized map of the Building Information Model (BIM), and the building structure type identifier of the raster cell containing the mapped location is determined. If the building structure type identifier is a wall or an inaccessible partition, the filtered location coordinates are projected onto the nearest legal access area raster cell to obtain the constrained location coordinates. If the building structure type identifier is a legal access area, the filtered location coordinates are directly used as the constrained location coordinates. During projection, the distance metric uses Euclidean distance from the raster map, and projection is only performed within the same floor, without projection across floors or walls. When the nearest legal access area raster cell is located on the other side of a wall, the nearest legal access area raster cell within the same floor that does not cross walls is selected. Through map constraints, jump points caused by multipath interference can be eliminated, ensuring that the displayed trajectory always conforms to the physical corridor.

[0096] It should be noted that the specific method of landmark beacon attachment is as follows: When the device tag enters the signal coverage range of the landmark beacon, and the received landmark beacon signal strength is higher than the preset attachment threshold, the room identifier corresponding to the landmark beacon is used as the room assignment result, and soft calibration is performed with the Kalman-filtered position coordinates for confirmation, without forcibly changing the position coordinates; when the signal strength is lower than the preset attachment threshold or conflicts with the map constraint result, the map-constrained position coordinates are retained, and the room identifier of the landmark beacon is not used. The default radius of the landmark beacon coverage range is 3 meters, and the preset attachment threshold is pre-calibrated based on the beacon transmission power and the site environment. Landmark beacon attachment is used to assist in calibrating the room assignment of the device at key entrances and exits such as ward entrances and operating room corridors, without relying on wireless signal penetration through walls to determine the floor.

[0097] It should be noted that the formula for calculating the pressure difference is as follows:

[0098] In the formula, This indicates the pressure difference between the equipment's current height and a reference height, expressed in meters. This represents the universal gas constant, with a value of 8.314 joules per mole Kelvin; This represents absolute temperature, measured in Kelvin. The value represents the acceleration due to gravity, which is 9.8 m / s²; M represents the molar mass of air, which is 0.029 kg / molar. This represents the reference air pressure value at a reference altitude, in Pascals. This indicates the current air pressure value measured by the device, in Pascals.

[0099] Furthermore, the specific method for determining floor and room assignment using dual verification is as follows: On one hand, room assignment is obtained by adsorbing the landmark beacon signal; on the other hand, the air pressure height difference is calculated based on barometer data. Floor switching is triggered only when the absolute value of the air pressure height difference is greater than a preset floor switching threshold, thus obtaining the floor assignment result. The room assignment result and the floor assignment result are cross-verified to obtain the final floor and room assignment result. The default preset floor switching threshold is 1.5 meters. When the absolute value of the air pressure height difference is not greater than the preset floor switching threshold, floor switching will not be triggered even if the landmark beacon signal is temporarily lost due to environmental interference, thereby avoiding false floor jumps caused by air pressure fluctuations due to air conditioning start-stop or window ventilation. When the landmark beacon determination and the air pressure height difference determination are inconsistent, the floor result determined by the air pressure height difference is used as the floor identifier; if the room identifier given by the landmark beacon is inconsistent with the current floor, the room identifier is temporarily not used, and the previous valid room identifier is retained until the next valid determination. In terms of execution timing, the corrected device location information is executed first within each positioning cycle, followed by trajectory extrapolation based on this corrected device location information. If the air pressure height difference triggers a floor switch within the current positioning cycle, the trajectory extrapolation within that cycle will not perform restricted area determination. Restricted area determination will resume only after the floor markers are updated in the next cycle and the corrected device location information is obtained again. Restricted area determination is performed solely based on the building space label data corresponding to the horizontal coordinates and the current floor marker; changes in the height component of the predicted location coordinates do not directly trigger restricted area determination.

[0100] It should be noted that the corrected device location information is merged as follows: the constrained location coordinates are used as the corrected coordinates, the velocity estimate obtained from Kalman filtering is used as the velocity estimate, and the floor and room identifiers from the floor and room assignment results are used as the floor and room identifiers, respectively. These are then merged to obtain the corrected device location information. The corrected device location information provides a location reference and motion trend input for trajectory intent prediction and dwell time confirmation.

