627 results about "Notification system" patented technology

A system for facilitating battery fault prediction is configurable to: (i) access a set of raw data comprising battery sensor data associated with a physical battery and operation data associated with operation of the physical battery; (ii) obtain an estimated battery state for the physical battery by utilizing the battery sensor data as input to a battery digital twin; (iii) obtain a battery fault prediction by utilizing (a) the estimated battery state obtained via the battery digital twin and (b) operation input based on the operation data as input to a battery fault prediction model, and wherein the battery fault prediction comprises one or more likelihood metrics indicating a likelihood of one or more battery faults occurring within one or more predetermined time periods; and (iv) cause presentation of an alert via a battery fault notification system.

Systems and methods for accident detection and notification are described. In some embodiments, an Information Handling System (IHS) may include: an Embedded Controller (EC); and a memory coupled to, or integrated into, the EC, where the memory includes program instructions that, upon execution by the EC, cause the EC to: receive sensor data from a sensor; determine, based at least in part on the sensor data, that an accident occurred to the IHS; and in response to the determination, issue a notification. In some embodiments, to issue the notification, the program instructions, upon execution, further cause the EC to: transmit information to a second IHS via a personal area network (PAN).

Techniques for generating notifications with emotion-inciting images based on the context of report data, are discussed herein. A notification system may configure components and models to receive report data and analyze the report data for context data. The context data may include contextual information associated with the report data and / or a report recipient. The system may generate an image text prompt based on the context data. The system may use the image text prompt as input for an artificial intelligence (AI) image generator and receive an emotion-inciting image as output. The system may generate a notification for the report data and transmit the notification with the emotion-inciting image.

The invention provides a service system disaster recovery system based on cloud computing, and relates to the technical field of disaster recovery backup recovery and cloud computing, and the system comprises a software application registration and arrangement module which is used for registering an entity object of a service application to a software warehouse, arranging a topological structure of the service application according to a dependency relationship, and configuring a disaster recovery strategy; the software application deployment disaster recovery module is used for automatically deploying a pull-up service application and backing up the pull-up service application according to a disaster recovery strategy; the fault monitoring and damage decision-making module is used for performing fault monitoring and damage decision-making on the application instance, and sending out an alarm notification when a fault or a disaster is monitored; and the system recovery disaster recovery switching module is used for executing system recovery operation when receiving the alarm notification, executing disaster recovery switching operation such as upstream data flow and service access entry redirection, and realizing system recombination recovery and service replacement. The invention further provides a service system disaster recovery method based on cloud computing, electronic equipment and a storage medium.

A system for filtering and presenting notifications received by an aircraft includes a processor, a display device, a communication device, and computer-readable memory. The computer-readable memory encoded with instructions that, when executed by the processor, cause the system to perform the following steps. The system receives one or more broadcast notifications. The notifications are, for example, Notices to Air Missions (NOTAMs). The system filters the one or more broadcasted notifications based upon applicability to a present flight plan to generate applicable notifications. The system filters the applicable notifications based upon one or more filtering criteria to assign a criticality to each of the applicable notifications. The system display, via the display device, the applicable notifications based upon the criticality of each of the applicable notifications. The system outputs alternate flight plans due to restrictions on the present flight plan.

An obstacle determination unit determines whether an obstacle is present in a periphery of the work machine. An action detection unit detects an action of an operator of the work machine. An action determination unit determines whether the detected action is a confirmation action executed at the time of safety confirmation. A notification unit changes a mode of notification when the action is determined to be the confirmation action.

To provide a notification transmitter and receiver, a notification system, a fire extinguisher stand, a notification transmitter, a notification transmitter and a notification receiver that can easily carry out a rapid and continuous firefighting activity.SOLUTION: A notification transmitter and receiver which is attached to a fire extinguisher stand for placing a fire extinguisher, and comprises: a transmitting unit that transmits instruction information corresponding to a notification instruction to an external field when the fire extinguisher is removed from the fire extinguisher stand; a receiving unit that receives the instruction information transmitted from the external field; and a notification unit that notifies a presence of the fire extinguisher when the instruction information is received by the receiving unit.SELECTED DRAWING: Figure 2

A system enables management of dispensable units by supporting functions such as retrieval, scheduled distribution, analysis, and notifications. To this end, a dispensable retrieval mechanism may be programmed to carry out blind retrievals of dispensable units using a retrieval strategy with a predetermined sequence of retrieval attempts (e.g., fixed or varying two-dimensional retrieval patterns), which may be open loop or closed loop. Techniques may also include the identification of dispensable units through optical sensors and weight measurement devices that can detect, e.g., a texture, a shape, and a size of dispensable units. Such identification can be used to program retrieval attempts by a retrieval robot and in the formulation of the retrieval pattern. Additionally, networked notification systems for dispensable units can be used for updating rules or schedules related to the dispensable units, or alerting users and remote resources of any potential misuse or hazards of the dispensable units.

