Abstract: A system and a method for tracking individual persons across multiple cameras and over extended periods include an event streaming processing circuitry, a server, an application processing circuitry, a Tensor Database system and an output device. The event streaming processing circuitry receives streams of data from the cameras. The server includes Artificial Intelligence (AI) based models for person detection and embedding vector extraction to obtain person bounding box images and person embedding vectors. The application processing circuitry includes an Embedding Manager that maintains a collection of distinct embedding vectors for each person and an ID Manager that maps short-term person IDs to respective long-term IDs. The ID Manager associates the person with a unique long-term ID across the cameras. The Tensor Database system maintains the extracted embedding vectors. The output device tracks the person appearing across the cameras based on the long-term ID.

Abstract: A method, system, and computer readable medium are described to capture, detect, and recognize faces using machine learning and a single-stage face detector. A method to determine live faces from spoof 2D and spoof 3D images using a liveness score as well as a method to classify faces using machine learning deep convolutional neural networks is also described.

Abstract: A light intensity monitoring system, a light intensity monitor and a method for monitoring light intensity the light intensity monitor attached to a vehicle roof. The light intensity monitor includes light sensors which measure light intensity at a top wall and two sidewalls and records the location of the vehicle at precise time intervals using a global positioning sensor. A microcontroller within the monitor compiles the measured data into communications packets, which include light intensity measurements and the corresponding vehicle location for each measurement period. These packets are then wirelessly transmitted to a remote computing device using either a wireless network communications unit or a dual-mode near-field communications unit. The remote device receives the data and utilizes a mapping application to display the various light intensity levels, expressed in lux, with the location of the measurement.

Abstract: A method and system for constructing a three-dimensional (3D) aerial survey of a city street scene include obtaining a plurality of video frames from a calibrated multi-camera setup covering a 360-degree view mounted on a moving vehicle. The plurality of video frames is split into a plurality of 3D parts containing a subset of the plurality of video frames and preprocessing the subset of the plurality of video frames of each part of the plurality of parts to obtain a calculated information. Further, constructing, by the processing circuitry, a 3D representation of each part of the plurality of parts based on the calculated information to obtain a plurality of local 3D reconstructed scene intervals. The method includes stitching and filtering, by the processing circuitry, the plurality of local 3D reconstructed scene intervals to construct the 3D city street scene.

Abstract: An Arabic information extraction apparatus includes one or more processors configured to: receive a query comprising a long query or a short query; extract, using one or more language models, a named entity and a keyword from the query to generate extracted information; classify, using one or more classification models, the query to generate a classified query; convert the classified query and the extracted information into a dense vector representation; and determine and output a similarity match between the dense vector representation and a document vector representation of a knowledge base comprising an Islamic law document.

Abstract: A computer-implemented method of generating speech from a source voice of a speaker in a language for a speech device connected to the computer, where the speech device language is a non-native language of the speaker. The method includes inputting speech in the source voice, encoding the speech in the source voice into a content vector, retrieving top k similar content vectors from a vector representation database that substantially match phonetic patterns of the encoded source voice, generating a new voice waveform based on the similar content vectors that contains linguistic content of the source voice, but with the phonetic patterns of a native speaker's voice of the speech device language, and outputting the new voice waveform.

Abstract: An automated system for generating Frequently Asked Questions (FAQs) from call center interactions includes a call center device for recording audio conversations between agents and customers, and a backend system. The backend system segments the conversation between agent and customer speech, converts the segmented speech into text using an Automatic Speech Recognition engine, and generates FAQs using a Large Language Model. Each FAQ includes a query statement corresponding to the customer's speech and at least one answer statement corresponding to the agent's speech. The system also includes mechanisms for selecting relevant, non-duplicate FAQs, determining the importance of each FAQ based on frequency, sentiment, and coherence scores, and dynamically updating the FAQ database in real-time. A user interface displays the generated FAQs with dropdown arrows to view the answers, enhancing customer service efficiency and accuracy by providing immediate, relevant responses to common inquiries.

Abstract: An automated system for generating Frequently Asked Questions (FAQs) from call center interactions includes a call center device for recording audio conversations between agents and customers, and a backend system. The backend system segments the conversation between agent and customer speech, converts the segmented speech into text using an Automatic Speech Recognition engine, and generates FAQs using a Large Language Model. Each FAQ includes a query statement corresponding to the customer's speech and at least one answer statement corresponding to the agent's speech. The system also includes mechanisms for selecting relevant, non-duplicate FAQs, determining the importance of each FAQ based on frequency, sentiment, and coherence scores, and dynamically updating the FAQ database in real-time. A user interface displays the generated FAQs with dropdown arrows to view the answers, enhancing customer service efficiency and accuracy by providing immediate, relevant responses to common inquiries.

Abstract: Disclosed is a method and apparatus for identifying similar record elements to a query, the method including receiving a query, determining an index for the query, generating candidate records from a reference list to match the query based on the index and applying any one or any combination of a q-gram filter, a length filter, and a shared character count (SCC) filter, determining similarity scores of each of the candidate records identifying records from among the candidate records having a similarity score greater than or equal to a threshold, selecting data records similar to the query based on sorting the selected records according to respective similarity scores, and outputting one or more of the selected data records.

Abstract: A computer-implemented method of generating speech from a source voice of a speaker in a language for a speech device connected to the computer, where the speech device language is a non-native language of the speaker. The method includes inputting speech in the source voice, encoding the speech in the source voice into a content vector, retrieving top k similar content vectors from a vector representation database that substantially match phonetic patterns of the encoded source voice, generating a new voice waveform based on the similar content vectors that contains linguistic content of the source voice, but with the phonetic patterns of a native speaker's voice of the speech device language, and outputting the new voice waveform.