[0101] S4. Based on the corrected device location information, generate trajectory intention prediction results, then generate advance warning instructions and confirmation warning instructions, and transmit the confirmation warning instructions to the device management state machine.

[0102] In this embodiment of the invention, generating trajectory intention prediction results based on the corrected device location information includes: S601, obtaining building space label data, the building space label data including the area type of each area, the area type including normal medical area, corridor, sewage room and non-medical area.

[0103] S602, based on the corrected coordinates and velocity estimation in the corrected equipment position information, extrapolate the trajectory of the equipment's future position to obtain the predicted position coordinates.

[0104] S603, determine the region type of the area into which the predicted position coordinates fall, and obtain the trajectory intention prediction result.

[0105] It should be noted that the building space labeling data is generated by semantically annotating hospital building spaces according to their management attributes. The semantic types of each area include normal medical areas, corridors, waste rooms, and non-medical areas. Waste rooms and non-medical areas constitute a restricted area set. Non-medical areas refer to rooms not used for medical purposes, such as offices, storage rooms, and equipment rooms, excluding common passageways such as hospital corridors, elevator lobbies, and stairwells. The semantic types of each area are pre-labeled by the hospital's equipment management department based on the intended use of each area.

[0106] It should be noted that the location prediction formula used for trajectory extrapolation is as follows:

[0107] In the formula, Indicates the predicted time The predicted location coordinates; The corrected coordinates at the current moment are taken from the corrected device position information obtained in step S3; The current speed estimate is taken from the corrected device position information obtained in step S3. This indicates the prediction time step, with a default value of 5 seconds.

[0108] Furthermore, the trajectory extrapolation is used as follows: the corrected coordinates at the current moment are taken as the current position, the velocity estimate is taken as the current velocity, the current velocity is multiplied by the prediction time step to obtain the predicted displacement, and the current position is added to the predicted displacement to obtain the predicted position coordinates. The trajectory extrapolation is based on the linear motion assumption, using the velocity estimate output by the Kalman filter to extrapolate and predict the short-term motion trend of the device. When the device velocity is detected to be less than 0.2 meters per second or the velocity direction changes by more than 45 degrees compared to the previous cycle, the prediction time step is shortened from 5 seconds to 2 seconds, and the predicted position coordinates are obtained by adding the current corrected coordinates to the current velocity multiplied by the shortened prediction time step. This avoids excessive deviations in nonlinear motion scenarios such as turning, deceleration, or stopping during linear extrapolation.

[0109] When the absolute value of the height velocity component in the velocity estimate is greater than the preset vertical motion threshold, the device is determined to be in vertical motion. At this time, the prediction time step is shortened to the preset vertical motion prediction step, and the predicted position coordinates are not mapped to the restricted area for determination. After the floor and room assignment determination in step S3 completes the floor switching and updates the floor identifier, the trajectory extrapolation and restricted area determination are restored based on the updated and corrected device position information. The preset vertical motion threshold is pre-calibrated according to the vertical running speed of the elevator in the courtyard, with a default value of 0.5 meters per second; the preset vertical motion prediction step is set to 1 second by default. When the positioning refresh frequency corresponding to the device management status is less than once every 2 seconds, before executing trajectory extrapolation, the system temporarily increases the positioning refresh frequency to once every 2 seconds and continuously collects position data for at least 3 positioning cycles to obtain the currently valid velocity estimate before executing trajectory extrapolation. During this temporary increase, the device management status remains unchanged and the original mapping rules of the positioning strategy mapping function are not changed.

[0110] It should be noted that the temporary frequency boosting mechanism before trajectory extrapolation and the temporary coverage mechanism of the positioning strategy after the generation of the advance warning command are independent of each other: the former is used to provide continuous location data that meets the sampling density requirements for trajectory extrapolation, and the latter is used to continuously record the time when the device enters and leaves the restricted area after the generation of the advance warning command. Neither of them triggers the device management state machine transition.

[0111] It should be noted that the rules for determining the trajectory intent prediction results are as follows:

[0112] In the formula, This indicates the trajectory intention prediction result. A value of 1 indicates that the prediction device is about to enter the restricted area, while a value of 0 indicates that the prediction device will not enter the restricted area. This represents a mapping function that maps location coordinates to the corresponding region type. This represents a set of restricted areas, which includes waste disposal areas and non-medical areas.

