53 results about "Continuous sensing" patented technology

The invention provides a fan running state identification method and system based on multi-mode optical fiber sensing monitoring, and the method comprises the steps: obtaining a continuous sensing signal collected by a distributed optical fiber sensor, carrying out the time-space correlation filtering of the continuous sensing signal, generating a multi-physical field micro-variation feature vector set, and carrying out the recognition of the running state of a fan through the multi-physical field micro-variation feature vector set; inputting the multi-physical field micro-variation feature vector set into a pre-trained coupling response modeling network, and performing correlation modeling on the strain field micro-variation feature vector and the temperature field micro-variation feature vector through a space-time cross attention mechanism in the coupling response modeling network to generate a dynamic response fingerprint spectrum; calling a fault evolution path set in a historical fault database, performing similarity matching on the dynamic response fingerprint spectrum, and generating an operation state deviation index; and querying a preset health state evaluation strategy library, determining the overall health state level of the fan and the corresponding potential fault risk probability, and generating an operation state evaluation result containing the fault area positioning coordinates. The accuracy of fan operation state recognition can be improved.

The invention provides a portable fire blast risk dynamic identification and danger tracing method and terminal, and the method comprises the steps: collecting positioning data in real time through a GNSS positioning module; a high-speed analog-to-digital conversion chip ADC is used for carrying out high-frequency and synchronous processing on the gas concentration collected in real time; collecting field environment parameters in real time; performing dynamic threshold intelligent judgment to obtain a leakage judgment result, and executing a grading early warning mechanism; recording an inspection track in real time, and carrying out space gas concentration gradient analysis to obtain a gas concentration gradient; calculating a built-in space distance; judging the leakage direction according to the gas concentration gradient data, and intelligently tracing the leakage source according to the leakage judgment result; and uploading the security data to the cloud. According to the invention, the limitation of static and single-threshold alarm of an instrument is solved, and the technical problems of difficulty in spatial continuous sensing and automatic tracing positioning of gas leakage abnormity in a complex inspection environment with dynamic changes of multi-component combustible gas and environmental parameters are solved.

The invention discloses a ship target detection method based on distributed optical fiber sensing, and belongs to the technical field of ship target detection. M spatial continuous sensing channels are selected from the distributed optical fiber sound wave sensing system, one-dimensional acoustic time sequence data of each channel are acquired, and constant Q transformation is carried out to generate a time-frequency spectrogram; harmonic and broadband feature decoupling is carried out on each time-frequency spectrogram to construct a dual-channel input tensor; and inputting the M input tensors into the cross-channel space self-attention neural network, and outputting the ship-existence or ship-absence classification probability of each channel. The network takes ResNet-50 as a trunk, a cross-channel spatial attention fusion module is embedded after shallow feature extraction to utilize spatial correlation between channels, and a time-frequency separation attention module and an adaptive frequency band enhancement module are embedded in an intermediate feature extraction stage to realize decoupling of time-frequency features and enhancement of key frequency bands respectively. According to the invention, the detection precision, robustness and space positioning capability of the ship target in a strong noise environment are effectively improved.

The invention discloses a multi-source operation exception association analysis and grading disposal method and system. The method comprises the steps of telemetry data collection and caching, non-blocking sending and self-adaptive readaptation, sliding time window and matrix construction, exception association clustering and comprehensive scoring, exception type judgment and grading alarm and self-healing disposal. The method comprises the following steps: continuously sensing a program execution state and an abnormal behavior, realizing data peak clipping storage by local cache, introducing a self-adaptive backoff retry mechanism, decentralizing transmission of abnormal data on the premise of not blocking a main service, and identifying and distinguishing anomalies in combination with abnormal propagation characteristics and an influence coupling relationship. And after quantitative judgment, automatically outputting a matched grading treatment strategy and an operation recovery measure. The closed-loop operation treatment mechanism of coverage sensing, transmission, aggregation, judgment and disposal constructed by the invention can realize rapid sensing, accurate attribution and adaptive response of the abnormity in a complex industrial load environment, and the stability and reliability of the operation of an industrial system are remarkably improved.