An asset health system includes an edge-based computing device that receives high-granularity asset data for an asset from an asset data source or asset database and receives contextual data from a contextual database. The edge-based computing device processes the asset data and the contextual data with a machine-learned model. The machine-learned model includes processor-executable instructions for extracting run cycle data from the asset data to determine a run cycle of the asset, creating a feature vector based on the asset data that characterizes the run cycle, comparing the feature vector to a nominal feature vector to detect one or more anomalies, validating the one or more detected anomalies with the contextual data, determining a health index for the asset based on the one more anomalies, determining a mitigating action for mitigating the anomalies, and notifying a system operator regarding the one or more detected anomalies, health index, and mitigating actions.

The invention discloses a DICT operation and maintenance notification method and device, terminal equipment and a storage medium, and the method is realized based on a DICT operation and maintenance notification system, and comprises the following steps: equipment classification and management: collecting information about equipment performance parameters from various sensors; processing the collected data by using a machine learning algorithm, and extracting key features; dividing the equipment into different groups according to feature similarity; staff classification and management: classifying and scoring professional skills of the staff; tracking and recording various item experiences completed by each person; classification and scoring are performed in combination with professional skills, and comprehensive rating is given to each worker through personal experience; according to the method, key features can be automatically extracted, intelligent matching of tasks and maintenance personnel is realized, and the matching precision and efficiency are improved; the load condition of each person is calculated according to the current task number and the predicted completion time of each person, corresponding adjustment is made accordingly, and resource waste and excessive load are avoided.

Example embodiments relate to train data recorder and event notification systems and techniques for using such systems. An example device includes a housing configured to attach onto a train with multiple sensors located in the housing, such as a Global Navigation Satellite System (GNSS) receiver, an inertial measurement unit (IMU), and a camera that can capture images of an environment outside the housing. The device also includes a memory and a processor located inside the housing where the processor is configured to receive sensor data from at least one of the sensors and store the sensor data on the memory. A central computing system can aggregate location-based data generated by train data recording devices positioned on one or multiple trains and map the data to the network of train tracks to detect trends and provide insights to operators.

A patient support apparatus and a method of notifying persons within a vicinity of the patient support apparatus are disclosed. The patient support apparatus includes a patient support structure for supporting a patient, an actuator for moving the patient, a notification system, and a controller coupled to the notification system and the actuator. The controller receives a selection of a remote control function via a communication network, generates a notification in response to receiving the selection of the remote control function, and transmits an output signal to the actuator based on the selection of the remote control function. The notification system executes the notification prior to the controller transmitting the output signal to the actuator.

A notification system includes: an obtainer that obtains an audio content to be notified of and a result of sensing by a sensor that senses a space in which a notification device is located; a determiner that determines whether a first user ready to listen to the audio content notified of by the notification device is in the space, based on the result of the sensing; and a controller that performs first control of controlling notification of the audio content by the notification device depending on whether the first user is in the space. In the first control, the controller: causes the notification device to notify of the audio content, when the first user is in the space; and prevents the notification device from notifying of the audio content, when the first user is not in the space.

Systems, methods, and software are disclosed herein for anomaly detection in a wireless communication network based on congestion notification in various implementations. In one example, a computing apparatus processes network telemetry data and congestion data using a machine learning model trained to detect anomalous behavior on wireless communication network. In response to detecting the anomalous behavior, the computing apparatus identifies a source of the anomalous behavior on the network and initiates an action with respect to a network function associated with the source of the anomalous behavior to mitigate one or more effects of the anomalous behavior.

A pedal touch anomaly notification system for a vehicle is provided. The system includes the vehicle itself, and at least one sensor configured to capture information about the position or orientation of the driver's foot relative to a control pedal of the vehicle. A processor uses the captured information, as well as a database containing baseline information and variance information about expected positions or orientations of the driver's foot relative to the control pedal. Based on the captured information, the processor determines the position or orientation of the foot of the driver relative to the control pedal, and compares the determined position or orientation to the baseline information and variance information. If the position or orientation fall outside the variance information, the processor generates a driver alert.

A system for a security platform and services for protecting an artificial intelligence system, comprising: wherein the security platform detects all events and creates a log of anomalous events; wherein a detector detects malware based on the anomalous events; wherein the security platform analyzes the malware by creating a risk analysis based on each detected malware; wherein based on the risk analysis, the security platform engages in adversarial threat mapping; wherein adversarial threat mapping includes input filtering, output filtering and masking; wherein the security platform also tracks the malware utilizing a variety of tracking services; wherein, if malware is detected, then the security platform informs a user of the system that the user has been hacked; wherein if the malware is contained, the security platform attempts to identify where the malware came from; wherein 1 form of finding an origin of the malware is engaging in incident correlation.

