Abstract: A handheld vacuum cleaner includes a dirt separator. The dirt separator includes a chamber having an inlet through which dirt-laden fluid enters and an outlet through which cleansed fluid exits the chamber. A disc located at the outlet rotates about a rotational axis and comprises holes through which the cleansed fluid passes.

Abstract: A method of altering an operating state of a transportation system may include: receiving social data from a plurality of social data sources about at least one occupant of a vehicle of the transportation system; analyzing, at a first neural network, the social data and associating the social data with a route plan for the vehicle occupied by the at least one occupant; predicting, by the first neural network, an effect on a satisfaction of the at least one occupant based on the route plan of the vehicle through an analysis of the social data; and altering, by the first neural network, a route plan of the transportation system responsive to the predicted effect.

Abstract: A system may receive social data from a plurality of social data sources. A system may process the social data using semantic analysis to detect keywords in the social data indicative of a group transportation need. A system may identify a plurality of individuals who share a group transportation need. A system may predict the group transportation need using a neural network trained to predict transportation needs based on the detected keywords. A system may provide a transportation recommendation based on the prediction.

Abstract: A method of executing a charging plan for at least one vehicle in a transportation system includes: receiving, at a charging infrastructure control system, operational state and energy consumption information for a plurality of network-enabled vehicles; predicting a geolocation of one or more vehicles of the plurality of network-enabled vehicles in a geographic region; allocating the one or more vehicles of the plurality of network-enabled vehicles to charging infrastructure in the geographic region; and optimizing, at an artificial intelligence system, a parameter of the charging plan based on the prediction of the geolocation of the one or more vehicles in the geographic region.

Abstract: A method of operating a vehicle in a transportation system includes: receiving data collected for each of a set of users based on interactions of the set of users with a user interface of the vehicle including at least one of a vehicle data system, a vision system, and a connected system; performing robotic process automation on the interactions; learning changes in driving style using an artificial intelligence system based on the robotic process automation; and undertaking an action within the vehicle on behalf of the user based on the learned changes in driving style.

Abstract: A system for improving a state of a rider in a vehicle includes at least one Internet-of-Things (IoT) device and an artificial intelligence system. The at least one IoT device in disposed in the environment of the vehicle, the at least one IoT device to sense and output data based on at least one of: a state of the rider, a state of the vehicle environment, or a state of the vehicle. The artificial intelligence system for processing the data output by the at least one IoT device to determine a determined state of the vehicle and to improve the at least one operating parameter of the vehicle to improve the state of the rider based on the determined state of the vehicle.

Abstract: A transportation system to optimize an operating parameter of a vehicle based on a physiological state of an occupant of the vehicle. The transportation system includes a sensor to sense a physiological condition of the occupant and to output data based on the sensed physiological condition. The sensor includes a movement sensor to detect physical actions of the vehicle occupant. The transportation system further includes a real-time control system to receive and process the data to determine an emotional state of the occupant based on the detected physical actions and to optimize, for achieving a favorable emotional state of the occupant, at least one operating parameter of the vehicle in response to the detected emotional state of the occupant.

Abstract: A system may include a digital twin management system to one of create, maintain, or render a digital twin based on received sensor data from one or more sensor systems associated with a vehicle. A system may include a digital twin simulation system to execute vehicle performance simulations using the digital twin by adjusting one or more vehicle performance parameters of the digital twin, and collect simulation outcome data resulting from the simulation. A system may include a cognitive process system to train machine learned models using vehicle performance simulation outcome data and makes predictions for providing decision support related to a simulated performance parameter to minimize a cost criterion associated with operating the vehicle.

Abstract: A system may include an artificial intelligence system for processing data output by at least one Internet-of-Things device associated with the vehicle, wherein the at least one Internet-of-Things device is configured to sense and output data based on at least one of: a state of the rider, a state of the vehicle environment, or a state of the vehicle, and wherein the artificial intelligence system is configured to determine a determined state of the vehicle and to adjust the at least one operating parameter of the vehicle to improve the state of the rider based on the determined state of the vehicle.

Abstract: A method of optimizing a state of a rider of a vehicle. The method includes: receiving data from a wearable sensor worn by the rider of the vehicle indicative of an emotional state of the rider; comparing the data received from the wearable sensor to stored wearable sensor data in which quantitative patterns present in the stored sensor data are labelled as emotional states; determining a pattern of an emotional state based on the data received from the wearable sensor and the comparison to the stored wearable sensor data; detecting a change in emotional state of the rider based on a detected change in the data received from the wearable sensor indicative of a change in the emotional state of the rider; and adjusting an operational parameter of the vehicle in real time in response to the detected change in the emotional state of the rider.

Abstract: A system may collect human operator interactions with a vehicle control system interface operatively connected to a vehicle, and may collect vehicle response and operating conditions associated at least contemporaneously with the human operator interaction. Environmental information is collected contemporaneously with the human operator interaction.

