92 results about "Mobile sensing" patented technology

A system for inductive energy transfer may include a stationary induction charging device including a stationary energy coil, a mobile induction charging device including a mobile energy coil, and a positioning device configured to detect a positioning of the stationary energy coil and the mobile energy coil relative to one another. During a charging operation of the system, one of energy coils may provide an alternating magnetic field which induces a voltage for energy transfer in the other energy coil and / or the induction charging devices may be disposed spaced apart from one another in a height direction. The positioning device may include i) four transmission coils in one of the induction charging devices and ii) at least one receiver in the other induction charging device. The transmission coils may, during a positioning operation, provide positioning fields that are distinguishable from one another.

The embodiment of the utility model provides a detection assembly and cleaning equipment. The detection assembly comprises a detection device, a mounting piece, an elastic piece and a sensing device. The detection device comprises a moving part. The moving part can move in the first direction relative to the mounting piece. The sensing device is provided with a sensing area, one of the moving part and the mounting part is provided with the sensing device, the other one is provided with a triggering area, and the sensing area is opposite to the triggering area in the first direction. The elastic piece is located between the moving part and the mounting piece and can elastically stretch out and draw back in the first direction. According to the detection assembly provided by the embodiment of the invention, the sensing device is triggered through the relative movement of the moving part and the mounting piece to judge whether the detection device is collided or not.

A system for inductive energy transmission may include a stationary induction charging device, a mobile induction charging device, and a positioning device configured to detect a relative position of respective charging coils of the charging devices during charging. The positioning device may include a transmitting device and a receiving device that are each arranged in a respective one of the charging devices. The transmitting device may include at least two transmitters that simultaneously emit a respective transmission signal with an associated predetermined frequency. The receiving device may include a receiver configured to output a superimposition of all received transmission signals as a time-dependent received signal. The positioning device may be configured to i) determine an associated amplitude for each transmission signal from the time-dependent received signal and / or ii) provide a position information item from the determined amplitudes. The position information item may represent the relative position of the coils.

A motor vehicle including a mobile induction charging device is disclosed. The motor vehicle is configured to: receive alignment fields generated by stationary induction charging devices of parking spaces of a parking lot and to detect the signal strength and alignment frequency of the alignment fields, recognize based on a stronger alignment field and the alignment frequency of the stronger alignment field that the mobile induction charging device is to be aligned with the stationary induction charging device associated with the parking space as it approaches one of the parking spaces, and output a navigation instruction for aligning the motor vehicle on the parking space via the alignment field associated with the approached parking space.

The embodiment of the invention provides a detection assembly and cleaning equipment. The detection assembly comprises a detection device, a mounting piece, an elastic piece and a sensing device. The detection device comprises a moving part. The moving part can move in the first direction relative to the mounting piece. The sensing device is provided with a sensing area, one of the moving part and the mounting part is provided with the sensing device, the other one is provided with a triggering area, and the sensing area is opposite to the triggering area in the first direction. The elastic piece is located between the moving part and the mounting piece and can elastically stretch out and draw back in the first direction. The detection assembly comprises a trigger state and a standby state; in the standby state, the triggering area and the sensing area are spaced in the first direction; in the triggering state, the triggering area abuts against the induction area in the first direction, and the elastic piece is in the stretching state or the compression state. According to the detection assembly provided by the embodiment of the invention, the sensing device is triggered through the relative movement of the moving part and the mounting piece to judge whether the detection device is collided or not.

The utility model discloses an unmanned intelligent boom sprayer, which comprises working mechanisms and a control system, the working mechanisms are arranged on a rack, each working mechanism comprises a walking mechanism, a steering mechanism, a boom action mechanism, a spraying mechanism and a fertilizer spreading mechanism, and the control system comprises a control terminal, a main controller, a manual operation mechanism and an external sensing mechanism; the control terminal is used for receiving signals of the external induction mechanism, sending signals to the main controller or the working mechanism and setting a moving track, and the main controller is used for receiving signals of the control terminal, the manual operation mechanism and the external induction mechanism and sending signals to the working mechanism. The external sensing mechanism comprises a movement sensing mechanism, a spray rod position sensing mechanism and a spray internal sensing mechanism; the spraying rod action mechanism comprises side spraying rods located on the two sides of the machine frame, each side spraying rod comprises a main rod and an auxiliary rod, one end of each main rod is hinged to one end of the corresponding auxiliary rod, an auxiliary unfolding oil cylinder is installed on each main rod, and a floating connector of each auxiliary unfolding oil cylinder is hinged to the corresponding auxiliary rod.

