Vehicle intelligence tool for early warning with fault signature

    公开(公告)号:US12205418B2

    公开(公告)日:2025-01-21

    申请号:US17464056

    申请日:2021-09-01

    Abstract: A method for early warning is provided. The method clusters normal historical data of normal cars into groups based on the car subsystem to which they belong. The method extracts (i) features based on group membership and (ii) feature correlations based on correlation graphs formed from the groups. The method trains an Auto-Encoder and Auto Decoder (AE&AD) model based on the features and the feature correlations to reconstruct the normal historical data with minimum reconstruction errors. The method reconstructs, using the trained AE&AD model, historical data of specific car fault types with reconstruction errors, normalizes the reconstruction errors, and selects features of the car faults with a top k large errors as fault signatures. The method reconstructs streaming data of monitored cars using the trained AE&AD model to determine streaming reconstruction errors, comparing the streaming reconstruction errors with the fault signatures to predict and provide alerts for impending known faults.

    Semantic image capture fault detection

    公开(公告)号:US12205356B2

    公开(公告)日:2025-01-21

    申请号:US18188766

    申请日:2023-03-23

    Abstract: Methods and systems for detecting faults include capturing an image of a scene using a camera. The image is embedded using a segmentation model that includes an image branch having an image embedding layer that embeds images into a joint latent space and a text branch having a text embedding layer that embeds text into the joint latent space. Semantic information is generated for a region of the image corresponding to a predetermined static object using the embedded image. A fault of the camera is identified based on a discrepancy between the semantic information and semantic information of the predetermined static image. The fault of the camera is corrected.

    Free flow fever screening
    3.
    发明授权

    公开(公告)号:US12201403B2

    公开(公告)日:2025-01-21

    申请号:US17325613

    申请日:2021-05-20

    Abstract: A method for free flow fever screening is presented. The method includes capturing a plurality of frames from thermal data streams and visual data streams related to a same scene to define thermal data frames and visual data frames, detecting and tracking a plurality of individuals moving in a free-flow setting within the visual data frames, and generating a tracking identification for each individual of the plurality of individuals present in a field-of-view of the one or more cameras across several frames of the plurality of frames. The method further includes fusing the thermal data frames and the visual data frames, measuring, by a fever-screener, a temperature of each individual of the plurality of individuals within and across the plurality of frames derived from the thermal data streams and the visual data streams, and generating a notification when a temperature of an individual exceeds a predetermined threshold temperature.

    PROMPT-BASED MODULAR NETWORK FOR TIME SERIES FEW SHOT TRANSFER

    公开(公告)号:US20250005373A1

    公开(公告)日:2025-01-02

    申请号:US18749887

    申请日:2024-06-21

    Abstract: Systems and methods are provided for adapting a model trained from multiple source time-series domains to a target time-series domain, including integrating input data from source time-series domains to pretrain a model with a set of domain-invariant representations, fine-tuning the model by learning prompts specific to each source time-series domain using data from the source time-series domains, and applying instance normalization and segmenting the time-series data into subseries-level normalized patches for the target time-series domain. The normalized patches are fed into a transformer encoder to generate high-dimensional representations of the normalized patches, and a limited number of samples from the target time-series domain are utilized to learn the prompt specific to the target domain. Cosine similarity between the prompt of the target domain and the prompts of source domains is calculated to identify a nearest neighbor prompt, which is utilized for model prediction in the target time-series domain.

    DETECTING ARTIFICIAL INTELLIGENCE GENERATED COMPUTER CODE

    公开(公告)号:US20240419801A1

    公开(公告)日:2024-12-19

    申请号:US18731845

    申请日:2024-06-03

    Abstract: Systems and methods for detecting artificial intelligence (AI) generated computer code. Lines of code can be masked from a candidate code to obtain perturbed codes. Missing code can be generated from the perturbed codes by employing an AI code generator model to obtain machine-filled codes. Probabilities of the candidate code probability and the machine-filled codes as AI-generated can be predicted by employing a surrogate model. The candidate code can be distinguished as AI-generated by comparing the probabilities against a detection threshold to obtain detection results.

    FIBER-OPTIC ACOUSTIC ANTENNA ARRAY AS AN ACOUSTIC COMMUNICATION SYSTEM

    公开(公告)号:US20240405890A1

    公开(公告)日:2024-12-05

    申请号:US18731283

    申请日:2024-06-01

    Abstract: Disclosed are systems, methods, and structures employing a distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) system operating as an underwater wireless acoustic antenna in which an optical fiber sensor cable serves as a distributed acoustic antenna that receives multiple data from transmitters using an optical interrogator. Sensing channels, in the form of acoustic-antenna-array systems are located near transmitters taking advantage of the fact that these channels are automatically synchronized. The sensing channels may also be manually selected from software controlling the interrogator, and acoustic repeaters may be introduced as one data transmission mechanism. Acoustic tata transmission using an orthogonal frequency division multiplexed (OFDM) signal is demonstrated as a cure for data transmission using a DAS, such as multipath fading impacting bit error rate (BER) and limitations in acoustic transmission bandwidth.

    RULE-BASED EDGE CLOUD OPTIMIZATION FOR REAL-TIME VIDEO ANALYTICS

    公开(公告)号:US20240403137A1

    公开(公告)日:2024-12-05

    申请号:US18678121

    申请日:2024-05-30

    Abstract: Systems and methods are provided for dynamically optimizing microservice placement in a distributed edge and cloud computing environment, including receiving application specifications that include telemetry data collection methods, placement rules, and modes of operation, validating the received application specifications to ensure completeness and correctness, and composing an application graph where vertices represent microservices and edges represent connections between the microservices. Availability of resources specified in the application graph is checked, and the microservices are deployed according to initial placement rules. Telemetry data from the deployed microservices and underlying infrastructure is collected and evaluated against the placement rules, and the placement of microservices is dynamically adjusted responsive to a determination that current microservice placement is suboptimal based on the evaluating of the collected telemetry data.

    Learning word representations via commonsense reasoning

    公开(公告)号:US12154024B2

    公开(公告)日:2024-11-26

    申请号:US17398476

    申请日:2021-08-10

    Abstract: A method trains a recursive reasoning unit (RRU). The method receives a graph for a set of words and a matrix for a different set of words. The graph maps each word in the set of words to a node with node label and indicates a relation between adjacent nodes by an edge with edge label. The matrix indicates word co-occurrence frequency of the different set of words. The method discovers, by the RRU, reasoning paths from the graph for word pairs by mapping word pairs from the set of words into a source word and a destination word and finding the reasoning paths therebetween. The method predicts word co-occurrence frequency using the reasoning paths. The method updates, responsive to the word co-occurrence frequency, model parameters of the RRU until a difference between a predicted and true word occurrence are less than a threshold amount to provide a trained RRU.

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