Smart wearable devices for sanitation emergency operations

Abstract

This invention discloses a smart wearable device for sanitation emergency operations, comprising a shell, a fixing mechanism, a sensing and positioning module, and a controller. The shell integrates a biosensing window, a check-in button, and an active safety warning module. The controller is used to recognize check-in signals and switch operation modes; when responding to emergency tasks, it calculates the thermal pressure load index based on personnel age, physiological characteristics, and environmental microclimate, and determines the matching degree between personnel and tasks based on spatial distance; after successful matching, it automatically broadcasts the tool carrying list and drives the warning module to emit corresponding flashing signals; during operation, it compares the action posture with the standard operation model in real time, identifies valid operation actions, and automatically marks progress. This invention realizes scientific scheduling, material linkage reminders, active safety protection, and automatic attendance acceptance for sanitation emergency operations.

Description

Technical Field

[0001] This invention belongs to the field of sanitation operation management technology, and specifically relates to an intelligent wearable device for sanitation emergency operations. Background Technology

[0002] Urban sanitation operations are a crucial part of maintaining the normal operation of a city. In addition to daily cleaning and maintenance, the ability to respond to emergencies (such as oil spills on the road, overflowing garbage, and snow and water accumulation) is a key indicator for measuring the level of sanitation management. Traditional sanitation dispatching models mainly rely on the geographical location of workers (BeiDou positioning). When emergency tasks are issued, the system often simply follows the principle of shortest distance for dispatching tasks.

[0003] However, existing sanitation operation and dispatching equipment has the following main shortcomings: The lack of comprehensive consideration of the physiological and environmental factors of sanitation workers is a significant issue. Sanitation workers are generally elderly, and their work environments are mostly outdoor. Dispatch methods based solely on distance ignore the workers' current physical condition (e.g., fatigue) and the impact of environmental microclimates (e.g., high temperature and humidity). Assigning physically demanding emergency tasks to workers at critical thermal stress levels greatly increases the risk of heatstroke or cardiovascular accidents.

[0004] Passive protection has blind spots: sanitation workers typically rely solely on reflective vests for passive warning when performing street cleaning or emergency tasks. In situations with poor visibility (such as at night or in fog or haze) or when attention is diverted, passive reflection is unlikely to attract the attention of vehicles traveling at high speeds, resulting in a higher risk of traffic accidents.

[0005] Disconnect between task and material information: Emergency tasks are diverse, and the tools required for different tasks vary greatly (e.g., snowplows are needed for snow removal, and absorbents are needed for oil removal). Existing equipment usually only notifies the location and lacks strong correlation reminders about the tools to be carried, resulting in personnel arriving on site but being unable to start work immediately due to the lack of tools, causing secondary delays.

[0006] Difficulties in monitoring and interacting with the work process: Sanitation workers typically wear heavy gloves while working, making it difficult to use touchscreens for complex task confirmations or progress reports. Current monitoring methods rely heavily on manual patrols or fixed-point check-ins, which cannot verify whether workers have actually performed effective cleaning actions, easily leading to situations where workers are not actively engaged in cleaning or simply show up at their posts without actually working.

[0007] Therefore, there is an urgent need for a smart wearable device that can comprehensively assess environmental and physical conditions, provide active safety protection, and enable touchless task acceptance. Summary of the Invention

[0008] In view of this, the main objective of the present invention is to provide an intelligent wearable device for emergency sanitation operations.

[0009] To achieve the above objectives, the technical solution of the present invention is implemented as follows: A smart wearable device for emergency sanitation operations includes: The casing integrates a biosensing window, a physical attendance button, and an active safety warning module; A fixing mechanism, connected to the housing, for securing the equipment to the wrist or shoulder of a sanitation worker, includes a mechanical buckle with a self-locking function; The sensing and positioning module is arranged inside the housing and is used to collect real-time geographical location data, work posture data, and microclimate data of the current work environment of sanitation workers in online operation mode. The controller, housed within the casing and electrically connected to the sensing and positioning module, biosensor window, physical check-in button, and active safety warning module, is used to identify the operation signal of the physical check-in button and switch the sanitation worker corresponding to the smart wearable device from off-duty mode to online operation mode. It is also used to respond to sanitation emergency tasks and, by combining the sanitation worker's age profile, physiological data collected through the biosensor window, and microclimate data of the current working environment, determine the thermal stress load index. Based on the geographical location data, it determines the spatial distance between the sanitation worker and the sanitation emergency task location, and combines the spatial distance and the thermal stress load index to determine the matching degree between the sanitation worker and the sanitation emergency task. Upon successful matching, it automatically associates and broadcasts the sanitation tool carrying list according to the sanitation emergency task type, and simultaneously drives the active safety warning module to emit a flashing warning signal corresponding to the task type. During operation, it compares the work actions and postures with a preset sanitation standard operation model in real time. When a valid work action matching the task characteristics is identified and continues for a preset duration, the task progress is automatically marked.

[0010] Preferably, the microclimate data includes at least ambient temperature and relative humidity; the physiological data includes at least the current heart rate of the sanitation worker. The controller is used to determine the thermal stress load index by comprehensively considering the age profile, current heart rate, ambient temperature, and relative humidity of the sanitation workers; specifically, it is used to... Determine the thermal pressure load index, where, The current heart rate value is collected in real time by the biosensor window. The data contains the ages of sanitation workers stored in the equipment. The ambient temperature is from the current operational environment microclimate data. This represents the percentage of relative humidity in the current working environment's microclimate data. and The preset weighting coefficients, and + =1.