[0113] Furthermore, the determination method for trajectory intention prediction results is as follows: map the predicted location coordinates to the corresponding area in the building space label data, and determine whether the area type belongs to the restricted area set; if it belongs to the restricted area set, the trajectory intention prediction result is 1; if it does not belong to the restricted area set, the trajectory intention prediction result is 0.

[0114] In this embodiment of the invention, the generation of advance warning instructions and confirmation warning instructions includes: S701, generating advance warning instructions based on trajectory intent prediction results.

[0115] S702: Based on the corrected equipment location information, determine the dwell time of the equipment after it actually enters the restricted area, confirm the advance warning command, and generate a confirmation warning command; specifically, based on the corrected coordinates and speed estimation in the corrected equipment location information, perform trajectory extrapolation to obtain the predicted position coordinates, determine whether the area where the predicted position coordinates fall belongs to the restricted area, the restricted area includes the waste room and non-medical area, if so, generate the advance warning command; when the equipment actually enters the restricted area and the dwell time is greater than or equal to the preset dwell time confirmation threshold, upgrade the advance warning command to a confirmation warning command.

[0116] It should be noted that when the positioning refresh frequency corresponding to the device management status is less than once every 2 seconds, the positioning refresh frequency is temporarily increased to once every 2 seconds before executing trajectory extrapolation. Then, based on the corrected device location information, the actual dwell time of the device after entering the restricted area is determined, the pre-warning command is confirmed, and a confirmation warning command is generated. In this embodiment of the invention, transmitting the confirmation warning command to the device management state machine includes: Confirmation warning commands are transmitted to the equipment management state machine as equipment management commands; advance warning commands are only pushed to management personnel and are not transmitted to the equipment management state machine.

[0117] It should be noted that the pre-warning command is generated as follows: when the trajectory intent prediction result is 1, a pre-warning command is immediately generated and pushed to the management personnel, indicating that the device is about to enter a restricted area; when the trajectory intent prediction result is 0, no pre-warning command is generated. The pre-warning command is generated before the device actually enters the restricted area, providing management personnel with a window for pre-emptive interception. After the pre-warning command is generated, before it is revoked or upgraded to a confirmed warning command, if the device's current positioning refresh frequency is less than once every 2 seconds, the positioning refresh frequency is increased to once every 2 seconds through a temporary overlay mechanism to continuously record the time of the device entering and leaving the restricted area; the device management status remains unchanged during the upgrade period. The temporary coverage mechanism for the positioning strategy is executed independently of the positioning strategy mapping function. It only takes effect when there is a valid pre-warning instruction. The actual effective positioning refresh frequency is temporarily adjusted to once every 2 seconds. This does not change the device management status or the original mapping rules of the positioning strategy mapping function. When the pre-warning instruction is revoked or upgraded to a confirmed warning instruction, the temporary coverage is automatically removed, and the positioning acquisition strategy determined by the positioning strategy mapping function based on the device management status is restored.

[0118] It should be noted that the device location refresh frequency is once every 2 seconds when in use. The device has not yet entered the restricted area when the advance warning command is generated. If the device continues to move and actually enters the restricted area, the default value of the dwell time confirmation threshold is 30 seconds. During this period, the system can still continuously collect location data for at least 15 location refresh cycles and has a continuous monitoring and handling time window of more than 30 seconds, allowing managers to complete the pre-interception before the confirmation warning command is generated.

[0119] It should be noted that the formula for calculating the length of stay is as follows:

[0120] In the formula, This indicates the duration of time the device remains in the restricted area, in seconds. Indicates the actual moment when the equipment entered the restricted area; This indicates the moment when the device leaves the restricted area.

[0121] Furthermore, the confirmation rules for the advance warning command are as follows: After the advance warning command is generated, it continuously monitors whether the device actually enters the restricted area within the predicted time step; if the device actually enters the restricted area and the dwell time is greater than or equal to the dwell time confirmation threshold, the advance warning command is upgraded to a confirmation warning command; if the device does not actually enter the restricted area within the predicted time step, or if the device actually enters the restricted area but the dwell time is less than the dwell time confirmation threshold, the advance warning command is revoked, and a short-term passing event is recorded. The default value for the dwell time confirmation threshold is 30 seconds. The advance warning command and the confirmation warning command together constitute the device management command.