Techniques for filtering the output of supplemental content are described. When a supplemental output system (e.g., a supplemental content system or notification system) receives supplemental content for output, the supplemental output system sends a user identifier (of the recipient user) and the supplemental content to separately implemented filtering component. The filtering component uses a machine learning (ML) model to determine a topic of the supplemental content. The filtering component determines whether the supplemental content should not be output based on the ML model-determined topic, one or more guardrail policies of the supplemental output system, and user frustration data regarding previously output supplemental content. Use of the ML model to determine the topic prevents a content publisher from surreptitiously associating supplemental content with a specific topic in an effort to bypass topic-based output guardrails.

The invention relates to an intelligent bid evaluation expert extraction method and system in the technical field of bidding and tendering information management. The method comprises the following steps: S1, constructing an expert multi-dimensional portrait; s2, receiving review project information, analyzing and calculating relevancy between a project demand vector and each expert capability vector, and screening candidate experts; s3, performing intelligent scheduling and priority ranking according to the historical response rate, attendance rate and evaluation of the candidate experts; s4, carrying out credible evidence storage on key data of the extraction process by utilizing a block chain, and ensuring tampering prevention and traceability of the extraction process and expert information; s5, at the appointed time and place before bid opening, decrypting and reviewing expert sensitive information under supervision, and completing confirmation and notification of a final expert group; the system comprises an expert database management module, a semantic matching module, an intelligent scheduling module, a block chain evidence storage module, a security decryption module and a visual interface. According to the extraction method and the system thereof, the precision, the intelligence and the security of expert extraction can be realized.

A remote operation notification system includes a determination section and a notification section. The determination section is configured to determine whether there is a remote operation performed by a worker of a board work machine configured to perform predetermined board work on a board. The notification section is configured to give a notification of the remote operation performed by a specific worker of the board work machine, who is the worker who performs the remote operation on the board work machine, to at least a general worker, who is the worker other than the specific worker, among the specific worker and the general worker when the determination section determines that there is the remote operation.

An emergency management system (EMS) generates a likelihood of a 911 service outage for a public safety access point (PSAP). The EMS receives supplemental call data for mobile devices that initiated 911 calls to a public safety answering point (PSAP). The EMS generates a 911 call volume metric for the 911 calls. The EMS receives a number of queries from the PSAP for a portion of the supplemental call data that corresponds to the 911 call volume metric. The EMS tracks the number of queries received from the PSAP. The EMS determines the likelihood of a 911 service outage for the PSAP based on the 911 call volume metric and the number of queries received. The EMS notifies the PSAP of the likelihood of the 911 service outage (e.g., with an outage score).

This notification system is provided with: a fitting room area entry / exit detection unit that detects users entering and exiting a fitting room area in which fitting rooms are provided; a fitting room area reading unit that, when a user enters or exits the fitting room area, reads product identification information for a product from a product price tag, attached to the product and including an RFID tag, via a reading device installed at an entrance / exit of the fitting room area; an individual fitting room entry / exit detection unit that detects an entry / exit of a user to / from an individual fitting room; a fitting room reading unit that reads the identification information for the product from the price tag via a reading device installed in the individual fitting room; and an output control unit that issues a notification if a combination of a reading state of the price tag in the individual fitting room, an entry / exit state of the user in the individual fitting room, an entry / exit state of the user in the fitting room area, and a reading state of the price tag in the fitting room area is not normal.

A patient support apparatus includes a base frame, lift mechanism supporting an upper frame relative to the base frame, a load frame, and a plurality of deck sections, a patient support surface, and a number of barriers positioned about the patient supporting surface. The patient support apparatus includes a notification system for visually notifying a caregiver of a condition or status of a component of the patient support apparatus.

A 5G server system establishes a wireless connection between a wireless device and a data network (DN) subsystem through a network slice. A user plane function (UPF) subsystem generates an aggregated wireless connection between the UPF subsystem and the DN subsystem by augmenting the wireless connection with additional network connections. The DN subsystem and the UPF subsystem transmit data packets from a Low Latency Low Loss Scalable Throughput (L4S) application server to the wireless device via the aggregated wireless connection. In response to a detection of the risk of reduced service performance, the system adds a notification to a respective data packet. The system causes the wireless device to forward a feedback message to the L4S application server upon receiving the notification. The system performs an action to prevent reduced service performance in response to receiving a request from the L4S application server.