1. The name of this design product: Smart sensor (built-in snap-on type). 2. Purpose of this design product: Used for intelligent sensing and interconnection of LED lamps, realizing the functions of motion sensing and automatic brightness adjustment and control of intelligent lighting systems. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The invention relates to the technical field of Internet of Vehicles data privacy protection, and discloses an Internet of Vehicles data privacy protection method based on mobile perception federated learning, comprising the following steps: S1, a vehicle-mounted unit obtains vehicle operation data, power consumption behavior data and wireless communication data through mobile perception, generates a data set, and stores the data set in a database; and S2, the vehicle-mounted unit is based on the power utilization behavior data in the data set in the S1. By combining basic encryption strength calculation of a vehicle state and final encryption strength optimization of link stability, a two-dimensional dynamic encryption mechanism is constructed, battery remaining capacity and running speed in the vehicle state provide a basis for basic encryption, wireless communication link quality parameters support encryption strength secondary optimization, so that the encryption strength is adjusted as required, and the encryption efficiency is improved. And when the link is unstable, the strength is improved to guarantee privacy, when the link is stable, the complexity is reduced, the delay is reduced, finally, the sensitive parameter leakage rate is controlled at an extremely low level, the communication delay is maintained within 200 milliseconds, and the vehicle-gauge-level real-time requirement is met.

The invention discloses a coal mine methane leakage early warning method and system based on a wireless sensor network, and relates to the technical field of leakage early warning. The method comprises the following steps: deploying a sparse sensor network in a coal mine area, and constructing a coal mine cloud picture; real-time data of a coal mine area are collected and transmitted back to the central control processor; if the real-time data represents that no leakage exists, but the real-time data is in a metastable critical state, carrying out directional sensing management by calling a mobile sensing component in the sparse sensing network; if the real-time data represents that leakage exists, a leakage verification assembly is triggered, the data are synchronized to a coal mine cloud picture, cloud picture network screening and superposition state definition based on leakage events are carried out, and leakage data are determined and leakage early warning management is carried out based on superposition state collapse of candidate leakage paths by introducing a walking operator. The technical problem that in the prior art, coal mine methane leakage monitoring depends on a fixed sensing point, and the leakage state cannot be dynamically tracked is solved, and the technical effect of coal mine methane leakage dynamic positioning is achieved.

The invention provides a belt inspection robot control method and system, and relates to a data processing technology, the method comprises the following steps: obtaining an oblique detection zone located at a belt mechanism, and collecting magnetic flux data of static induction units obliquely arranged in the oblique detection zone at intervals; according to the magnetic flux data and the distribution positions of the static induction units, verification areas are generated, and based on the magnetic flux data of the change induction units corresponding to the verification areas, estimated contours corresponding to the verification areas are constructed; when it is determined that the verification area is located in the treatment area, a robot in the treatment area is controlled to sort and recognize the verification area, and the recognition contour of the to-be-sorted object is obtained; on the basis of the comparison result of the estimated contour and the recognized contour, the mobile sensing unit is controlled to move to the re-checking area for verification, a re-checking result is obtained, shape estimation can be conducted on the metal foreign matter buried below the coal, therefore, a robot is effectively guided, and the efficiency and reliability of removing the metal foreign matter are improved.