[0011] Preferably, the controller is specifically used to determine the spatial distance between sanitation workers and the location of sanitation emergency tasks based on the geographic location data. ,according to Determine the degree of matching ;in, This refers to the spatial distance between the device and the task location calculated based on the aforementioned geographical location data. The preset maximum effective response radius; This refers to the thermal pressure load index; This is a priority adjustment factor based on task type; Spatial distance weights As physiological load weight, Weights for task types.

[0012] Preferably, the active safety warning module includes a high-brightness LED array or laser projection unit surrounding the side of the housing; The controller is specifically used to drive the LED array to emit a high-frequency orange strobe signal when the sanitation emergency task is road sweeping or sewage discharge; to drive the LED array to emit a low-frequency, high-brightness blue breathing signal when the sanitation emergency task is snow removal or extreme weather operation; and to activate the laser projection unit to project a safety warning light circle under the feet of the sanitation worker when it is detected that the sanitation worker is located in the motor vehicle lane and the ambient light is lower than the safety threshold.

[0013] Preferably, the controller is specifically used to input the collected acceleration and angular velocity data into the sanitation standard operation model for feature extraction, and the identified action types include sweeping action, shoveling action and bending over to pick up action; when the identified action type is logically consistent with the type of emergency task currently issued, and the action frequency and amplitude meet the characteristics of effective operation, the effective operation time is accumulated.

[0014] Preferably, the controller is further configured to pre-store a task mapping table including the list of sanitation tools carried; The controller is also used to, when broadcasting the list of sanitation tools, if the sensing and positioning module detects that the distance between the current geographical location and the task target point has shortened to a preset range, but no sanitation workers have been detected to be staying or preparing materials, increase the volume of the voice broadcast and trigger a vibration reminder to perform a secondary material verification.

[0015] Preferably, the biosensing window is made of high-transmittance optical glass, and its outer surface is covered with an oleophobic and anti-fouling coating. The controller is also used to detect detachment through the biosensor window. If the biosensor window does not receive a valid photoelectric reflection signal within a preset time, it is determined that the smart wearable device is in a non-wearing state, automatically suspends the online operation mode, and sends an abnormal offline alarm to the background.

[0016] Preferably, the controller is also used to perform a fall assistance and rescue function; when it is determined from the work posture data that a sanitation worker has fallen and no active getting-up action is detected subsequently within a preset time, the controller controls the active safety warning module to emit an SOS Morse code flashing signal and broadcasts a distress signal to other similar smart wearable devices within a preset radius through the wireless communication module.

[0017] Preferably, a pressure sensor is also integrated inside the housing; The controller is also used to combine the geographical location data and the barometric pressure sensor data to determine the floor or altitude of the sanitation worker, so as to distinguish between elevated bridge operations and ground operations, and to perform differentiated weighting of physical load for workers at different altitudes during task matching.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention breaks through the limitations of traditional task matching based solely on distance. By comprehensively collecting data on the age profiles of sanitation workers, real-time physiological characteristics, and microclimate data of the current working environment, the controller calculates a thermal stress load index. When assigning emergency tasks, both spatial distance and the thermal stress load index are considered, avoiding the allocation of high-intensity emergency tasks to workers in high-temperature and high-humidity environments or those experiencing physiological overload. This effectively prevents occupational health risks (such as heatstroke) in sanitation work, achieving human-centered intelligent scheduling. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and, together with their descriptions, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the structure of a smart wearable device for emergency sanitation operations provided in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] In the accompanying drawings of this embodiment, the same or similar reference numerals correspond to the same or similar components. In the description of this invention, it should be understood that the terms "upper," "lower," "left," "right," "inner," "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the accompanying drawings are only for illustrative purposes and should not be construed as limiting this patent. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0022] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0023] This invention provides a smart wearable device for emergency sanitation operations, such as... Figure 1 As shown, it includes: The housing 100 integrates a biosensing window, a physical attendance button 101, and an active safety warning module; A fixing mechanism 200, connected to the housing 100, is used to fasten the equipment to the wrist or shoulder of the sanitation worker, and includes a mechanical buckle with a self-locking function. The sensing and positioning module 300 is arranged inside the housing 100 and is used to collect the geographical location data, work posture data and microclimate data of the current work environment of sanitation workers in real time during online operation mode. The controller 400, housed inside the housing 100, is electrically connected to the sensing and positioning module 300, the biosensing window, the physical check-in button 101, and the active safety warning module. It is used to identify the operation signal of the physical check-in button 101, switching the sanitation worker corresponding to the smart wearable device from off-duty mode to online operation mode. It is also used to respond to sanitation emergency tasks and, based on the sanitation worker's age profile, physiological data collected through the biosensing window, and microclimate data of the current working environment, determines the thermal pressure load index and, according to the geographical location data... The spatial distance between sanitation workers and the location of sanitation emergency tasks is determined, and the matching degree between the sanitation workers and the sanitation emergency tasks is determined by combining the spatial distance with the thermal pressure load index. After successful matching, the sanitation tool carrying list is automatically associated and broadcast according to the sanitation emergency task type, and the active safety warning module is driven to emit a flashing warning signal corresponding to the task type. During the operation, the operation posture is compared with the preset sanitation standard operation model in real time. When a valid operation posture that meets the task characteristics is identified and continues for a preset duration, the task progress is automatically marked.