Abstract: A system and computer-implemented method of attention tracking and includes obtaining a video stream of a predefined area, the predefined area including at least one person, detecting a person image of the person in the predefined area, detecting objects in the predefined area, extracting gaze points and determining a possible attention target of the detected person, continuously tracking of attention direction of the person, determining in real time an attention score based on the attention target, and dynamically displaying, in a display device, the video stream together with attention information, including the attention score, for the person. The system and method provides real time determining of a personalized attention score for an individual student or an overall attention score for a group of students attending a lecture in a classroom environment.

Abstract: A method includes receiving an input including a starting location, a destination, a time of arrival, a plurality of user-defined events, and a preparation time from a user; receiving traffic data from an integrated sensor system including a computing device including a processor, a memory, and a communication module, and an internet of things (IoT) sensor communicatively connected to the computing device, the IoT sensor configured to obtain traffic data; generating a first route option from the starting location to the destination based on the traffic data and the input from the user; determining, via an artificial intelligence model and based on the first route option, a total time to the destination; determining a dynamic alarm set time based on the total time to destination and the time of arrival; and instructing a first electronic device to set a dynamic alarm based on the alarm set time.

Abstract: In some embodiments, a method and system for detecting surface changes in a geographical area over time is disclosed. The method includes encoding pre- and post-event images using frozen features of Segment Anything Model (SAM), processing encoded embeddings by a change modeler, processing change embeddings by a change prompter, decoding change embeddings and prompt embeddings using SAM to obtain change masks which include the detected changes.

Abstract: A system for detection of a vehicle that blocks an ambulance while the ambulance is responding to an emergency call. The system includes a camera mounted on the ambulance that captures images or video of the surrounding area. A processor, such as an edge computing device with a graphical processing unit (GPU), analyzes the captured data to identify vehicles obstructing the ambulance's path. The system can identify both a leading violating vehicle that directly blocks the ambulance and a primary violating vehicle further ahead that may be causing the obstruction. The system also includes a communication unit to transmit data to a web-based portal or a cloud-based AI engine for further analysis and action.

Abstract: A light intensity monitoring system, a light intensity monitor and a method for monitoring light intensity the light intensity monitor attached to a vehicle roof. The light intensity monitor includes light sensors which measure light intensity at a top wall and two sidewalls and records the location of the vehicle at precise time intervals using a global positioning sensor. A microcontroller within the monitor compiles the measured data into communications packets, which include light intensity measurements and the corresponding vehicle location for each measurement period. These packets are then wirelessly transmitted to a remote computing device using either a wireless network communications unit or a dual-mode near-field communications unit. The remote device receives the data and utilizes a mapping application to display the various light intensity levels, expressed in lux, with the location of the measurement.

Abstract: A system and method includes a textual document search engine. The method initializes the textual document search engine by inputting, into a memory, a very large number of documents, where each document has textual sentences, and each sentence of each document has m semantic embedding vectors. The method maps the m semantic embedding vectors to 1-dimensional vectors of Hilbert numbers using a Hilbert curve transformation, constructs an index table with the 1-dimensional vectors, and stores the index table in the memory. The index table is used for efficient search by inputting a full query document, which has embedding vectors corresponding to sentences in the query document, where the query embedding vectors are mapped into 1-dimensional vectors of Hilbert numbers using Hilbert curve transformation. The index table is searched using the Hilbert numbers and candidate documents are retrieved that are similar to the query document based on the Hilbert numbers.

Abstract: A system and method measures in real time the reputation of products or services based on customer reviews and social media mentions. The method includes cyclically refining a search to collect, using a natural language processing (NLP) model, data relating to the products or services, and simultaneously recognizing product/service aspects and classifying sentiment for the collected data, using a single multi-task machine learning model.

Abstract: A tailgating detection system and method includes a single monocular camera, an embedded computer system for determining a tailgating event based on images captured by the camera, the determining of the tailgating event including detecting and tracking wheels of front and tailgating vehicle candidates and determining respective speeds relative to a speed of a vehicle that the camera is mounted and using frame rate of the camera, a location determining device for determining the location where the tailgating event occurred, and a communication unit for transmitting a notification of the tailgating event including the location where the tailgating event occurred.

Abstract: A system, apparatus and method of embedded ego vehicle speed estimation apparatus, including a car-mounted monocular camera for capturing a sequence of video frames of an outdoor scene from a moving car, where the outdoor scene includes a road, as a camera channel, and processing circuitry. The processing circuitry is configured with a single-shot network and a 3D convolutional neural network (3D-CNN), the single-shot network segments features of the road in the video frame sequence and generates a masked-attention map for the segmented road features, a concatenation circuit concatenates the masked-attention map as an additional channel to the camera channel to generate a masked-attention input, and the 3D-CNN network receives the masked-attention input and generates an estimated speed of the ego vehicle based on displacement of the segmented road features in the video sequences.

Abstract: A stackable, non-contact device for operating elevator buttons is described. The non-contact device includes a servo mechanism with a dual-arm configured to press either of two elevator buttons. Two proximity sensors are configured to register the approach of a finger touch of either proximity sensor, which commands the servo mechanism to press the corresponding elevator button. The stackable, non-contact device includes a microcontroller configured to receive near field communications from a mobile application, which includes commands for pressing a specific elevator button.