[0122] Furthermore, the significance of the two-tiered mechanism of advance warning and dwell time confirmation is as follows: The first-tier advance warning is triggered before the equipment actually enters the restricted area, providing managers with a pre-emptive interception window; the second-tier dwell time confirmation verifies the advance warning, filtering out false alarms caused by positioning jitter or short-term passing. This two-tiered mechanism achieves a balance between the timeliness of warnings and the accuracy of alarms.

[0123] It should be noted that the feedback mechanism works as follows: The confirmed warning command is transmitted as a warning trigger event to the constructed device management state machine, driving the device management state machine to transition the corresponding device's device management state to the warning state. The pre-warning command is only pushed to administrators and does not drive the device management state machine transition; it also does not trigger a state machine change if it is revoked within the predicted time step. After the device management state transitions to the warning state, the positioning strategy mapping function dynamically upgrades the positioning acquisition strategy to an ultra-wideband time-of-arrival mode, coupled with continuous locking packet transmission of 10 times per second, to achieve automatic locking and tracking of abnormal devices, forming a management event-driven positioning strategy adjustment.

[0124] Furthermore, the connection between the feedback mechanism and the positioning acquisition strategy corresponding to the early warning state is as follows: the early warning trigger event is generated by the feedback of the confirmed early warning command, which drives the device management state to the early warning state; the early warning state corresponds to the ultra-wideband time difference of arrival mode, the positioning refresh frequency of 10 times per second and the wake-up strategy of continuous locking packet transmission in the positioning strategy mapping function, so as to automatically increase the positioning tracking strength of the device after the device abnormality is detected.

[0125] S5. Obtain the device search request and the identity card information of the search initiator. Verify the permissions of the identity card information of the search initiator. If the verification is successful, generate the device search scheduling result.

[0126] In this embodiment of the invention, the step of obtaining the device search request and the identity card information of the search initiator, and verifying the permissions of the identity card information of the search initiator, includes: S901, obtaining the device search request and the identity card information of the search initiator, wherein the device search request includes the target device identifier and the search initiation location.

[0127] S902 verifies the identity card information to obtain the identity verification result.

[0128] S903: When the authentication result is successful, the target device location and target device status corresponding to the target device identifier are determined based on the confirmation warning instruction and the corrected device location information.

[0129] It should be noted that the device search request is initiated by the searcher through the in-hospital device search terminal. The device search request includes the target device identifier and the search initiation location. The target device identifier is the unique identifier of the target device that the searcher wants to find; the search initiation location is the current location of the searcher, which is obtained by the built-in positioning module of the device search terminal.

[0130] It should be noted that the identity card information is the information read from the card when the initiator swipes the identity card through the card reader terminal. This identity card information includes the holder's identity identifier and job level. The holder's job level is used to add level restrictions to the authorized device set, limiting search permissions for highly controlled devices. The card reader terminal and the device search terminal are integrated, simultaneously completing secondary authentication of the identity card when the initiator initiates a device search request.

[0131] It should be noted that the authentication rules used for permission verification are as follows:

[0132] In the formula, This indicates the authentication result; a value of 1 indicates successful authentication, and a value of 0 indicates unsuccessful authentication. Indicates the target device identifier; This represents the set of authorized devices for the search initiator. The set of authorized devices is a pre-configured set of device identifiers that the search initiator has the right to search for and manage. It is uniformly maintained by the hospital's equipment management department in the permission database. When equipment is transferred, handed over, scrapped, or added, the equipment management department will promptly update the authorized device set of the relevant personnel. Indicates the holder's job rank; This indicates the minimum job level required to locate the target device, which is preset based on the target device's current management status and location.

[0133] Furthermore, the specific mapping rules for minimum job level are as follows: When the target equipment is in normal, standby, or operational status, the required minimum job level is the general medical / nursing level; when the target equipment is in emergency status, the required minimum job level is the medical / nursing level involved in emergency care, and will not be downgraded to invalid verification due to the emergency scenario; when the target equipment is in warning status, the required minimum job level is the security level or equipment management level; when the target equipment is located in a restricted area (such as a waste disposal room or non-medical area), the required minimum job level is raised to the security level or equipment management level. These mapping rules are pre-configured by the hospital's equipment management department and can be adjusted according to the hospital's internal management strategies.

