Abstract: A system and method extracting insights from sensed data are provided. The method includes receiving at least one data packet from at least one IoT tag, extracting at least one parameter from the at least one received data packet, where the parameter is a measure of the at least one IoT tag, identifying patterns from the at least one extracted parameter, and determining an insight based on the identified patterns.

Abstract: A method and system for determining locations of internet of things (IoT) tags are provided. The method includes receiving, during a predefined time window, packets from a plurality of gateways, wherein a received packets include at least sensing signals transmitted from the IoT tags; determining an affinity among the IoT tags based on the sensing signals; determining locations of IoT tags based on the determined affinity and the sensing signals, wherein a location of an IoT tag is a probability that an IoT tag is located in proximity to a gateway; and reporting the determined locations to a user terminal.

Abstract: A system and method for detecting material type using low-energy sensing are disclosed. The method includes receiving frequency words from a tag attached to a container containing material, wherein the tag provides a low-energy sensing configured to transmit the frequency words; extracting at least a first data feature from the received frequency words, wherein the first data feature changes in response to a type of material in the container; classifying the extracted data feature to label a type of the material in the container; and sending a notification indicating the type of material in the container.

Abstract: A system and method for determining and monitoring occupancy level of items placed on a surface are provided. The system comprises receiving frequency words from tags placed on the surface, wherein each tag is configured to transmit a plurality of frequency words; extracting at least one data feature from the plurality of frequency words, wherein each data feature changes in response to an item placed in a proximity to a respective tag; determining, based on the extracted at least one data feature from a group of tags placed on the surface and based on at least one baseline, the occupancy level of items placed on the surface; and reporting the determined occupancy level of items.

Abstract: A system and method for detecting material type using low-energy sensing are disclosed. The method includes receiving frequency words from a tag attached to a container containing material, wherein the tag provides a low-energy sensing configured to transmit the frequency words; extracting at least a first data feature from the received frequency words, wherein the first data feature changes in response to a type of material in the container; classifying the extracted data feature to label a type of the material in the container; and sending a notification indicating the type of material in the container.

Abstract: A system and method for tracing vaccine vials are provided. The method includes receiving, from a gateway of a plurality of gateways, frequency words from tags attached to vaccine vials, wherein each tag is configured to transmit a plurality of frequency words; extracting at least one data feature from the plurality of frequency words, wherein each data feature changes in response to a change in a state of a vaccine vial; classifying the extracted data feature based on a machine learning model trained with respect to a location of the gateway, wherein the classifier is trained to label a trace parameter indicative of a state of a vaccine vial; and sending a semantic event indicating a value of the trace parameter.

Abstract: A system and method extracting insights from sensed data are provided. The method includes receiving at least one data packet from at least one IoT tag, extracting at least one parameter from the at least one received data packet, where the parameter is a measure of the at least one IoT tag, identifying patterns from the at least one extracted parameter, and determining an insight based on the identified patterns.

Abstract: Systems and method are provided for generating an integrated interface in a vehicle. In one embodiment, a method includes: receiving data associated with an environment of the vehicle; encoding the environment data into a plurality of layers; extracting data from the plurality of layers into a point cloud; projecting the point cloud onto a meta-template defining a basic element and manipulable features of the basic element; and generating display data based on the projecting.

Abstract: A system and method for predicting whether a driver of a host vehicle or a remote vehicle intends to make a left or right turn or travel straight through an intersection before the host vehicle or remote vehicle reaches the intersection that relies on a probability model that employs a dynamic Bayesian network. The method includes obtaining a plurality of environmental cues that identify external parameters at or around the intersection, where the environmental cues include position and velocity of the remote vehicle, and obtaining a plurality of host vehicle cues that define operation of the host vehicle. The method then predicts the turning intent of the host vehicle and/or remote vehicle at the intersection using the model based on both the external cues and the vehicle cues using the model. The model can use learned information about previous driver turns at the intersection.