[0024] This invention breaks through the limitations of traditional task matching based solely on distance. By comprehensively collecting data on the age profiles of sanitation workers, real-time physiological characteristics, and microclimate data of the current working environment through the controller 400, a thermal stress load index is calculated. When assigning emergency tasks, both spatial distance and the thermal stress load index are considered, avoiding the allocation of high-intensity emergency tasks to workers in high-temperature and high-humidity environments or those with excessive physiological load. This effectively prevents occupational health risks (such as heatstroke) in sanitation work and achieves human-centered intelligent scheduling.

[0025] This invention integrates an active safety warning module and deeply binds its operating mode to emergency task types. The smart wearable device is not only a passive positioning terminal but also an active safety defense shield. Upon successful pairing, the controller 400 drives the module to emit corresponding strobe warning signals according to the task type (e.g., high-frequency flashing during road work), significantly improving the visibility of sanitation workers in hazardous working environments at the physical level and reducing the traffic accident rate.

[0026] Addressing the pain point of sanitation workers' inconvenience in operating gloves, this invention compares their work movements and postures with preset standard sanitation operation models (such as sweeping and shoveling). Task progress is automatically marked only when a valid action matching the identified characteristics is continuously performed for a preset duration. This not only solves the interaction problem and achieves seamless attendance tracking, but also effectively prevents false attendance (being present but not working), thus improving management efficiency.

[0027] This invention automatically associates and broadcasts the list of sanitation tools carried during the task assignment phase, solving the information asymmetry problem of personnel arriving but equipment not arriving during emergency response. It ensures that operators know the required equipment before departure, improving the success rate and response speed of emergency response.

[0028] In some embodiments, the housing 100 adopts a corrosion-resistant sealing structure with a protection level of not less than IP67. Combined with a biosensor window and a mechanical buckle with a self-locking function, it ensures that the equipment can still work stably in harsh environmental sanitation environments filled with dust, water vapor, and corrosive substances, and is not easy to accidentally fall off during strenuous operations.

[0029] In some embodiments, the microclimate data includes at least ambient temperature and relative humidity; the physiological data includes at least the current heart rate of the sanitation worker. The controller 400 is used to determine the thermal pressure load index by comprehensively considering the age profile, current heart rate, ambient temperature and relative humidity of the sanitation workers. Specifically, the controller 400 performs real-time calculation of the thermal stress load index through an internally integrated algorithm engine. This calculation process relies on the input of four core variables: the current heart rate value acquired in real time through a biosensor window. The age of personnel pre-stored in the device's memory and ambient temperature collected by environmental sensing sensors. and relative humidity percentage for.

[0030] The controller 400 determines the thermal pressure load index according to the following formula. : , and The preset weighting coefficients, and + =1.

[0031] In this computational model, through These characterize physiological load factors. Among them, A commonly used formula in sports medicine for estimating maximum heart rate was employed to define the cardiac limits of workers in this specific age group. Real-time heart rate was then used. By comparing the current rate to this limit, the current cardiovascular load of the worker can be quantified intuitively. For example, for a 50-year-old sanitation worker, the theoretical maximum heart rate is 170 bpm; if the current heart rate reaches 136 bpm, the coefficient value is 0.8, indicating that the worker is already in a state of high-intensity physical exertion.

[0032] The environmental thermal stress factor is characterized, where 37 represents the standard human core body temperature (degrees Celsius), which is the environmental temperature. Normalized to body temperature, it reflects the intensity of thermal radiation from external heat sources to the human body. Simultaneously, it introduces... As a correction factor, the inhibitory effect of humidity on the human body's heat dissipation mechanism is fully considered. In sanitation work scenarios (especially after rain or on humid days), high humidity hinders sweat evaporation, causing the perceived temperature to be much higher than the actual air temperature. Through this product term, the algorithm can sensitively capture the dual pressure that high temperature and high humidity environments place on the human body's thermal regulation system.

[0033] Weighting coefficient and The settings (satisfy) + =1) Used to balance the influence weights of internal and external factors. For example, the default setting... =0.6, =0.4, meaning it focuses more on the body's own physiological responses. However, it detects a sudden increase in ambient temperature (such as...). When the temperature exceeds 35℃ or a special seasonal mode is entered, the controller 400 can dynamically adjust. The value (e.g., increased to 0.6) is used to improve the system's sensitivity to environmental risks and trigger early warnings.

[0034] Based on calculations If the value is not specified, controller 400 will execute a tiered response strategy: safe zone ( <0.7: This indicates that the sanitation worker is in good condition, can normally receive all types of emergency tasks, including heavy physical labor (such as snow shoveling and transportation), and has a high priority in the matching algorithm.

[0035] Warning range (0.7≤ <0.9): The sanitation worker is determined to be in a sub-healthy or mildly fatigued state. In this case, the controller 400 will reduce its weight in the distance-first matching strategy, and block high-intensity tasks (such as continuous bending over work), allowing only light tasks (such as road patrol) to be assigned, while sending a reminder to replenish water through equipment vibration.