[0134] Furthermore, the specific process for authorization verification is as follows: First, the holder's identity identifier and job level are extracted from the identity card information; then, the authorized device set corresponding to the holder's identity identifier is queried from the authorization database, and the minimum required job level is determined based on the target device's current device management status and location; finally, it is determined whether the target device identifier belongs to the authorized device set and whether the holder's job level is not lower than the minimum required job level. If both conditions are met, the authentication result is 1; otherwise, the authentication result is 0. When the authentication result is "authentication failed," a lookup denial message is generated, and subsequent association and path planning operations are not performed. Through secondary authentication of the identity card, it is ensured that only personnel with the corresponding device lookup and management permissions and whose job level meets the requirements can obtain the location and status information of the target device.

[0135] It should be noted that the association between equipment management commands and the revised equipment location information is as follows: using the target equipment identifier as an index, the latest revised coordinates, floor identifier, and room identifier of the target equipment are queried in the revised equipment location information to obtain the target equipment location; the corresponding confirmation warning command for the target equipment is queried in the equipment management commands (i.e., confirmation warning commands) to obtain the target equipment status. Pre-warning commands are only used to notify management personnel and do not participate in determining the target equipment status.

[0136] In this embodiment of the invention, the generation of device search and scheduling results includes: S1001, based on the search initiation location and the target device location, performing path planning in the hospital navigation map to generate a navigation path.

[0137] S1002, merge the navigation path with the target device status to generate the device search and scheduling result.

[0138] It should be noted that the shortest path objective function used for path planning is as follows:

[0139] In the formula, This indicates the optimal navigation path from the location where the search originates to the location of the target device. Indicates candidate paths; Represents the edges in the candidate path; Representing an edge The passage weight.

[0140] Furthermore, the access weights are determined as follows: access weights are determined based on path distance, elevator congestion, inter-floor connectivity, access control permissions, infection control areas, and restrictions on medical equipment access. Longer path distances and more congested elevators result in higher access weights. If a candidate path includes access to a route with insufficient access control, an infection control area, or a route not open to medical equipment, that route is marked as impassable. The priority of emergency access routes is reflected by reducing the access weight of the corresponding route.

[0141] For example, the passage weight can be calculated using the following composite formula:

[0142] In the formula, Representing an edge The passage weight is dimensionless; The normalized value representing the path distance is determined by the ratio of the side length to the maximum side length in the navigation map within the hospital, and the value ranges from 0 to 1. The normalized value representing the degree of congestion in the elevator, ranging from 0 to 1; The value of the restriction penalty item is 1 when the edge contains a passage with insufficient access control, an infection control area, or a passage that is not open to medical equipment; otherwise, it is 0. When the edge is an emergency passage, the weight coefficient α is adjusted to a reduction coefficient of less than 1 to reflect priority passage. , , These are weighting coefficients, with default values ​​of 0.5, 0.3, and 0.2, which can be adjusted by the hospital management department according to actual management needs. For inaccessible edges, [the weighting coefficients are not specified in the original text]. Set it to infinity to ensure that the optimal navigation path does not pass through this type of edge.

[0143] Furthermore, the data sources for elevator congestion levels include: IoT-based passenger flow sensors deployed in the elevator lobby, elevator access control counting devices, or elevator monitoring video analysis systems. These sources obtain real-time congestion levels by statistically analyzing the number of people passing through the elevator lobby per unit time or the elevator car occupancy rate. This real-time congestion level is then normalized to the 0-1 range before being used as input. In the hospital's navigation map, the search initiation location and the target device location are mapped to the starting node and ending node, respectively. Among all candidate paths connecting the starting and ending nodes, the candidate path with the minimum sum of the edge traffic weights is selected as the optimal navigation path.

[0144] It should be noted that the device search and scheduling results are generated as follows: the navigation path and the target device status are merged to generate the device search and scheduling results, which include the navigation path, the target device location, and the target device status. The search initiator can travel to the target device according to the navigation path and determine whether to execute corresponding early warning actions based on the target device status.

[0145] It should be noted that the cumulative usage time formula used for usage time statistics is as follows:

[0146] In the formula, Indicates the first The cumulative usage time of each device within the statistical period, in seconds; Indicates the number of times within the statistical period Number of times the equipment is used; Indicates the first The first piece of equipment The start time of the first use; Indicates the first The first piece of equipment The end time of the next use.