The technical scheme belongs to the technical field of intelligent cabinets, and particularly relates to an anti-pinch intelligent cabinet, which comprises a cabinet body, the upper end surface of which is provided with an accommodating cavity; the cabinet door is arranged at the opening of the accommodating cavity and slides relative to the cabinet body; the front panel is fixed on the rear side of the upper end surface of the cabinet body and is provided with a sensing device; the driving device is mounted on the front panel and is used for driving the cabinet door to move between an opening position and a closing position; the sensing device comprises a plurality of ultrasonic ranging assemblies, the detection ends of the ultrasonic ranging assemblies face the containing cavity, the driving device is controlled through the control mainboard, and when ranging is smaller than a set value, the control mainboard ensures that the cabinet door is in a normally-open state, the cabinet door is not automatically closed to prevent hands from being pinched and limbs from leaving the cabinet body from the detection range; the cabinet door is automatically closed after being waited for a short time, when the hand enters the induction area in the door closing process, the cabinet door stops closing and is opened again in the reverse direction until no object exists in the induction range, the cabinet door continues to be closed, the hand is effectively prevented from being pinched, and the use safety is improved.

This application relates to the field of Internet of Things (IoT) technology, and in particular to a method and system for personnel safety monitoring in chemical industrial parks based on dual-channel heterogeneous data transmission and multi-source fusion. The method synchronously collects environmental parameters and inertial data through mobile sensing terminals; constructs an extended Kalman filter model to tightly couple and fuse ultra-wideband positioning coordinates with inertial dead reckoning data to correct cumulative drift in predicted values; employs a vertical distance threshold trajectory compression algorithm at the edge to eliminate redundant positioning points on linear paths, reducing transmission load; dynamically adjusts the radius of the electronic fence based on gas concentration and determines fall events by combining acceleration amplitude temporal characteristics; and utilizes a dual-channel WiFi collaborative mechanism to normally upload lightweight data via a low-power channel, only activating the high-speed channel to upload on-site images when boundary crossings or fall anomalies are detected. This application effectively solves the technical problems of low positioning accuracy, multimedia data transmission bandwidth conflicts, and delayed safety warnings in industrial sites.

The invention discloses an intelligent fire-fighting robot system and a control method. Comprising the following steps: acquiring wide-area environment image information through a fixed monitoring camera network deployed in an operation area, and acquiring approaching environment image information through a mobile sensing system carried by a fire-fighting robot; according to the intelligent fire-fighting robot system and the control method, the fire-fighting robot can automatically adapt to complex terrains such as oil stains and stairs and accurately recognize fire source properties, so that the optimal moving mode and the fire extinguishing agent are automatically selected. According to the system, sensing data of fixed monitoring and the robot body are fused, dynamic path planning and personnel guiding are achieved, the traffic capacity, the fire extinguishing precision and the personnel rescue efficiency in a complex fire scene are remarkably improved, and the risk of rescue personnel is effectively reduced.

The present application relates to a steering wheel assembly, a steering device and a vehicle. The steering wheel assembly includes a steering wheel body, a drive unit and a sensing control unit. The steering wheel body includes a gripping portion and a protrusion assembly provided on the gripping portion. The gripping portion is provided with a gripping surface. The protrusion assembly includes a plurality of protrusions arranged on the gripping surface. The drive unit is connected to the protrusion assembly and is used to drive the lifting and lowering movement of the protrusions. The sensing control unit is electrically connected to the drive unit and is used to detect the gripping position of the sensing target so that the drive unit can drive the corresponding lifting and lowering movement of the protrusions.

The invention relates to a laser measuring device for measuring the width and length of a bridge crack, and belongs to the technical field of bridge detection, and the laser measuring device comprises a walking assembly, a steering assembly, an adjusting assembly, a laser range finder and a sensing assembly. Wherein the walking assembly is used for providing power for the laser measuring device to walk on a bridge; the steering assembly is arranged on a walking base in the walking assembly and used for providing power for the laser range finder to rotate in the vertical direction. The adjusting assembly is arranged on a steering table in the steering assembly, and independent movement in the vertical direction and the horizontal direction is provided for the laser range finder through an adjusting plate. The sensing assembly is arranged on the walking assembly and corrects the walking direction of the whole laser measuring device, and the situation that a complex visual system is needed to complete crack width and length measurement work is avoided. According to the method, the dependence on a complex visual identification algorithm is abandoned, and the problems of instable identification, precision reduction and even failure in the prior art are fundamentally eliminated.

