7 results about "NarrowBand IOT" patented technology

This invention discloses a method and system for radio frequency fingerprinting of narrowband IoT transceivers. The method involves a receiver acquiring wireless messages sent by the transceiver to be identified, obtaining in-phase / orthogonal discrete sample sequences, locating and extracting preamble sample segments, performing a short-time Fourier transform on the preamble sample segments to generate a spectrogram energy matrix, and extracting compressed time-frequency features through singular value decomposition. The main component of the carrier frequency offset is obtained based on the cross-correlation peak position shift between rising and falling chirps, and the carrier frequency offset correction component is obtained based on the phase drift of adjacent rising chirps. The compressed time-frequency features and the carrier frequency offset estimation results are concatenated into a fused feature vector, which is then input into a convolutional neural network classification model to output the device category and category confidence. This invention reduces the dependence on channel location features and decreases model input overhead, making it suitable for online identification of narrowband IoT devices.

The invention discloses a narrowband environment video code rate optimization system and method based on a convolutional neural network, and belongs to the technical field of video processing. The method comprises the following steps: after a video frame sequence is obtained by configuring a video transmission synchronization time sequence, setting the grouping number of a grouping convolution CNN model according to the number of feature types, and generating an initialized input feature map; establishing a pixel two-dimensional coordinate system, and dynamically adjusting the convolution weight by combining the real-time bandwidth and the transmission delay to obtain a local enhanced pixel value; constructing a pixel state matrix, and calculating the video frame sequence similarity of the current and historical synchronous transmission stages; the average similarity of the windows is calculated through sliding window grouping, a trend function is constructed, the scale of the sliding windows is optimized, the picture change trend is judged according to the slope of the trend function, and the code rate compression mode of the next stage is indicated. Dynamic balance of video transmission image quality and transmission efficiency in a narrowband environment is realized, the problems of poor adaptability and adjustment lag of a traditional scheme are solved, and the method is suitable for a narrowband Internet of Things scene.

This invention discloses a method and system for uplink single-carrier symbol correction in narrowband IoT based on a Costas ring, supporting the narrowband IoT protocol specifications defined in 3GPP Release 13. This invention combines the Costas ring with the characteristics of narrowband IoT uplink, utilizing software-defined radio equipment to acquire uplink single-carrier signals. By reconstructing the Costas ring structure, a nonlinear phase detector and a low-pass filter are jointly designed to form a loop filter with joint gain. A digital frequency synthesis module replaces the traditional voltage-controlled oscillator, dynamically compensating for symbol frequency offset and phase distortion based on the error signal output from the Costas ring, thereby completing the demodulation of the real narrowband RF signal. This invention solves the symbol distortion problem caused by frequency offset, multipath effects, and hardware nonlinearity in narrowband IoT scenarios, and can significantly reduce the communication bit error rate compared to traditional channel estimation schemes.

This invention discloses a statistical system and method for monitoring the condition of construction machinery based on narrowband Internet of Things (IoT) technology. The system includes the following steps: collecting operating status signals of construction machinery and generating continuous raw time-series data; preprocessing the data to construct a cumulative deviation statistical sequence; performing change point detection at the edge to generate structured change point events; transmitting the structured change point events to the cloud via narrowband IoT; constructing a change point event sequence based on the received structured change point events in chronological order; defining stable operating segments based on the time intervals between adjacent change points; constructing time-dependent covariates within each stable operating segment and reconstructing them as new change point events arrive; inputting the time-dependent covariates into a proportional hazards model and using the change point time as a risk function to generate a risk value sequence segmented by nodes; forming a equipment risk ranking result and outputting a maintenance priority list. This invention enables remote monitoring, statistical analysis, and maintenance decision-making for the operating status of construction machinery.

This invention relates to the field of intelligent monitoring and proposes an acoustic-vibration multimodal edge cloud collaborative monitoring method based on adaptive dual entropy. By extracting features from multimodal signal sample data, it achieves second-level output of window-level state features and triggers alarms, meeting the real-time monitoring requirements for equipment start / stop identification and rapid response to abnormal operating conditions. It uses three-dimensional features to replace the uplink of complete acoustic waveforms and high-dimensional time-frequency matrices, significantly reducing the pressure on wireless link bandwidth and cloud storage and computing load. It can still connect a large number of devices and achieve long-term online monitoring in narrowband IoT environments, significantly improving scalability and cost controllability. It ensures real-time performance and reliability when deployed on a large scale in resource-constrained industrial sites. Based on multimodal feature fusion and discrimination, it can stably identify multi-level states, improving robustness and discrimination accuracy in complex operating conditions and high-noise environments. This invention improves the stability and accuracy of intelligent monitoring of electromechanical equipment.

This invention relates to an IoT-connected wall-mounted water dispenser water quality monitoring and purification system, method, and storage medium, specifically in the field of water quality monitoring for water dispensers. It achieves high-precision monitoring of water quality parameters by collaboratively correcting sensor data using digital twins and adaptive filtering. Utilizing time-series reconstruction and intelligent scoring mechanisms, it can accurately identify abnormal events and extract key features. Through reinforcement learning-driven resource perception strategy optimization, it can intelligently decide the timing and content priority of data transmission under limited network and energy constraints. Finally, through cross-layer parameter dynamic adaptation and load optimization, it ensures reliable and efficient transmission of key information in narrowband IoT, thereby achieving comprehensive benefits of accurate perception, timely early warning, and energy-saving communication.

This disclosure relates to a method, apparatus, storage medium, and electronic device for verifying the location of a user equipment, and pertains to the field of Internet of Things (IoT) communication technology. The method includes: for narrowband IoT satellite scenarios, a mobility management function entity can send control information to the radio access network. This disclosure solves the problem in related technologies where the coarse location information of a user equipment cannot meet the corresponding requirements, thus hindering accurate location verification.