[0147] Further, the implementation method for usage duration statistics is as follows: Based on the corrected device location information and the device management status migration record in S1, when the device management status first migrates to the usage state, the start time of this usage is recorded; when the device management status leaves the usage state and does not return to the usage state within a preset time interval, the time of leaving the usage state is taken as the end time of this usage; the default value of the preset time interval is 5 minutes. If the device management status leaves the usage state and then returns to the usage state within the preset time interval, it is considered the same usage, and the end time is not recorded, while the start time of usage remains unchanged. The difference between the end time and the start time of each usage within the statistical period is used to obtain the duration of a single usage session, and then all the durations of single usage sessions are added together to obtain the cumulative usage duration. If the device migrates from the usage state to the warning state due to a warning trigger and returns to the usage state after the warning is lifted, it is considered the same usage session, and the start time of usage remains unchanged; if the device migrates from the usage state to the emergency state or other non-usage state and does not return to the usage state within the preset time interval, the end time is recorded. Equipment that transitions directly from standby to emergency status due to an emergency call and returns to standby after the emergency is completed is not counted towards usage time. If an equipment usage registration event occurs after returning to standby and the equipment enters usage status, the time of entering usage status corresponding to that equipment usage registration event is taken as the start time of the new usage. This provides data support for equipment procurement decisions.

[0148] In the several embodiments provided by this invention, it should be understood that the disclosed method can be implemented in other ways.

[0149] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for locating and tracking in-hospital equipment based on a medical IoT terminal, characterized in that, The method includes: S1. Obtain the equipment management attribute information and real-time management events of each medical device in the hospital, construct the equipment management state machine, and obtain the equipment management status of each medical device; S2. Configure the positioning acquisition strategy based on the device management status and collect positioning signal data to obtain the real-time location coordinates of each medical device. S3. Based on the real-time location coordinates of each medical device, perform map constraint correction and floor / room affiliation determination to obtain the corrected device location information; S4. Based on the corrected device location information, generate trajectory intention prediction results, and then generate advance warning instructions and confirmation warning instructions, and transmit the confirmation warning instructions to the device management state machine; S5. Obtain the device search request and the identity card information of the search initiator. Verify the permissions of the identity card information of the search initiator. If the verification is successful, generate the device search scheduling result.

2. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The process of acquiring equipment management attribute information and real-time management events for each medical device within the hospital, constructing an equipment management state machine, and obtaining the equipment management status of each medical device includes: S201, Obtain equipment management attribute information, which includes equipment identification, emergency response timeliness score, mobility frequency score, and asset control level score; S202, Obtain real-time management events, which include equipment usage registration events, usage end events, emergency call events, emergency end events, warning trigger events, and warning cancellation events; S203. Initialize the equipment management status of each medical device based on the equipment management attribute information, and construct the equipment management state machine. The equipment management status includes normal state, standby state, use state, emergency state and warning state. S204, based on real-time management events, drives the device management state machine to perform state transitions through state transition functions to obtain the device management status of each medical device.

3. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The configuration of the positioning acquisition strategy based on the device management status and the acquisition of positioning signal data include: S301, based on the device management status, the positioning mode, positioning refresh frequency, and wake-up strategy for each medical device are determined through a positioning strategy mapping function to obtain the positioning acquisition strategy. The positioning strategy mapping function includes: when the device management status is in emergency mode, the positioning mode is ultra-wideband time difference of arrival mode, and the positioning refresh frequency is 10 times per second; when the device management status is in use mode, the positioning mode is Bluetooth angle of arrival mode, and the positioning refresh frequency is once every 2 seconds; when the device management status is in normal mode, the positioning mode is Bluetooth signal strength mode, and the positioning refresh frequency is once every 5 minutes; when the device management status is in standby mode, the device tag enters deep sleep, and the positioning refresh frequency is once every 10 minutes; when the device management status is in early warning mode, the positioning mode is ultra-wideband time difference of arrival mode, the positioning refresh frequency is 10 times per second, and the wake-up strategy is continuous lock packet transmission; the positioning mode also includes ultra-high frequency radio frequency identification access control mode. S302 collects positioning signal data of each medical device based on the wake-up strategy and positioning refresh frequency; among them, the UHF RFID access control mode is passively triggered by the access control reader when the device tag passes through the reading range, and is not constrained by the positioning refresh frequency and wake-up strategy.

4. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The process of obtaining the real-time location coordinates of each medical device includes: S401, based on positioning signal data, performs position analysis using a position analysis method corresponding to the positioning mode to obtain the real-time position coordinates of each medical device; the position analysis method includes at least one of position analysis based on time difference of arrival measurement, position analysis based on angle of arrival measurement, and position analysis based on signal strength measurement; wherein the UHF RFID access control mode only records the discrete position points of the device when it passes through the access control and does not participate in continuous position analysis. S402, When the device management state changes, the positioning strategy mapping function is re-executed to update the positioning acquisition strategy.

5. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The process involves correcting map constraints and determining floor and room affiliation based on the real-time location coordinates of each medical device to obtain corrected device location information, including: S501 acquires the rasterized map of the building information model within the compound, landmark beacon signals, and barometer data; S502 performs Kalman filtering on the real-time position coordinates to obtain the filtered position coordinates and velocity estimates. S503, based on the rasterized map of the building information model, applies validity constraints to the filtered location coordinates, removes invalid location points that fall inside the walls or unreachable partitions, and obtains the constrained location coordinates; S504, the floor and room assignment determination is based on a dual verification of landmark beacon signals and barometer data to obtain the floor and room assignment result; wherein the floor and room assignment determination includes: obtaining the room assignment result by room adsorption based on landmark beacon signals, calculating the air pressure height difference based on barometer data and triggering floor switching only when the absolute value of the air pressure height difference is greater than a preset floor switching threshold to obtain the floor assignment result, and verifying the room assignment result with the floor assignment result to obtain the floor and room assignment result; S505 combines the constrained position coordinates, velocity estimates, and floor / room assignment results to obtain the corrected equipment location information; the corrected equipment location information includes corrected coordinates, velocity estimates, floor identifiers, and room identifiers.

6. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The generation of trajectory intent prediction results based on the corrected device location information includes: S601, Obtain building space label data. The building space label data includes the area type of each area, which includes normal medical area, corridor, sewage room and non-medical area. S602, Based on the corrected coordinates and velocity estimation in the corrected equipment position information, the trajectory extrapolation of the equipment's future position is performed to obtain the predicted position coordinates; S603, determine the region type of the area into which the predicted position coordinates fall, and obtain the trajectory intention prediction result.

7. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The generation of the advance warning command and the confirmation warning command includes: S701 generates advance warning commands based on trajectory intent prediction results; S702: Based on the corrected equipment location information, determine the dwell time of the equipment after it actually enters the restricted area, confirm the advance warning command, and generate a confirmation warning command; specifically, based on the corrected coordinates and speed estimation in the corrected equipment location information, perform trajectory extrapolation to obtain the predicted position coordinates, determine whether the area where the predicted position coordinates fall belongs to the restricted area, the restricted area includes the waste room and non-medical area, if so, generate the advance warning command; when the equipment actually enters the restricted area and the dwell time is greater than or equal to the preset dwell time confirmation threshold, upgrade the advance warning command to a confirmation warning command.

8. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The step of transmitting the confirmation warning command to the device management state machine includes: Confirmation warning commands are transmitted to the equipment management state machine as equipment management commands; advance warning commands are only pushed to management personnel and are not transmitted to the equipment management state machine.

9. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The process of obtaining the device search request and the identity card information of the search initiator, and verifying the permissions of the identity card information of the search initiator, includes: S901, Obtain the device search request and the ID card information of the search initiator. The device search request includes the target device identifier and the search initiation location. S902, verify the identity card information to obtain the identity verification result; S903: When the authentication result is successful, the target device location and target device status corresponding to the target device identifier are determined based on the confirmation warning instruction and the corrected device location information.

10. The in-hospital equipment location and tracking method based on a medical IoT terminal as described in claim 1, characterized in that, The generation device search scheduling result includes: S1001, based on the location of the initiating location and the location of the target device, performs path planning in the internal navigation map and generates a navigation path; S1002, merge the navigation path with the target device status to generate the device search and scheduling result.

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