[0036] Danger zone ( ≥0.9): This indicates that sanitation workers face an extremely high risk of heatstroke or cardiovascular accidents. The controller 400 will immediately lock the online operation mode, stop distributing any new tasks to the sanitation workers corresponding to the smart wearable device, and drive the active safety warning module to emit a red SOS flashing signal. At the same time, it will automatically send a health emergency alarm to the back-end management center to achieve timely intervention and rescue.

[0037] In some embodiments, the controller 400 is specifically configured to determine the spatial distance between sanitation workers and sanitation emergency task locations based on the geographic location data. ,according to Determine the degree of matching ;in, This refers to the spatial distance between the device and the task location calculated based on the aforementioned geographical location data. The preset maximum effective response radius; This refers to the thermal pressure load index; This is a priority adjustment factor based on task type; Spatial distance weights As physiological load weight, Weights for task types.

[0038] Specifically, the spatial distance The distance between the device's current location and the mission target point is calculated based on the device's BeiDou positioning data. In specific implementations, the controller 400 can call its built-in GIS engine to calculate the straight-line Euclidean distance, or combine it with an electronic map API to obtain the actual road network travel distance, thereby improving accuracy.

[0039] The preset maximum effective response radius (For example, set to 3000 meters); the aforementioned This is a normalized distance utility factor; the closer the distance, the closer the value is to 1, representing the highest response timeliness; when the distance exceeds... If this value is zero or negative, it means that the person is too far away and has lost the qualification for optimal response, thus ensuring the basic requirement of second-level response for emergency tasks.

[0040] As a physiological safety reserve factor, among which, The higher the value, the more fatigued the sanitation workers are or the harsher the environment; the corresponding (1- The lower the score, the better. For example, when a sanitation worker is very close to the site (high score for the first item), but is in a state of severe fatigue (…), the score is lower. When the score is approximately 0.9, the low score of the second item will significantly reduce the degree of matching. The total score is used to avoid assigning emergency tasks to personnel in poor physical condition, effectively mitigating sudden health risks during operations.

[0041] The priority correction coefficient based on task type Instead of fixed values, these are dynamically generated based on the match between the task type and the personnel profile. For example, when the emergency task is cleaning oil stains on the road (requiring delicate operations but moderate physical exertion), the profile of all sanitation workers will be dynamically generated. Set to a base value (e.g., 0.5); however, when the task is snow removal or clearing fallen trees (which are physically demanding, urgent, and dangerous tasks), the controller 400 will read the personnel's age profile. If the personnel's age... For individuals over 55 years old, the controller 400 will automatically assign a negative correction value (e.g., ...). =-0.3), to reduce the probability of elderly people being selected for heavy physical tasks; conversely, for young and middle-aged people, positive incentives are given (such as... =+0.8), thereby achieving refined scheduling of personnel and job matching.

[0042] The spatial distance weight Physiological load weight Task type weight For example, in the emergency rescue and disaster relief mode, timeliness is the top priority, and automatic adjustments are made. In high-temperature warning mode, safety is the top priority, and the temperature is automatically adjusted. Ultimately, the controller 400 will evaluate all sanitation workers in the candidate pool. Sort the results and select the highest scores that exceed a preset threshold (e.g., ...). The personnel with a score >0.6 are selected as the best executors, and task instructions are sent to them.

[0043] In some embodiments, the active safety warning module includes a high-brightness LED array or laser projection unit surrounding the side of the housing 100; The controller 400 is specifically used to drive the LED array to emit a high-frequency orange strobe signal when the sanitation emergency task is road sweeping or sewage discharge; to drive the LED array to emit a low-frequency high-brightness blue breathing signal when the sanitation emergency task is snow removal or extreme weather operation; and to activate the laser projection unit to project a safety warning light circle under the feet of the sanitation worker when it is detected that the sanitation worker is located in the motor vehicle lane and the ambient light is lower than the safety threshold.

[0044] Specifically, the high-brightness LED array consists of multiple full-color (RGB) SMD LEDs, evenly distributed within the translucent sidewall of the housing 100, achieving a 360-degree ring-shaped light emission effect without blind spots. Furthermore, a micro laser projection unit is integrated at a 45-degree angle diagonally below the housing 100 towards the ground, used to project high-contrast graphic signals onto the ground in specific high-risk scenarios.

[0045] The controller 400 executes differentiated light-based warning strategies based on the type of emergency task received, using different colors and flashing frequencies to produce specific psychological warning effects on drivers of surrounding vehicles: High-frequency orange strobe mode (for mobile operations): When the controller 400 determines that the current emergency task is road cleaning or sewage disposal, these tasks typically involve frequent movement or crouching of personnel on the road. The controller 400 will drive the LED array to emit a high-frequency (e.g., 2Hz~4Hz) orange strobe signal, which can simulate the warning light effect of large construction vehicles. Utilizing the human eye's instinctive sensitivity to rapidly flashing light, it instantly evokes the subconscious awareness of passing drivers to avoid the construction site from a distance, thereby creating a visual safety barrier in solo operation scenarios without the cover of large vehicles.