Abstract: Systems and method are provided for generating an integrated interface in a vehicle. In one embodiment, a method includes: receiving data associated with an environment of the vehicle; encoding the environment data into a plurality of layers; extracting data from the plurality of layers into a point cloud; projecting the point cloud onto a meta-template defining a basic element and manipulable features of the basic element; and generating display data based on the projecting.

Abstract: A vehicle braking system integrates information regarding relative distance and velocity of both a preceding vehicle/obstacle and a proceeding vehicle in order to execute a braking scheme that optimizes the operating distance between the host vehicle to both the preceding vehicle/obstacle and the proceeding vehicle.

Abstract: Methods and systems are provided for notifying a user. In one embodiment, a method includes: receiving perception data from a sensing device; determining a presence of an agent based on the perception data. In response to the determined presence, determining at least one of a type and a location of the agent based on the perception data; and selectively communicating directly to the agent based on at least one of the type and the location of the agent.

Abstract: A product and method for autoactive brake light activation. A host vehicle may be provided with a brake pedal and braking lights. A perception system may be provided with the host vehicle. Whether the perception system provides information indicative of a triggering event may be evaluated. The braking lights may be activated if the perception system indicates a triggering event. Depression of the brake pedal may be monitored.

Abstract: A system and method for predicting whether a driver of a host vehicle or a remote vehicle intends to make a left or right turn or travel straight through an intersection before the host vehicle or remote vehicle reaches the intersection that relies on a probability model that employs a dynamic Bayesian network. The method includes obtaining a plurality of environmental cues that identify external parameters at or around the intersection, where the environmental cues include position and velocity of the remote vehicle, and obtaining a plurality of host vehicle cues that define operation of the host vehicle. The method then predicts the turning intent of the host vehicle and/or remote vehicle at the intersection using the model based on both the external cues and the vehicle cues using the model. The model can use learned information about previous driver turns at the intersection.

Abstract: The present disclosure relates to a continuous sensory output system and haptic apparatus, including a processor and a computer-readable where the processor to performs operations including receiving a sensor signal containing a sensor data set, applying the sensor data sets to a filter of a software package to form a projection data set, delivering the projection data set to a controller to form an action data set, and performing the action data set to an implementation section to perform the sensory output. Also, disclosed are methods including receiving a sensor signal containing a sensor data set, applying the sensor data sets to a filter of a software package to form a projection data set, delivering the projection data set to a controller to form an action data set, and performing the action data set to an implementation section to perform the sensory output.

Abstract: A system and method provided on an ego-vehicle for assessing potential threats in a vehicle collision avoidance system, and/or to plan safety-allowed vehicle trajectories for vehicle path planning. The method includes detecting objects in a predetermined vicinity around the ego-vehicle, and determining the relative velocity or other measure between each detected object and the ego-vehicle. The method defines a virtual dynamic safety shield around each detected object that has a shape, size and orientation that is determined by predetermined properties related to the current state of traffic around the ego-vehicle. The method also defines an action grid around the ego-vehicle. The method assesses the threat level of a potential collision between each detected object based on how the shield for that object and the action grid interact. The interaction between the shields and the grid induces actions aimed at aborting collisions and allows for trajectory planning.

Abstract: A system and method provided on an ego-vehicle for assessing potential threats in a vehicle collision avoidance system, and/or to plan safety-allowed vehicle trajectories for vehicle path planning. The method includes detecting objects in a predetermined vicinity around the ego-vehicle, and determining the relative velocity or other measure between each detected object and the ego-vehicle. The method defines a virtual dynamic safety shield around each detected object that has a shape, size and orientation that is determined by predetermined properties related to the current state of traffic around the ego-vehicle. The method also defines an action grid around the ego-vehicle. The method assesses the threat level of a potential collision between each detected object based on how the shield for that object and the action grid interact. The interaction between the shields and the grid induces actions aimed at aborting collisions and allows for trajectory planning.