The invention relates to a scale out network backup path fast switching notification system and method, and aims to solve the problem that the existing VRRP / BFD protocol switching time cannot meet the high real-time requirement of an AI server scale out network. The scheme is realized through a collaborative architecture of a CPU (Central Processing Unit), an inspection FPGA (Field Programmable Gate Array) and power supply monitoring: the CPU runs a VRRP / BFD (Bidirectional Forwarding Detection) protocol stack and maintains a state table, and the FPGA is responsible for detecting a power supply fault, a port fault and GPU alarm in real time, and generating and sending a pre-installed message in one main frequency period; and the power supply monitoring module ensures that power supply is maintained for more than or equal to 5ms after sudden power failure through the energy storage capacitor, so that complete transmission of fault messages is ensured. The system has the advantages that the system supports multi-scale out interface redundancy, the end-to-end delay of fault detection and backup path switching is smaller than or equal to 1ms by adopting a low-power-consumption switching chip and independent minimum power domain design, the fault response speed and reliability of an AI server scale out network are remarkably improved, and the system is suitable for guaranteeing the network continuity of a high-density AI training cluster.

Processing a vehicle maintenance transaction is provided. The method comprises receiving the transaction and entering the transaction into a blockchain ledger. In response to the transaction, an enhanced smart contract in the blockchain ledger executes. The enhanced smart contract specifies a number of compliance requirements to complete the transaction and automates a workflow for the transaction according to the compliance requirements. A number of notifications regarding the transaction are generated to a number of subscribers to the blockchain ledger. Confirmation of fulfillment of the compliance requirements is received from the subscribers to complete the transaction. The enhanced smart contract, verifies fulfillment of the compliance requirements, and completion of the transaction is recorded in the blockchain ledger.

An equipment recovery notification method includes: when two or more units of equipment among units of equipment that execute a first process are stopped, estimating, from among one or more units of subsequent-process equipment that execute a second process subsequent to the first process, a productivity of one or more units of the subsequent-process equipment that use at least one of components produced by the two or more units of equipment; identifying one unit of equipment among the two or more units of equipment as target equipment for recovery work, based on the productivity of the one or more units of subsequent-process equipment; and notifying of the identified target equipment.

A computer-implemented system for optimizing travel itineraries in real time includes a failover-capable API gateway, a search and recommendation engine, and a machine learning model trained on historical travel data. The system expands itinerary options using an Alternative Logic Service that incorporates flexible dates and nearby airports based on geographic metadata and pricing trends. Structured offer requests are transmitted to external APIs and evaluated using predictive scoring. A client-side graphical radius filter reduces request volume and latency. Updated itineraries are reranked dynamically and propagated across devices via a pub-sub notification system.

A digital healthcare ecosystem to transform patient care with real-time queue management, including: an appointment and laboratory test booking module configured to allow patients to easily book and schedule doctor consultations and diagnostic tests; a healthcare provider module configured to manage appointments, patient records, billing, internal laboratory and pharmacy integration, and operational analytics, with the healthcare provider module configured to manage dashboard features for physicians, hospital administrators, and laboratory technicians to monitor and update patient status; a real-time queue management module coupled to the healthcare provider module and the appointment and laboratory test booking module, wherein the real-time queue management module is configured to assign a digital token number to patients upon booking once accepted by the healthcare provider module, wherein the real-time queue management module is configured to update the queue position of patients using time-stamped data; a patient interface configured to allow patients to view real-time queue updates, book appointments, and access lab reports using the digital token number; a notification system configured to send notifications to patients and physicians regarding appointment reminders, queue progress, and follow-up instructions; a cloud-based server configured to securely store patient data and enable seamless communication between the patient interface and the healthcare provider module; a display unit configured to show estimated waiting times and notify patients when it is their turn; and a dynamic scheduling module configured to take into account physician availability, patient preferences, and historical data to minimize waiting times and avoid overbooking.

Systems and methods are disclosed for advising a user when an energy storage device in a computing system needs charging. State of charge data of the energy storage device can be measured and stored at regular intervals. The historic state of charge data can be queried over a plurality of intervals and a state of charge curve generated that is representative of a user's charging habits over time. The state of charge curve can be used to generate a rate of charge histogram and an acceleration of charge histogram. These can be used to predict when a user will charge next, and whether the energy storage device will have an amount of energy below a predetermined threshold amount before the next predicted charging time. A first device can determine when a second device typically charges and whether the energy storage device in the second device will have an amount of energy below the predetermined threshold amount before the next predicted charge time for the second device. The first device can generate an advice to charge notification to the user on either, or both, devices.

An aircraft notification system, the aircraft notification system having a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive aircraft angle data from a blended wing body aircraft (BWB) having a main body and a wing with no clear demarcation between the wings and the main body along a leading edge of the aircraft, determine an aircraft orientation as a function of the aircraft angle data, wherein the aircraft orientation comprises at least a pitch angle of the BWB while the BWB is in contact with a ground surface, transmit the aircraft orientation to an aircraft display system and visually display the aircraft orientation through the aircraft display system.