[0046] Low-frequency blue breathing mode (for severe weather): When the controller 400 determines that the current emergency task is snow removal or extreme weather operations (such as heavy rain or dense fog), the controller 400 will drive the LED array to emit a low-frequency (e.g., 0.5Hz) high-brightness blue breathing signal. In snow-covered white environments or rain / fog refraction environments, traditional yellow or red light is easily confused with streetlights or car taillights, and can easily cause visual fatigue due to snow reflection. High-brightness blue light has extremely high contrast (warm and cool contrast) against a white background and has strong penetrating power. Using a breathing mode (gradual brightening and fading) instead of strobe is intended to reduce battery power consumption during long-term snow removal operations and to avoid glare on highly reflective snow, which could interfere with the vision of sanitation workers.

[0047] Laser projection defense mode (for high-risk blind spots): The controller 400 monitors geographic location data and ambient light levels in real time. When high-precision positioning determines that a sanitation worker is within the vehicle lane and the ambient light level indicated by the light sensor is below the safety threshold (such as entering a dark environment at night, in a tunnel, or during heavy rain), the controller 400 will automatically activate the laser projection unit. This will project a bright red or green safety warning circle (or a dynamic light spot with a "No Entry" icon) with a diameter of approximately 1.5 meters onto the ground beneath the sanitation worker's feet and around them. The large area of ​​light on the ground will force the driver to instinctively steer to avoid the worker, thus gaining valuable survival space before a vehicle collision occurs.

[0048] In some embodiments, the controller 400 is specifically used to input the collected acceleration and angular velocity data into the sanitation standard operation model for feature extraction. The identified action types include sweeping action, shoveling action, and bending over to pick up action. When the identified action type is logically consistent with the type of emergency task currently issued, and the action frequency and amplitude meet the characteristics of effective operation, the effective operation time is accumulated.

[0049] Specifically, the controller 400 uses a built-in nine-axis inertial measurement unit (including a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer) in conjunction with a high-precision barometric pressure sensor and BeiDou positioning data to achieve multi-dimensional motion feature extraction and authenticity verification.

[0050] Considering the risks of misjudgment and cheating associated with using a single sensor, the controller 400 employs a multi-sensor spatiotemporal feature fusion algorithm for valid action determination, specifically including: The controller 400 not only identifies periodic reciprocating acceleration (0.5Hz~2Hz) in the horizontal plane through a nine-axis inertial measurement unit, but also extracts the low-speed displacement vector output by the Beidou positioning module. Only when periodic arm swings are detected, and the Beidou positioning shows that the person maintains a continuous micro-step displacement of 0.5m / s~1.5m / s within the work area, is the sweep considered valid. This effectively filters out spurious work (loafing around) behavior such as standing still and shaking the arm.

[0051] To address the technical challenge of directly reflecting torso posture when smart wearable devices are worn on the wrist, the controller 400 integrates acceleration and barometric pressure data. When the accelerometer detects that the arm's Z-axis is pointing downwards and undergoing high-frequency micro-movements (simulating a picking-up action), it simultaneously retrieves data from the barometric pressure sensor to calculate the device's altitude change. If the relative altitude calculated from the barometric pressure drops by 0.5 to 1 meter within a very short time and then recovers, the arm movement is combined with the precise determination of a bending-down picking-up action, significantly improving the accuracy of torso movement recognition by a single wrist-worn device.

[0052] The controller 400 incorporates a lightweight temporal action classification model based on a Long Short-Term Memory (LSTM) network. The raw nine-axis data, after being stripped of gravitational acceleration using a Kalman filter, is converted into quaternion attitude angles and input into the LSTM network. This model can learn the complete temporal context of the action (such as the continuous shovel-lifting-throwing features), effectively eliminating high-frequency interference actions such as daily walking, drinking water, or making phone calls. It can accurately identify and distinguish the kinematic features of the following typical sanitation worker actions: Sweeping motion: Characterized by a significant periodic reciprocating acceleration in the horizontal plane, accompanied by regular changes in the rotational angular velocity of the wrist or arm, corresponding to the scenario of sweeping the road with a broom; Shovel lifting action: Characterized by a complex motion trajectory of squatting-forward rushing-lifting-throwing, with a significant explosive acceleration peak on the vertical axis (Z-axis), corresponding to snow shoveling or shoveling silt. Bending over to pick up: Characterized by a large, slow change and recovery of the torso's tilt angle, accompanied by high-frequency micro-movements of the hands at the lowest point, corresponding to scenarios of picking up large pieces of trash or cleaning sewer grate.

[0053] After classifying the actions, the controller 400 reads the type of the currently issued emergency task. If the emergency task type is snow removal, the expected dominant action to be detected should be shoveling; if the emergency task type is road cleaning, the algorithm expects the expected dominant action to be sweeping or bending over to pick up. If the detected action is significantly inconsistent with the task type (for example, in a snow removal task, personnel remain stationary for a long time or only walk), the controller 400 will determine the current time period as invalid work time.

[0054] To prevent operators from falsifying work data by slightly shaking their arms, the controller 400 sets strict thresholds for valid work characteristics.

[0055] Amplitude threshold: The acceleration vector of the action must exceed a preset strength benchmark (e.g., greater than 1.5g) to confirm that the operator is indeed applying force; Frequency threshold: The frequency of periodic movements must fall within a reasonable ergonomic range (e.g., the frequency of sweeping movements should be between 0.5 Hz and 2 Hz).