The invention provides a variable-pitch buffer battery gripper and a battery moving method. The variable-pitch buffer battery gripper comprises a base frame; the pitch changing mechanism comprises a fixed plate, a movable plate and a movable sensing assembly, the movable sensing assembly comprises a movable sensor and a movable sensing piece, the movable sensor is fixedly arranged on the base frame, and the movable sensing piece is connected to the movable plate and synchronously moves along with the movable plate; and a clamping mechanism. The spacing distance of the clamping mechanisms is adjusted through the distance changing mechanism, so that it is ensured that the clamping mechanisms can be accurately matched with the feeding position point or the discharging position point, and the battery moving efficiency and quality are improved. According to the pitch changing mechanism, the accuracy degree of the pitch changing process is improved by means of the movable sensing assembly, and the reliability degree and the controllability degree of the pitch changing process are further improved. Based on the structural design, compared with a conventional battery material moving technology, the battery material moving device has the remarkable advantages of being high in use flexibility, wide in application scene, high in compatibility, capable of improving the battery processing efficiency and quality and the like.

The present invention discloses a method for mobile sensing prediction beamforming, which relates to wireless communication. This solution is proposed in view of the problem that the existing beamforming is not efficient enough. Steps: S1. Construct a new sensing-assisted SWIPT system model; S2. Construct a sensing prediction and tracking model of the motion state of a multi-antenna hybrid access point HAP for a mobile energy user MEU; S3. Construct an online beamforming framework based on the extended Kalman filter EKF; S4. Construct an optimization problem model that maximizes the ratio of the power collected by the mobile energy user MEU to the total power consumption at the multi-antenna hybrid access point HAP; S5. Based on the Dinkelbach and SDR transforms, perform convex optimization on the non-convex optimization problem to maximize the wireless power transfer WPT efficiency of the sensing-assisted SWIPT system. The advantage is that the multi-antenna hybrid access point HAP of the constructed sensing-assisted SWIPT system serves multiple single-antenna communication users IU and a mobile energy user MEU, which is closer to the actual application scenario and realizes accurate tracking accuracy and efficient power transmission.

This invention belongs to the field of bridge engineering technology, specifically relating to a bridge stress state diagnosis method based on digital twins and mobile sensors, aiming to achieve real-time diagnosis of the stress state of bridges with defects. The method includes acquiring spatial data of existing bridge defects, embedding defect parameters into a twin model, and generating an initial twin of the defective bridge. A modular monitoring station composed of mobile sensing devices is deployed on the bridge, with data transmitted between devices via a mesh self-organizing network to an edge computing terminal, where data preprocessing is performed. During the monitoring period, vehicle load, temperature and humidity, displacement, or vibration data are injected in real time into the initial twin of the defective bridge. An FEM-defect coupling algorithm is established to dynamically correct the structural stiffness matrix, forming a digital twin. A stress state diagnosis index system is established, comparing the responses of the digital and healthy twins under the same load, calculating the variation amplitude of each diagnostic index, and marking the structural health spectrum to determine whether the bridge has an abnormal stress state.

The present invention discloses an ultrasonic bone knife handle equipped with a force control device, which is characterized in that a movement sensing force control device is installed on the ultrasonic bone knife handle. In the above manner, the present invention enables the physician to sense several key pressure values ​​due to movement, so that when surgical efficiency is required, the cutting pressure can be accurately controlled within the maximum cutting efficiency range to ensure surgical efficiency. When surgical safety is required, the force control device can be turned off to avoid safety hazards caused by the telescopic elasticity of the blade head, thereby reflecting the maximum safety feature of the ultrasonic bone knife.

A mobile sensing platform and system for mental healthcare that supports seamless integration of different mobile devices into the health system is disclosed. The mobile sensing platform and system for mental healthcare uses the HL7 FHIR standard to seamlessly integrate the various, different mobile devices into the health system.