The invention relates to the technical field of smart home, discloses a smart home equipment state monitoring and fault self-healing optimization method and system, and aims to solve the problems of low operation and maintenance efficiency and untimely fault processing of smart home equipment in the prior art. The method comprises the following steps: continuously acquiring equipment operation state data, communication interaction data and environment context data through a multi-source sensor and a communication interface; preprocessing and feature engineering are carried out on the collected original data, and association weights of cross-device features are calculated based on an attention mechanism; constructing a fault prediction network by using a gating cycle unit and a causal graph model, and outputting fault probability distribution and a root cause analysis result; and generating a self-adaptive repair strategy according to the fault type, the root cause chain and the equipment operation context. The system comprises a multi-source heterogeneous data acquisition module, an equipment state feature extraction and fusion module, a fault prediction and root cause analysis engine, a self-adaptive repair strategy generator and a knowledge migration and model evolution module. Through adoption of the technical scheme, fine-grained and continuous sensing of the equipment state can be realized, accurate root cause analysis and multi-granularity early warning are provided, manual intervention requirements are reduced, the self-healing efficiency of the system is improved, and the adaptability and robustness of the system are enhanced on the premise of guaranteeing user privacy.

The invention discloses a multi-mode flexible tactile sensor capable of realizing full-surface continuous sensing, a module and a preparation method of the multi-mode flexible tactile sensor capable of realizing full-surface continuous sensing, and the multi-mode flexible tactile sensor comprises a collector circuit board, the upper surface of the collector circuit board is regularly provided with a flexible pressure sensor used for pressure signal measurement and pressure sensing, a flexible temperature sensor used for temperature signal measurement and temperature sensing, and a mixed magnetic particle adhesive film used for generating a magnetic field. A Hall sensor array used for magnetic field signal measurement and three-dimensional force sensing and a signal processing module used for signal acquisition and processing are regularly arranged on the lower surface of the collector circuit board. According to the multi-mode flexible touch sensor capable of continuously sensing the whole surface, through cooperative work of the mixed magnetic particle glue film, the flexible pressure sensor / flexible temperature sensor and the Hall sensor layer, accurate collection of three-dimensional force signals / temperature signals and magnetic field changes can be achieved.

The invention relates to the technical field of intelligent traffic, in particular to road parameter detection equipment and system based on a triboelectric sensor. The road parameter detection device comprises a triboelectric sensor and a data processing unit. The triboelectric sensor is installed on an automobile shock absorber and used for generating a first pulse signal, a second pulse signal and a third pulse signal. The data processing unit converts the pulse signal I into displacement time domain data in the vertical direction of the road surface so as to sense the unevenness of the road surface in real time; the second pulse signal and the third pulse signal are converted into the swing angle and the swing direction of the single swing block in the horizontal direction, and then the slope angle of the road is sensed in real time. Two road parameters including road surface unevenness and road slope angle are continuously sensed in real time by arranging the friction electric sensor of a specific structure and utilizing the vehicle-road coupling effect, collaborative sensing of parameters of a road in two dimension directions is achieved at the same time, and the efficiency of road multi-parameter collaborative sensing is improved.

The invention discloses an electromagnetic shielding environment signal transmission method and device based on mechanical vibration, and the method comprises the steps: collecting original information which comprises continuous sensing data and discrete manual instructions; original information is mapped into a vibration sequence through frequency-time sequence two-dimensional coding, and verification information is added to generate a control signal; driving a vibration generator to generate mechanical vibration waves penetrating through the metal wall according to the control signal; receiving a vibration signal penetrating through the metal wall through a high-sensitivity sensor, and performing signal conditioning to obtain a vibration electric signal; and performing spectrum analysis and feature extraction on the vibration electric signal, decoding and restoring original information, and uploading data through a multimode transmission interface. According to the invention, on the premise that the structural integrity and electromagnetic shielding performance of the fully-sealed metal cavity are not damaged, transmission of sensor data and manual coding instructions can be realized.