[0056] The controller 400 will start the timer to accumulate the effective working time only when the identified action type is correct and its force and frequency meet the standards.

[0057] When the accumulated effective working time reaches the preset standard of the task (for example, for a fixed-point snow shovel task, the effective shovel lifting time accumulates to 20 minutes), the controller 400 automatically generates a task completion report and uploads it to the cloud without manual intervention, realizing a fully digital and quantitative assessment of the sanitation operation process.

[0058] In some embodiments, the controller 400 is further configured to pre-store a task mapping table including the sanitation tool carrying list; The controller 400 is also used to, when broadcasting the list of sanitation tools, if the sensing and positioning module 300 detects that the distance between the current geographical location and the task target point has shortened to a preset range, but no sanitation workers have been detected to be staying or preparing materials, increase the volume of the voice broadcast and trigger a vibration reminder to perform a secondary material verification.

[0059] Specifically, the controller 400's non-volatile storage module pre-programs or synchronizes a task mapping table with the cloud. This table constructs a logical association matrix between various emergency tasks and essential operational materials. For example, when the task type is marked as road oil stain cleaning, the associated material list includes oil-absorbing mats, strong degreasing agent, and stiff brushes; when the task type is marked as emergency repair of missing manhole covers, the associated material list includes warning cones, spare manhole covers, and crowbars; when the task type is marked as snow and ice removal, the associated material list includes industrial de-icing salt, flat-headed shovels, and anti-skid chains.

[0060] Based on this task mapping table, when a new emergency task instruction is received, the controller 400 immediately parses the task type code, retrieves the task mapping table, and generates a voice synthesis instruction. Through the built-in speaker or headphones, it broadcasts to sanitation workers, "Snow removal task received. Please confirm that you have a snowplow and de-icing agent." At this point, it is assumed that the workers are in a state of preparation for departure.

[0061] The controller 400 uses the sensing and positioning module 300 to continuously monitor the real-time distance between the operator and the task target point. A critical decision-making distance threshold is set (e.g., 500 meters from the site or 5 minutes remaining until estimated arrival). When a threshold is detected... When the distance is reduced to the critical decision-making distance threshold, the controller 400 automatically initiates behavior pattern analysis. It combines BeiDou positioning speed data and IMU attitude data to determine the personnel's current activity status: if it detects pausing or material preparation actions, and if positioning data shows that the personnel lingered for more than a preset time (e.g., 60 seconds) while passing the nearest sanitation tool room or tool vehicle, or if IMU data identifies characteristic bending over to pick up items or opening a container door, the controller 400 determines that the materials are likely ready and remains silent to avoid interfering with driving or movement. If it is determined that the personnel are heading directly to the site without preparation: if positioning data shows that the personnel maintain a constant speed (while driving or riding) and have not stopped at any material station, the controller 400 will determine that there is a high risk of forgetting to bring tools. At this time, the controller 400 triggers the strong intervention verification mode, automatically increases the volume of the voice broadcast to the maximum safe decibel above the environmental noise benchmark, and switches to an urgent prompt tone: "Arriving at the site soon. The system has detected that no items have been retrieved. Please confirm that the supplies are complete!" It drives the linear motor (LRA) to trigger high-intensity intermittent vibrations (such as a "long vibration-short vibration" cycle).

[0062] In some embodiments, the biosensing window is made of high-transmittance optical glass, and its outer surface is covered with an oleophobic and anti-fouling coating. The controller 400 is also used to detect detachment through the biosensor window. If the biosensor window does not receive a valid photoelectric reflection signal within a preset time, it is determined that the smart wearable device is in a non-wearing state, automatically suspends the online operation mode, and sends an abnormal offline alarm to the background.

[0063] Specifically, due to the large amounts of dust, sewage, and grease present in sanitation work environments (such as in food waste disposal scenarios), as well as high-intensity physical friction, ordinary plastic or general-purpose glass materials are easily scratched or covered with stains, leading to light path blockage. Therefore, the biosensor window in this embodiment is made of a high-transmittance optical glass material (such as sapphire glass or Corning Gorilla Glass), which has an extremely low light attenuation rate for specific wavelengths (such as 525nm green light or 940nm infrared light). More importantly, the outer surface of the biosensor window is coated with an AF (Anti-Fouling) oleophobic and anti-fouling coating using a vacuum evaporation process. This coating has extremely low surface energy, preventing water droplets or oil stains from spreading on the window surface (the contact angle is typically greater than 110 degrees).

[0064] The controller 400 drives an internal light-emitting diode (LED) to emit a probe beam through the biosensing window and continuously monitors the echo signal received by a photodiode (PD). Under normal wear conditions, the echo signal contains an alternating current (AC) component that varies periodically with the heartbeat. If the controller 400 detects any of the following abnormal characteristics in the photoelectric reflection signal, and the duration exceeds a preset time threshold (e.g., 10 seconds): a) The received light intensity is extremely high and without fluctuation (usually indicating that the device has fallen off and the window is directly exposed to strong ambient light); b) The received light intensity is close to the dark current level (usually indicating that the device is suspended or the sensor is blocked by a non-biological object); c) Although the signal is present, it lacks the typical microvascular pulsation frequency characteristics of the human body.