The present disclosure provides a system of distributed edge computing for cooperative augmented reality with mobile sensing capability. The system includes a plurality of nodes configured to generate a plurality of data streams; and a plurality of distributed edge servers configured to process one or more tasks using the plurality of data streams. An Apache Storm distributed stream processing platform is installed and properly configured on each distributed edge server; the plurality of distributed edge servers includes one or more service modules installed on each distributed edge server and configured to process the one or more tasks; and the plurality of distributed edge servers includes a master distributed edge server and a plurality of slave distributed edge servers; and a scheduler is installed on the master distributed edge server and configured to distribute the one or more tasks to the plurality of distributed edge servers.

The application discloses a tea garden pest multi-source sensing monitoring and intelligent decision-making pesticide application system, and relates to the technical field of intelligent agriculture. The system comprises a mobile sensing array, a static monitoring base station and a time synchronization module. By collecting multispectral images and environmental parameters and completing space-time alignment, the system realizes multi-modal feature deep fusion relying on the cross-attention mechanism, combines space-time sequence repair technology and sheltering bottom-up strategy to deal with target sheltering problems, generates pesticide application action vectors based on a deep reinforcement learning algorithm, and integrates mechanical response characteristics and physical constraint filtering to ensure stable execution. Meanwhile, the system constructs a pesticide application amount residual feedback closed loop to realize online optimization of the model. The application effectively improves the accuracy of pest identification and pesticide application and the stability of equipment operation, solves the problems of poor environmental adaptability, insufficient sheltering response and disconnection between decision-making and execution in the prior art, and realizes intelligent and accurate prevention and control of tea garden pests.

The present invention discloses an optimization method for task offloading in a vehicle-to-everything (V2X) network based on mobile sensing. The method includes: (1) initializing system parameters, including parameters related to roadside units, vehicles, tasks, and initial algorithm parameters; (2) generating an offloading ratio allocation vector for computing tasks, where each element in the vector represents the ratio of tasks received by the corresponding vehicle; (3) optimizing the energy consumption of the system by optimizing the task offloading ratio, and finding the optimal solution for task offloading based on the proposed algorithm; (4) performing task offloading according to the allocation strategy corresponding to the optimal solution. The present invention can quickly and effectively optimize the task offloading calculation, effectively reduce the latency, and lower the cost of offloading calculation.

The invention discloses a computing power server case electric leakage detection device and method, and the device comprises a plurality of convergence modules which are installed in at least one or more functional regions of the inner wall of a computing power server case; the convergence module at least comprises a functional body matched with the shape of the functional area; and the central monitoring and processing module is electrically connected with and controls the track driving unit and the mobile sensing assembly. All corners and key areas in the server can be covered according to requirements, weak leakage currents occurring at the corners of a case are captured and collected, and therefore detection blind areas are eliminated, and the potential fault detection and early warning capacity is improved; the detection signal of the mobile sensing assembly and the real-time position of the mobile sensing assembly on the track are synchronously analyzed through the central processing module, and a fault can be attributed to a specific convergence module, so that the physical compatibility contradiction is reduced, the adaptation range is wider, and electric leakage detection can be stably carried out on the case.

The invention relates to the technical field of sleep monitoring, in particular to a sleep monitoring method and system.The method comprises the steps that real-time data in the sleep process are collected, and sleep monitoring data are obtained; processing the sleep monitoring data, and extracting data features in the sleep monitoring data; establishing a corresponding relation between the related sleep event characteristics and different sleep states through a conditional random field, and predicting the sleep state of the next moment according to the corresponding relation; judging whether the predicted sleep state at the next moment is in a wake-up threshold value or not, and if yes, performing relaxation service on the user; intelligent awakening is carried out according to the awakening time period selected by the user, and it is guaranteed that the user is awakened at the optimal time point. The sleep quality is detected through the mobile sensing technology, intelligent awakening is carried out according to the awakening time period selected by the user, it is guaranteed that the user is awakened at the optimal time point, and the optimal sleep effect is achieved.