The application relates to the technical field of radio monitoring, and discloses a low-cost micro-distributed radio monitoring system, which comprises a plurality of distributed radio frequency monitoring nodes, a plurality of converging gateway nodes and a remote monitoring center; the distributed radio frequency monitoring nodes are used for periodically wide-frequency scanning sensing on a space electromagnetic environment; an energy management module is used for controlling the distributed radio frequency monitoring nodes to enter a low-duty-cycle working mode in a normal state, adjusting monitoring frequencies and data reporting frequencies; a self-organizing network communication module is used for establishing a multi-hop wireless communication topology; the converging gateway nodes are used for fusing and processing monitoring data uploaded by the distributed radio frequency monitoring nodes; and the remote monitoring center is used for unified management, command issuing, monitoring data analysis, visual display and abnormal signal alarming of the whole network and the like. The application realizes continuous sensing on a complex urban electromagnetic environment or a specific area, blind area compensation coverage and automatic discovery of abnormal signals.

The invention discloses a side slope real-time monitoring system based on longitudinal continuous sensing, relates to the technical field of side slope real-time monitoring, is used for solving the problem that the safety and early warning response efficiency of a side slope structure are reduced, identifies a fill side slope collision area through a monitoring layer, detects the side slope outward movement amount of the area and analyzes the displacement deformation trend, and achieves the real-time monitoring of the side slope. Marking damaged areas according to a deformation trend; acquiring stress distribution and pore water pressure data of a pressure bearing layer; evaluating bearing stability characteristics and generating an abnormal level; screening a target damaged area according to the abnormal level, detecting vibration amplitude data of a slip layer of the target damaged area, and evaluating a response coefficient of a target damaged point according to the vibration amplitude data. According to the method, the number of peak values of the response coefficients is counted, whether alarm prompt is triggered or not is judged based on the number of peak values, multi-level continuous monitoring from surface deformation to deep deformation after the fill slope is subjected to external collision is achieved, potential slippage risks are recognized, real-time alarm is achieved, and the safety and early warning response efficiency of the slope structure are improved.

The application discloses an intelligent deep scarification spade, a ploughing layer resistance continuous sensing method and a ploughing depth intelligent regulation and control system. The intelligent deep scarification spade comprises a connecting frame and a spade handle. The lower end of the spade handle is provided with a spade tip. A plurality of soil breaking blocks are mounted on the front side of the spade handle. Each soil breaking block is connected with the spade handle through a strain pressure sensor. The strain pressure sensor comprises a connecting block and a first strain gauge. A total soil breaking force detection sensor is connected between the spade handle and the connecting frame. The connecting block comprises a narrow body part and a wide body part. The narrow body part is provided with a connecting end and a neck part. The neck part is provided with a first through hole. The first strain gauge is mounted on the outer wall of the neck part. The wide body part is provided with a notch. The wide body part has two forked parts. The end parts of the two forked parts are connected with the soil breaking blocks. In the two adjacent strain pressure sensors, the corresponding narrow body part of one is embedded in the notch of the connecting block of the other. Except that the connecting end directly contacts with the front side of the spade handle, there is a gap between the other parts of the connecting block and the spade handle.

The invention relates to a method and a device for online calibration of an environmental sensing system in a motor vehicle, the method comprising the following steps: during the vehicle's journey, the environmental sensing system continuously senses positioning data of objects in its surroundings and transmits them wirelessly to a calibration service, together with motion data of the vehicle; the calibration service has access to a road signature in the form of a digital map in which the positions of permanent stationary signature objects that can be sensed by the environmental sensing system are recorded along the road traveled by the vehicle, and filters the positioning data transmitted by the environmental sensing system according to the signature objects; based on the signature object positioning data and on the motion data, the calibration service tracks the vehicle's motion on the digital map; by comparing the signature object positioning data with the positions of the signature objects relative to the vehicle on the digital map, the calibration service calculates correction data that are indicative of calibration errors of the environmental sensing system and transmits them to the vehicle; the environmental sensing system recalibrates based on the correction data.