[0065] Once the above conditions are met, the controller 400 immediately determines that the device is not being worn and automatically pauses the device's online operation mode, immediately stops accumulating the personnel's effective working hours, and pauses the marking of the Beidou positioning trajectory during operation to prevent the generation of false operation data. The controller 400 generates an abnormal offline alarm data packet containing the detachment timestamp and the last known location, and sends it to the back-end management center with the highest priority. The device screen automatically locks and displays a prompt to wear the device, accompanied by a brief vibration, to remind the operator to check whether the device has accidentally slipped off, ensuring asset safety.

[0066] In some embodiments, the controller 400 is further configured to perform a fall assistance and rescue function; when it is determined from the work posture data that a sanitation worker has fallen and no active getting-up action is detected subsequently within a preset time, the controller controls the active safety warning module to emit an SOS Morse code flashing signal and broadcasts a distress signal to other similar smart wearable devices within a preset radius via a wireless communication module.

[0067] Specifically, the vector sum of triaxial accelerations is calculated in real time. When an acceleration value is detected to first drop sharply (weightlessness characteristic) and then rise sharply (impact characteristic) within a very short time (e.g., 200ms), and the peak value exceeds a preset fall impact threshold (e.g., greater than 3.5g), it is marked as a suspected fall event. Immediately following the impact signal, the controller 400 calculates the change in the device's tilt angle relative to the direction of gravity using gyroscope data. If the device rapidly changes from a vertical / swinging state (standing operation) to a horizontal stationary state (lying down), and the rate of change of tilt angle exceeds a preset threshold, the possibility of a fall is further confirmed.

[0068] To prevent false alarms (such as sudden bending over to pick up something or dropping tools), the controller 400 does not immediately generate an alarm message. Instead, it initiates a silent monitoring window of a preset duration (e.g., 30 seconds). During this silent monitoring window, the controller 400 continuously monitors the IMU for any recurrence of continuous acceleration fluctuations indicating climbing or standing, and for any weak struggling signals. If no effective active standing motion is detected within the preset time (i.e., the person remains still or only experiences weak twitching), the controller 400 determines that the person may have lost consciousness or mobility, and formally triggers the highest-level distress signal.

[0069] Upon triggering a distress call using a three-dimensional rescue response system with interconnected sound and light, the active safety warning module enters SOS mode. The controller 400 controls the lights to flash a bright red light according to Morse code (three short flashes followed by three long flashes). This quickly attracts the attention of passing vehicles or pedestrians, especially at night or in low-visibility conditions. The controller 400 transmits an RF broadcast signal to the surrounding area via a wireless communication module (preferably using low-power LAN protocols such as LoRa, ZigBee, or Bluetooth Mesh, but can also reuse 4G / 5G modules). This signal contains an accident type code (fall), the trapped person's ID, and precise relative location coordinates. Other similar smart wearable devices within a preset radius (e.g., nearby colleagues) will, upon receiving this broadcast, forcibly interrupt their current interface, emit a rapid alarm sound, and display an arrow navigation on their screen indicating the direction and distance to the fallen colleague. Utilizing the grid-like distribution of sanitation workers within the area, on-site mutual rescue can often be achieved earlier than by an ambulance within the crucial three minutes.

[0070] In some embodiments, the mechanical buckle in the fixing mechanism 200 integrates a magnetic assisted locking structure; the physical check-in button 101 is disposed in the side groove of the housing 100, and the controller 400 only responds to the off-duty / online mode switching command when it detects a long press signal with a duration exceeding a preset value or a double-click signal with a specific rhythm, so as to prevent accidental touch during sanitation operations.

[0071] In some embodiments, a pressure sensor is also integrated inside the housing 100; The controller 400 is also used to combine the geographical location data and the barometric pressure sensor data to determine the floor or altitude of the sanitation worker, so as to distinguish between elevated bridge operations and ground operations, and to perform differentiated weighting of physical load for workers at different altitudes during task matching.

[0072] Specifically, in some embodiments of the present invention, a high-precision barometric pressure sensor is integrated inside the housing 100 to compensate for the measurement limitations of satellite positioning systems in the vertical dimension. The controller 400 calculates the relative altitude of sanitation workers by collecting real-time barometric pressure values ​​and combining them with baseline barometric pressure data, thereby accurately distinguishing between the elevated bridge work level and the "ground work level" in three-dimensional space. When it detects that sanitation workers and the task location overlap in latitude and longitude but have a significant difference in altitude (e.g., more than 10 meters), the controller 400 automatically identifies that they are in different traffic levels and adds a path penalty factor when calculating spatial distance, effectively avoiding erroneous dispatches caused by extremely short straight-line distances but actual physical inaccessibility (requiring detours).

[0073] Furthermore, the controller 400 utilizes air pressure data to assist in calculating differentiated weights for physical workload. By continuously recording minute variations in air pressure, the controller 400 can calculate the cumulative climbing height of sanitation workers and construct a slope energy consumption model. If a sanitation worker is frequently detected to be working on slopes or at high altitudes, even if their resting heart rate has not yet triggered an alarm, it will determine that their leg muscle fatigue is high and introduce an elevation load correction coefficient. When matching subsequent emergency tasks, the matching score for that person with heavy physical labor or long-distance movement tasks will be automatically reduced, thereby achieving a more scientific and humane energy consumption assessment and task scheduling in a three-dimensional working environment.

