CPC Class H04W

Traditional home-automation systems utilize a single hub for controlling secondary devices within a home. The techniques described herein, meanwhile, utilize multiple hubs within the environment and/or located remotely from the environment. For instance, an environment may include multiple electronic devices, each configured to control one or more secondary devices within the environment. In addition, a remote service may be configured to control one or more secondary devices within the environment. As such, each controlling device stores and executes an instance of a control engine, rather than relying on a single instance of a control engine located at a single controlling hub.

The system generally includes a crosspoint switch in the local data collection system having multiple inputs and multiple outputs including a first input connected to the first sensor and a second input connected to the second sensor. The multiple outputs include a first and second output configured to be switchable between a condition in which the first output is configured to switch between delivery of the first sensor signal and the second sensor signal and a condition in which there is simultaneous delivery of the first sensor signal from the first output and the second sensor signal from the second output. Each of multiple inputs is configured to be individually assigned to any of the multiple outputs. Unassigned outputs are configured to be switched off producing a high-impedance state. The local data collection system is configured to manage data collection bands that define a specific frequency band and at least one of a group of spectral peaks, a true-peak level, a crest factor derived from a time waveform. The local data collection system is configured to create data acquisition routes based on hierarchical templates that each include the data collection bands related to machines associated with the data acquisition routes.

Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: obtaining ride preference information associated with a user, identifying a current vehicle pose, determining a motion plan for the vehicle along a route based at least in part on the ride preference information, the current vehicle pose, and vehicle kinematic and dynamic constraints associated with the route, and operating one or more actuators onboard the vehicle in accordance with the motion plan. The user-specific ride preference information influences a rate of vehicle movement resulting from the motion plan.

A computer-implemented method of using telematics data associated with an originating vehicle at a destination vehicle is provided. The method includes receiving telematics data associated with the originating vehicle by (1) a mobile device, or (2) a smart vehicle controller associated with a driver, and analyzing the telematics data to determine that a travel event exists. If the travel event exists, the method may determine if the travel event presents an issue or problem for the vehicle (or driver) by determining that a GPS location of the travel event is located along the current travel route of the vehicle and, if so, automatically taking a preventive or corrective action that alleviates a negative impact of the travel event on the driver or vehicle to facilitate safer or more efficient vehicle travel. Insurance discounts may be provided based upon the risk mitigation or prevention functionality, or usage thereof.

A method is provided, performed by a wearable computing device comprising at least one bio-signal measuring sensor, the at least one bio-signal measuring sensor including at least one brainwave sensor, comprising: acquiring at least one bio-signal measurement from a user using the at least one bio-signal measuring sensor, the at least one bio-signal measurement comprising at least one brainwave state measurement; processing the at least one bio-signal measurement, including at least the at least one brainwave state measurement, in accordance with a profile associated with the user; determining a correspondence between the processed at least one bio-signal measurement and at least one predefined device control action; and in accordance with the correspondence determination, controlling operation of at least one component of the wearable computing device, such as modifying content displayed on a display of the wearable computing device. Various types of bio-signals, including brainwaves, may be measured and used to control the device in various ways.