This invention discloses a monitoring and early warning system and method for a makeup water resin regeneration workshop, relating to the field of production process monitoring technology. The system includes the following steps: during the static settling stage of makeup water resin regeneration, temperature, pressure, flow rate, and visual information are simultaneously collected from the upper and lower positions of the bed. The temperature, pressure, flow rate, and visual information are then compared and analyzed to generate a settling status linkage record. This invention achieves continuous sensing of the internal temperature, water flow, and interface state during the resin settling stage through multi-dimensional parameter synchronous acquisition and linkage analysis, enabling early identification of internal changes and improving monitoring and safety. Furthermore, it optimizes the regenerated liquid entry method based on flow distribution and combines controlled reverse pressure to regulate the flow field, eliminating short circuits and enhancing uniform contact, thereby improving regeneration quality and reducing operating costs.

The invention relates to the technical field of body position monitoring, in particular to a surgical patient body position nursing compliance detection method which comprises the following steps: forming body position pressure distribution by collecting signals of multiple pressure sensing points in an operating table and carrying out time alignment and proportion conversion, calculating body position contact centers in combination with space coordinates of the sensing points, and sequencing the body position contact centers; the method comprises the following steps: continuously acquiring and proportionally processing pressure information, tracking displacement directions of adjacent periods, analyzing consistency, performing direction energy correlation judgment on pressure change, implementing consistency screening and state adjustment in a preset time window, and outputting a stable and reliable body position nursing compliance monitoring result. According to the method, body position compression distribution is constructed, a contact center change track is calculated, body position static judgment is converted into continuous sensing, the displacement direction and compression energy correlation is combined to analyze the body position deviation trend, time consistency screening is introduced, the misjudgment risk is reduced, and the body position monitoring accuracy and nursing reliability are improved.

The invention relates to the technical field of tunnel engineering intelligent perception and surrounding rock grading, and discloses a mountain tunnel surrounding rock grade automatic identification method, system and device based on image-point cloud fusion, and a storage medium. The automatic mountain tunnel surrounding rock grade identification method based on image-point cloud fusion comprises the following steps of multi-source surrounding rock perception data acquisition, surrounding rock image apparent semantic feature extraction, surrounding rock point cloud geometric state feature extraction, surrounding rock evaluation unit construction and image-point cloud feature fusion, surrounding rock engineering state comprehensive evaluation and grade identification. And surrounding rock grade zoning and result output. According to the invention, through image-point cloud fusion, a continuous evaluation unit is constructed along the axial direction of the tunnel, and the surrounding rock grade is automatically identified and output; according to the method, the objectivity and consistency of surrounding rock grade identification are improved, continuous sensing and grading of surrounding rock states are realized, the real-time performance of acquiring surrounding rock grade information is improved, deep fusion and engineering output of multi-source information are realized, and the method has good engineering applicability.

The invention relates to the technical field of inland river shipping, in particular to an inland river unmanned ship navigation anti-collision method and system based on multipoint ultrasonic ranging, and the method comprises the steps: configuring an ultrasonic sensor array which comprises five ultrasonic sensor nodes; original ranging signals of all the ultrasonic sensor nodes are circularly collected based on a time division multiplexing mechanism; constructing a virtual radar matrix; executing dynamic threat evaluation; and performing obstacle avoidance execution control. Five ultrasonic sensor nodes are configured to form a 180-degree fan-shaped array, and a continuous sensing field covering a bow and two side wings is formed in cooperation with a time division multiplexing mechanism and a virtual radar matrix algorithm; wherein co-frequency cross interference between ultrasonic sensors is eliminated through a time division multiplexing strategy, sensing discontinuity between discrete detection points is eliminated through a spatial interpolation technology, and the problem of lateral sensing blind areas existing in the background technology is solved.