[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. An intelligent wearable device for emergency operation of environmental sanitation, characterized in that, include: The casing integrates a biosensing window, a physical attendance button, and an active safety warning module; A fixing mechanism, connected to the housing, for securing the equipment to the wrist or shoulder of a sanitation worker, includes a mechanical buckle with a self-locking function; The sensing and positioning module is arranged inside the housing and is used to collect real-time geographical location data, work posture data, and microclimate data of the current work environment of sanitation workers in online operation mode. The controller, housed within the casing and electrically connected to the sensing and positioning module, biosensor window, physical check-in button, and active safety warning module, is used to identify the operation signal of the physical check-in button and switch the sanitation worker corresponding to the smart wearable device from off-duty mode to online operation mode. It is also used to respond to sanitation emergency tasks and, by combining the sanitation worker's age profile, physiological data collected through the biosensor window, and microclimate data of the current working environment, determine the thermal stress load index. Based on the geographical location data, it determines the spatial distance between the sanitation worker and the sanitation emergency task location, and combines the spatial distance and the thermal stress load index to determine the matching degree between the sanitation worker and the sanitation emergency task. Upon successful matching, it automatically associates and broadcasts the sanitation tool carrying list according to the sanitation emergency task type, and simultaneously drives the active safety warning module to emit a flashing warning signal corresponding to the task type. During operation, it compares the work actions and postures with a preset sanitation standard operation model in real time. When a valid work action matching the task characteristics is identified and continues for a preset duration, the task progress is automatically marked.

2. The smart wearable device according to claim 1, characterized in that, The microclimate data includes at least ambient temperature and relative humidity; the physiological data includes at least the current heart rate of the sanitation worker. The controller is used to determine the thermal stress load index by comprehensively considering the age profile, current heart rate, ambient temperature, and relative humidity of the sanitation workers; specifically, it is used to... Determine the thermal pressure load index, where, The current heart rate value is collected in real time by the biosensor window. The data contains the ages of sanitation workers stored in the equipment. The ambient temperature is from the current operational environment microclimate data. This represents the percentage of relative humidity in the current working environment's microclimate data. and The preset weighting coefficients, and + =1.

3. The smart wearable device according to claim 1 or 2, characterized in that, The controller is specifically used to determine the spatial distance between sanitation workers and sanitation emergency task locations based on the geographic location data. ,according to Determine the degree of matching ;in, This refers to the spatial distance between the device and the task location calculated based on the aforementioned geographical location data. The preset maximum effective response radius; This refers to the thermal pressure load index; This is a priority adjustment factor based on task type; Spatial distance weights As physiological load weight, Weights for task types.

4. The smart wearable device according to claim 3, characterized in that, The active safety warning module includes a high-brightness LED array or laser projection unit surrounding the side of the housing; The controller is specifically used to drive the LED array to emit a high-frequency orange strobe signal when the sanitation emergency task is road sweeping or sewage discharge; to drive the LED array to emit a low-frequency, high-brightness blue breathing signal when the sanitation emergency task is snow removal or extreme weather operation; and to activate the laser projection unit to project a safety warning light circle under the feet of the sanitation worker when it is detected that the sanitation worker is located in the motor vehicle lane and the ambient light is lower than the safety threshold.

5. The smart wearable device according to claim 4, characterized in that, The controller is specifically used to input the collected acceleration and angular velocity data into the sanitation standard operation model for feature extraction. The identified action types include sweeping action, shoveling action, and bending over to pick up action. When the identified action type is logically consistent with the type of emergency task currently issued, and the action frequency and amplitude meet the characteristics of effective operation, the effective operation time is accumulated.

6. The smart wearable device according to claim 5, characterized in that... The controller is also used to pre-store a task mapping table including the list of sanitation tools carried; The controller is also used to, when broadcasting the list of sanitation tools, if the sensing and positioning module detects that the distance between the current geographical location and the task target point has shortened to a preset range, but no sanitation workers have been detected to be staying or preparing materials, increase the volume of the voice broadcast and trigger a vibration reminder to perform a secondary material verification.

7. The smart wearable device according to claim 6, characterized in that, The biosensing window is made of high-transmittance optical glass, and its outer surface is covered with an oleophobic and anti-fouling coating. The controller is also used to detect detachment through the biosensor window. If the biosensor window does not receive a valid photoelectric reflection signal within a preset time, it is determined that the smart wearable device is in a non-wearing state, automatically suspends the online operation mode, and sends an abnormal offline alarm to the background.

8. The smart wearable device according to claim 7, characterized in that, The controller is also used to perform a fall assistance and rescue function; when it is determined from the work posture data that a sanitation worker has fallen and no active getting up action is detected within a preset time, the controller controls the active safety warning module to send an SOS Morse code flashing signal and broadcasts a distress signal to other similar smart wearable devices within a preset radius through the wireless communication module.

9. The smart wearable device according to claim 8, characterized in that, The housing also integrates a pressure sensor; The controller is also used to combine the geographical location data and the barometric pressure sensor data to determine the floor or altitude of the sanitation worker, so as to distinguish between elevated bridge operations and ground operations, and to perform differentiated weighting of physical load for workers at different altitudes during task matching.

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