Abstract: A system for transportation, includes at least one vehicle and an artificial intelligence (AI) system in communication with the at least one vehicle. The AI system is operative on at least one processor having access to a non-transitory storage medium that stores computer executable instructions to be executed by the at least one processor. The AI system includes a first neural network of a hybrid neural network to classify social media data sourced from a plurality of social media sources as affecting a transportation system, a second neural network of the hybrid neural network to predict at least one vehicle-operating objective of the transportation system based on the classified social media data, and a third neural network of the hybrid neural network to optimize a state of the at least one vehicle in the transportation system to achieve the at least one vehicle-operating objective of the transportation system.

Abstract: Improving satisfaction of a rider of a vehicle includes: receiving biometric data from a sensor of a biometric parameter of the rider indicative of a physiological condition of the rider; determining, at a first neural network, a predicted emotional state of the rider based on the biometric data; in response to determining the predicted emotional state of the rider: determining a current operating state of the vehicle; determining, by a second neural network, a corrective operating state for the vehicle based on the predicted emotional state and the current operating state to improve the emotional state of the rider; outputting the set of corrective operating parameters to a vehicle controller; receiving second biometric data from the sensor after the vehicle is operating in the corrective operating state; and updating the second neural network based on the predicted emotional state, the corrective operating state, and the second biometric data.

Abstract: Vehicles and methods described herein include a vehicle that operates with a rider according to an operating parameter. The vehicle includes: a physiological monitoring sensor configured to measure a physiological parameter of the rider; an experience hybrid neural network trained on outcomes related to a rider in-vehicle experience associated with the physiological parameter to determine an emotional state of the rider; an augmented reality system configured to present augmented reality content to the rider of the vehicle based, at least in part, on the operating parameter; and an optimization hybrid neural network that identifies a variation in the operating parameter to change the emotional state of the rider and that generates a command to vary the operating parameter and the augmented reality content according to the variation.

Abstract: A system for data collection and loan activities is disclosed. The system may include a data collection circuit to receive data relating to a status of a loan and a set of items of collateral acting as security for the loan. The system may further include a blockchain service circuit to maintain a secure historical ledger of events related to the loan, and to interpret a plurality of access control features corresponding to parties associated with the loan. The system may further include a loan evaluation circuit to determine a loan status based on the received data, a smart contract circuit to create a smart lending contract for the loan, and an automated agent circuit to perform a loan action based on the loan status, wherein the blockchain service circuit is further structured to update the secure historical ledger of events with the loan action.

Abstract: Systems, methods and apparatus relating to asset-class based tokens are described. An example apparatus may include a tokenization controller to implement a tokenization user interface where the tokenization controller includes a token definition circuit to interpret a token description in response to user operations. The example apparatus may further include an asset definition circuit to interpret an asset-class description in response to user operations and an asset backing circuit to interpret a token link description including a token performance representation corresponding to a beneficial characteristic of at least one asset of the asset-class description, and to generate at least one asset-class linked token in response to the token link description and the asset-class description. The example apparatus may further include a token deployment circuit to expose the at least one asset-class linked token to a token marketplace system.

Abstract: A transportation system, that optimizes at least one operating parameter of a vehicle based on a physiological state of an occupant of the vehicle, includes a sensor that senses a physiological condition of the occupant and that outputs data based on the sensed physiological condition. The transportation system further includes an artificial intelligence system that receives and processes the data to determine an emotional state of the occupant, and optimizes, for achieving a favorable emotional state of the occupant, the at least one operating parameter of the vehicle in response to detecting the emotional state of the occupant.

Abstract: Data processing systems disclosed herein may promote satisfaction of a rider of a vehicle and include a machine learning model and a vehicle control system. The machine learning model determines a measure of an emotional state of the rider based on data received from a sensor associated with the rider, where the data is indicative of a physiological condition of the rider. The vehicle control system: determines a target value of an operating parameter of the vehicle based on a correlation between the emotional state of the rider and the target value of the operating parameter; and adjusts the operating parameter of the vehicle based on the target value of the operating parameter.

Abstract: A transportation system, that optimizes at least one operating parameter of a vehicle based on a physiological state of an occupant of the vehicle, includes a sensor that senses a physiological condition of the occupant and that outputs data based on the sensed physiological condition. The transportation system further includes an artificial intelligence system that receives and processes the data to determine an emotional state of the occupant, and optimizes, for achieving a favorable emotional state of the occupant, the at least one operating parameter of the vehicle in response to detecting the emotional state of the occupant.

Abstract: A vehicle includes a display disposed to facilitate presenting an augmentation of content in an environment of a rider of the vehicle; a circuit for registering at least one of location and orientation of the vehicle; a machine learning circuit that determines at least one augmentation parameter by processing at least one input relating to at least one of the rider and the vehicle; and a reality augmentation circuit that, responsive to the at least one of the location or the orientation of the vehicle, generates an augmentation element for presenting in the display, the generating based at least in part on the at least one augmentation parameter.