The invention discloses a slope stability monitoring and evaluation method based on DAS optical fiber-displacement collaboration, and relates to the field of slope engineering, comprising the following steps: constructing a distributed optical fiber deformation monitoring system, constructing a displacement monitoring system, and performing data acquisition through the displacement monitoring system and the distributed optical fiber deformation monitoring system, processing the data through matlab data analysis software, establishing a mathematical relationship between a vibration signal and displacement data, and predicting a displacement value of the slope surface based on the mathematical relationship; a single-mode optical fiber is used as a continuous sensing network, the defects that a traditional point-type sensor is limited in monitoring range and high in maintenance cost are overcome, a precise mathematical model between optical fiber vibration frequency domain signals and physical displacement is established, and spanning from local point measurement to global surface sensing is achieved; the monitoring comprehensiveness and the early warning timeliness are remarkably improved, and an efficient, reliable and low-cost solution is provided for slope disaster prevention and control.

The invention discloses an intelligent inspection system for insulator appearance imaging based on an AOV camera and an operation method. The intelligent inspection system comprises a sensing acquisition unit, an edge analysis unit and a platform management unit, the sensing acquisition unit is arranged on a tower cross arm or a transformer substation framework, the sensing acquisition unit is composed of a low-power-consumption AOV camera, an inertial sensor module, a GPS / Beidou module, a cleaning module and a power supply module, the GPS / Beidou module obtains a spatial position, and the inertial sensor module unit senses a camera attitude angle; the edge analysis unit is arranged in the camera or is used as an independent device to be installed on a tower nearby, and is used for identifying and positioning equipment such as an insulator, a lightning arrester and a wire clamp in an image; the platform management unit is arranged on a cloud platform or a data center; according to the invention, unmanned intelligent inspection is realized, through continuous sensing and intelligent triggering mechanisms of the AOV camera and in combination with a special AI algorithm, full-automatic identification of electrical equipment appearance defects in 24 hours after the whole day is realized, and manual intervention is not needed.

In one embodiment, a flexible circuit board includes a plurality of facet locations, each facet location corresponding to a particular rigid sensor facet of a plurality of rigid sensor facets and a particular rigid display facet of a plurality of rigid display facets. The flexible circuit board also includes a plurality of wiring traces that connect the plurality of facet locations in series. The facet locations are arranged in a plurality of facet columns. When the flexible circuit board is flat, at least some of the facet locations are separated from one or more adjacent facet locations by a plurality of gaps. When the flexible circuit board is formed into a three-dimensional shape, the plurality of gaps are substantially eliminated, thereby allowing the plurality of rigid sensor facets to form a continuous sensing surface and the plurality of rigid display facets to form a continuous display surface.

The invention provides a meteorological environment intelligent sensing and real-time monitoring method and system, and relates to the technical field of gas phase monitoring, and the method comprises the steps: setting a plurality of meteorological environment sensing nodes in a target monitoring region, obtaining the original data of a meteorological environment, and generating a multi-dimensional meteorological state vector according to a preset time window; according to the multi-dimensional meteorological state vectors of the adjacent time windows, meteorological state change vectors are constructed, the meteorological state change vectors of different meteorological environment sensing nodes are compared on the regional scale, and a regional change reference is formed; carrying out consistency judgment on the meteorological state change vector of each meteorological environment sensing node and a regional change reference, identifying a local meteorological anomaly evolution process, and generating a corresponding identifier; and for the identified local abnormal region, dynamically adjusting the acquisition time window of the original data of the meteorological environment, and updating the meteorological state change vector according to the adjusted time window, thereby realizing continuous sensing and real-time monitoring of the change process of the local meteorological environment.

