Abstract: A computer-implemented method for optimizing a distributed database includes receiving, at an aggregator, one or more query logs comprising past queries received by the distributed database. The method includes generating, by the aggregator, a query prediction model based on the one or more query logs. The method includes predicting, by the aggregator, a future query using the query prediction model. The predicted future query is predicted to be received by an edge device. The method includes causing, by the aggregator, data for responding to the predicted future query to be transmitted to the edge device.

Abstract: An example monitoring system for data collection includes a data collector including a plurality of sensor. The system includes a data storage to store a collector route template for the plurality of sensors with a sensor collection routine defining how the plurality of sensors. The system includes a data acquisition and analysis circuit to receive detection signals and evaluate the detection values with respect to a rule, and further, based on the evaluation of the detection values with respect to the rule, to modify the sensor collection routine.

Abstract: A transportation system and method for managing rewards in the transportation system includes using a merchant interface to a cognitive system for managing the offering or fulfillment of a reward to a rider of a vehicle, where a merchant may specify parameters of the reward that can be earned by the rider as a result of performing an action while in the vehicle.

Abstract: Systems and methods for automatically soliciting the purchase of a first or second machine-related resource in a forward market, wherein the first resource and the second resource are distinct instances of the same type of resource, are described. A sample system may include a fleet of machines, each having a resource requirement comprising at least two of: a compute resource, a spectrum resource, or a network bandwidth resource. The system may include an circuits to aggregate data corresponding to the machine-related resources from at least a behavioral data source, to determine a substitution cost of a second resource; to determine a machine-related resource acquisition value; and to automatically solicit a purchase, in a forward market, of one of the first resource or the second resource in response to the determined substitution cost of the second resource.

Abstract: A system for transportation includes a vehicle configured to have a rider located therein or thereon, and an expert system to produce a recommendation for a configuration of the vehicle, wherein the recommendation includes at least one recommended parameter of configuration for the expert system that controls a parameter selected from the group consisting of a vehicle parameter, a rider experience parameter, and combinations thereof.

Abstract: A system for operating a vehicle based on a state of a rider includes an artificial intelligence system, a vehicle control system, and a feedback loop. The artificial intelligence system processes a sensory input from a wearable device in a vehicle to determine a state of a rider and optimizes an operating parameter of the vehicle to improve the state of the rider. The artificial intelligence system includes a neural net with a perceptron to mimic human senses to facilitate determining a state of a rider based on an extent to which at least one of the senses of the rider is stimulated. The vehicle control system adjusts vehicle operating parameters and the feedback loop indicates the change in the state of the rider, where the vehicle control system adjusts at least one of the plurality of vehicle operating parameters responsive to the indication of the change.

Abstract: Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.

Abstract: Systems and methods for monitoring a pump and a fan are disclosed. A monitoring system for a pump may include an industrial system including a pump, a data acquisition circuit to interpret a plurality of detection values corresponding to at least one of a plurality of input sensors operationally coupled to the pump and communicatively coupled to the data acquisition circuit. A monitoring system may further include a signal evaluation circuit including a timer circuit to generate at least one timing signal and a phase detection circuit structured to determine a relative phase difference between at least one of the detection values and at least one of the timing signals from the timer circuit. A response circuit may perform at least one operation in response to the relative phase difference.

Abstract: A system for transportation includes a vehicle, a rider occupying the vehicle, and a hybrid neural network. The hybrid neural network includes a first neural network to process a sensor input corresponding to the rider to determine an emotional state of the rider, and a second neural network to optimize at least one operating parameter of the vehicle to improve the emotional state of the rider.

Abstract: Systems and methods for balancing remote oil and gas equipment are disclosed. An example system may include analog sensors coupled to a piece of equipment and an analog switch with a plurality of analog sensor channels, wherein a first analog sensor channel comprises a trigger channel coupled to a first of the analog sensors, and wherein a second one of the analog sensor channels comprises an input channel coupled to a second sensors. The analog switch may digitally derive a relative phase between the trigger channel and the input channel, utilize a PLL band-pass tracking filter to determine at least one of slow-speed RPMs or phase information for the piece of equipment, and a response circuit that provides a process change command to remotely balance at least one component of the piece of equipment based on the RPMs or the phase information.

Abstract: A system for transportation includes a vehicle having at least one rider located in the vehicle and a data processing system for taking data from a plurality of social data sources. A hybrid neural network is connected to the data processing system. The system for transportation is to optimize satisfaction of the at least one rider based on processing the data from the plurality of social data sources with the hybrid neural network.

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 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 method of maintaining a favorable emotional state of a rider of a vehicle. The method includes: receiving emotional state indicative wearable sensor data of the rider in the vehicle; classifying, at a rider emotional state determining neural network, the emotional state indicative wearable sensor data and generating output data indicative of a classification of the rider emotional state as one of a favorable emotional state of the rider or an unfavorable emotional state of the rider; converting the output data from the rider emotional state determining neural network into a vehicle operational state datum; and adjusting a vehicle operating parameter in response to the vehicle operational state datum.

Abstract: Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.

Abstract: Transaction-enabled systems and methods for transaction execution with licensing smart wrappers are disclosed. An example system may include a smart contract wrapper configured to access a distributed ledger comprising a plurality of IP licensing terms for a plurality of IP assets comprising an aggregate stack of IP. The smart contract wrapper may be further configured to interpret an IP description value and an IP addition request and, in response to the request and IP description value, to add an IP asset to the aggregate stack of IP. A transaction execution circuit provides a transaction implementation command in response to at least one of a transaction geographic value or a transaction jurisdiction value.

Abstract: A transaction-enabling system is disclosed. The system may include a controller to interpret a behavioral data source and a resource utilization requirement for a task system having at least one of a compute task, a network task, or a core task. The controller may then operate a machine to forecast a forward market value for a resource in response to the resource utilization requirement and the behavioral data source. The controller then adjusts an operation of the task system or executes a transaction in response to the forecast of the forward market value for the resource.

Abstract: A method for processing a query for data stored in a distributed database includes receiving, at an edge device, the query for data stored in the distributed database from a query device. The method includes causing, by the edge device, the query to be stored on a dynamic ledger maintained by the distributed database. The method includes detecting, by the edge device, that summary data has been stored on the dynamic ledger. The method includes generating, by the edge device, an approximate response to the query based on the summary data stored on the dynamic ledger. The method includes transmitting, to the query device, the approximate response.

Abstract: Systems for vehicles are provided. A system includes a brain-computer interface, an artificial intelligence system, and a vehicle control system. The brain-computer interface is configured to interact with the vehicle, to interact with a rider of the vehicle, and to generate output data. The artificial intelligence system is configured to receive the output data and to analyze an emotional state of the rider based on the output data. The vehicle control system is configured to optimize at least one operating parameter of the vehicle based on the emotional state of the rider as analyzed by the artificial intelligence system.

Abstract: Systems, methods and apparatus for modifying a data collection trajectory for conveyors are described. An example system may include a data acquisition circuit to interpret a plurality of detection values, each corresponding to at least one of a plurality of input sensors communicatively coupled to the data acquisition circuit. The system may further include a data storage circuit to store specifications and anticipated state information for a plurality of conveyor types and an analysis circuit to analyze the plurality of detection values relative to specifications and anticipated state information to determine a conveyor performance parameter. A response circuit may initiate an action in response to the conveyor performance parameter.