The invention belongs to the technical field of household appliances, and particularly relates to a household appliance. The body of the household appliance is provided with an opening; the door body is connected to the opening of the machine body in an openable manner; the two ends of the buffering piece are connected with the door body and the machine body correspondingly. The triggering piece is connected to the buffering piece and reciprocates along with opening and closing of the door body; the sensing piece is connected to the machine body; wherein when the trigger piece is close to the induction piece, the induction piece is triggered and generates a trigger signal; and when the triggering piece is far away from the sensing piece, the sensing piece is not triggered. The safety hidden danger that the door body falls due to the fact that the door body is opened on the premise that the buffering piece fails can be avoided, safety and user experience are improved, and good practicability is achieved.

The invention belongs to the technical field of tunnel construction monitoring, and discloses a construction tunnel on-load roadside sensing method based on a laser radar, and the method comprises the steps: obtaining the point cloud data of an on-load laser radar and a roadside laser radar; calculating the real-time pose of the on-board laser radar in the global coordinate system based on the roadside laser radar point cloud data; performing combined filtering on the point cloud data; converting the filtered on-load laser radar point cloud data into a global coordinate system by using the real-time pose, and fusing the filtered on-load laser radar point cloud data with the filtered roadside laser radar point cloud data to obtain three-dimensional construction tunnel point cloud data; establishing geometric models of the left and right side walls of the construction tunnel, and calculating the actual width of the construction tunnel by using the geometric models; through cooperation of vehicle-mounted mobile sensing and roadside fixed sensing and combination of combined filtering and data processing flow specially designed for construction interference, the problem of large error of a construction tunnel section width calculation result is solved, environmental noise is effectively inhibited, and high-precision measurement of the construction tunnel width is realized.

This invention discloses an intelligent warehouse management system based on integrated hardware and software, belonging to the field of warehouse management technology. Specifically, it includes: First, a node synchronization module deploys and synchronizes multiple mobile sensing nodes. A data acquisition module controls the movement of work units and collects time-stamped point cloud data, sending it to the sensing nodes. A coordinate alignment module sets the receiving node as the master node and converts the point cloud data to its coordinate system to generate a local map. A fragmentation and distribution module divides the map into geographical segments and distributes them to neighboring nodes. A collaborative fusion module receives feedback fragments from neighboring nodes, merges them, and generates a corrected local map. Finally, a path planning module calculates and sends updated paths for work units based on this map. This invention achieves decentralized real-time environmental perception and adaptive path planning in a dynamic warehouse environment, improving the system's robustness and operational continuity in complex and changing scenarios.

This application relates to the field of traffic flow sensing technology, and in particular to a traffic flow sensing method and system. The method involves collecting multi-source heterogeneous traffic sensing data from fixed sensing devices, mobile sensing terminals, and environmental sensors within a target sensing area; sending this data to an edge computing node for preliminary processing and feature extraction to generate structured feature data, which is then uploaded to a cloud platform; aligning the data to a unified spatiotemporal reference on the cloud platform and performing multi-source data fusion processing based on dynamic confidence weighting to obtain fused traffic parameters; dynamically adjusting the fusion weights of each data source using a pre-generated environment-weight mapping model; and finally generating traffic situation information including traffic flow, average vehicle speed, lane occupancy, and traffic event types based on the fused traffic parameters. This method can adapt to environmental changes, improve the accuracy and robustness of traffic flow sensing, and solve the problem of perception bias easily occurring with a single data source in specific environments.

The invention provides a low-altitude interference source recognition method and system based on pattern recognition. The method comprises the following steps of: 1, integrating a mobile sensing front end on an unmanned aerial vehicle platform, and acquiring a sensing data sequence, and 2, performing low-altitude simulation space reconstruction under the combination of numerical electromagnetic simulation and ray tracing on a target low-altitude area, and generating an interference identification module through supervised training of a meta classifier based on interference mode identification; 3, initializing the low-altitude simulation space according to the perception data sequence, constructing a three-dimensional electromagnetic environment thermodynamic diagram, and determining an interference identification result by executing interference identification based on the three-dimensional electromagnetic environment thermodynamic diagram; 4, performing unmanned aerial vehicle inspection management according to the interference identification structure; according to the method, data preprocessing and multi-dimensional feature engineering are combined, a comprehensive and high-quality data basis can be provided for interference recognition, and the recognition accuracy is improved.