The present application relates to navigation control technical field, especially to a kind of unmanned aerial vehicle navigation method and system based on vision and reinforcement learning, method includes: obtaining lagged first time visual image, real-time second time depth image and the continuous sensing data between them;Through the preset distillation vision network extraction global semantic features and with positive shadow image matching, the visual positioning anchor point of first time is solved;Inertial compensation positioning point of current time is obtained by using sensing data to calculate displacement and attitude change in time window, and mapping visual positioning anchor point to second time;Tensor splicing is carried out to inertial compensation positioning point and depth image to build reinforcement learning state space, and control instruction is generated by inputting strategy network;Through inertial compensation mechanism, the time-space deviation caused by visual calculation delay is eliminated, the flight trajectory oscillation problem caused by different step of multi-source heterogeneous data is solved, and the high robustness autonomous navigation and smooth control of unmanned aerial vehicle in dynamic environment are realized.

The invention relates to an environment-friendly water ecology monitoring method and system based on big data, and is constructed based on multi-parameter data fusion and a dynamic anomaly detection mechanism. The system comprises a data acquisition module used for acquiring water quality parameters such as dissolved oxygen, pH value, ammonia nitrogen, conductivity and water temperature, and forming a continuous data sequence through time synchronization; the spectrum mapping module converts the time sequence into frequency domain features and extracts layered frequency band information; the change point detection module identifies an abnormal change trend by using the frequency domain features and generates a statistical index; the threshold judgment module generates an abnormal signal through the dynamic threshold; a feedback updating module adjusts a spectrum weight and a judgment strategy according to the abnormal characteristics; the record output module generates a monitoring result, and continuous sensing and intelligent early warning of the water ecological state are achieved.

The invention discloses a net-shaped sensing system for coastal slope in-situ monitoring and an application method thereof, and belongs to the technical field of geotechnical engineering safety monitoring and coastal protection engineering, the system comprises an implantable sensing network buried in a slope, a multi-channel signal acquisition and demodulation host and a data analysis and early warning platform; the implantable sensing network is composed of a plurality of crossed linear continuous sensing components and node type multi-parameter sensing components located at the crossed positions, and the linear continuous sensing components and the node type multi-parameter sensing components are respectively used for acquiring continuous physical field response information of the side slope distributed along the path and local mechanical state and seepage related state information at key positions; the multi-channel signal acquisition and demodulation host synchronously acquires and analyzes continuous distribution signals and discrete node signals, and the data analysis and early warning platform performs multi-source information fusion analysis and outputs a slope state evaluation and early warning result. According to the invention, long-term, real-time and in-situ monitoring of the multi-physical-field state in the slope can be realized in high-humidity, high-salt and other coastal complex environments.

The invention relates to the technical field of electrostatic protection and industrial safety monitoring, and discloses an ESD intelligent monitoring system and method for multi-source electrostatic data integration, and the system comprises a hardware architecture and a data processing and decision-making unit. The acquisition layer acquires multi-source heterogeneous data, pre-processes the multi-source heterogeneous data, inputs the pre-processed multi-source heterogeneous data into a space-time correlation potential field model construction module, fuses static environment attributes and dynamic disturbance, and calculates an STCPF risk potential field in real time. The risk analysis module identifies a high-risk area through potential field topology analysis and performs early warning; and the regulation and control module solves an electrical safety stability function based on the early warning information, and generates a coordinated regulation and control instruction to close the steady state control loop. And the closed-loop self-calibration module confirms signal backtracking characteristics by using the discharge event and updates model parameters. According to the invention, spatial interpolation and dynamic weight modulation technologies are utilized, global continuous sensing, active adaptive regulation and control and continuous model optimization of electrostatic risks are realized, and monitoring blind areas are effectively eliminated.

The application discloses a preparation method of a capacitive sensing hydrogel, which introduces EGCG as a protective modification layer of MXene nanosheets, enhances the oxidation resistance of MXene, improves the continuous sensing and sensitivity of the MXene hydrogel, introduces 4ARM-PEG-ACLT as a crosslinking agent, utilizes the dynamic covalent bond between APBA and EGCG as a secondary crosslinking point, constructs a double crosslinking point network, effectively improves the mechanical strength and rapid recovery ability of the hydrogel, solves the defects of poor deformation ability and easy oxidation of MXene in the design of a sensor device, and the preparation method is simple and efficient, so that the capacitive sensing hydrogel sensor makes a solid step towards practical application.

This invention discloses a temperature control method and system for automated electrical control cabinets, relating to the field of industrial equipment operating environment regulation technology. The method includes the following steps: collecting cabinet operation change records and temperature change records during automated production cycle changes, arranging them in a uniform chronological order to form a start-stop evolution time series; performing segmented analysis of the operating rhythm based on the start-stop evolution time series, extracting high-frequency pulse segments from the start-stop evolution time series, and calculating the heat accumulation trend based on the high-frequency pulse segments to form a junction temperature evolution curve reflecting internal temperature changes. This invention achieves continuous sensing of internal temperature rise changes by constructing a start-stop evolution time series and extracting high-frequency pulse segments to form a junction temperature evolution curve; further, by identifying abnormal segments to determine the critical start-stop frequency and duration, it coordinates the start-stop interval and air cooling intensity to stabilize the internal heat release rhythm of the cabinet and improve temperature control capabilities.

The application provides a meteorological environment intelligent sensing and real-time monitoring method and system, relates to the technical field of gas phase monitoring, and obtains meteorological environment original data by arranging multiple meteorological environment sensing nodes in a target monitoring area, and generates a multidimensional meteorological state vector according to a preset time window; constructs a meteorological state change vector according to the multidimensional meteorological state vectors of adjacent time windows, compares the meteorological state change vectors of different meteorological environment sensing nodes on a regional scale, forms a regional change benchmark; through consistency determination of the meteorological state change vectors of each meteorological environment sensing node and the regional change benchmark, a local meteorological abnormal evolution process is identified, and a corresponding identifier is generated; for the identified local abnormal area, the collection time window of the meteorological environment original data is dynamically adjusted, and the meteorological state change vector is updated according to the adjusted time window, so that the continuous sensing and real-time monitoring of the local meteorological environment change process are realized.

The embodiment of the invention relates to the technical field of information, and discloses a discontinuous perception area traffic flow estimation method, device and product, and the method comprises the steps: obtaining traffic flow observation data of a target area, and constructing a mask matrix of a missing value position in the traffic flow observation data; calculating a time delay matrix between observation time points; inputting the traffic flow observation data and the mask matrix into a time feature extraction network, and processing by using a long short-term memory network to obtain hidden variables; generating a time decay estimation value containing the time dimension feature; filling missing positions in the traffic flow observation data by using the time attenuation estimation value, and constructing pre-filled graph structure data; inputting the pre-filled graph structure data into a graph attention network, aggregating traffic flow information of adjacent vertexes based on a graph attention mechanism, and generating a spatial dependency estimation value; and fusing the time attenuation estimation value and the spatial dependence estimation value by using a tradeoff coefficient to obtain traffic flow complementation data, thereby making up for the deficiency of traffic situation index data.

Various examples are provided related to high-resolution sediment sensing including, e.g., water depth and / or water velocity sensing. In one example, a sediment dynamics monitoring system for scour, erosion or deposition detection includes a fiber-optic distributed temperature sensing (FO-DTS) sediment dynamics monitoring device including a support structure; a FO cable providing continuous sensing along a length of the support structure; and a heating element collocated along the FO cable; a power controller configured to control heating of the heating element; and a DTS system that can measure a temperature profile along a length of the FO cable. An anomaly in the measured temperature profile indicates an interface surrounding the FO-DTS sediment dynamics monitoring device. interface can be a sediment-water interface or a water-air interface.