Aspects of the subject technology relate to communication device used as a power meter. The communication device includes circuitry to determine values of several forces and a processor. The processor determines a combined force by combining the determined values of the forces. The processor further determines a value of a power based on the s combined force, a speed and a loss factor. The communication device is used by a user to measure the power. The power is generated by the user when engaged in an activity, and the forces affect a movement of the user.

According to an example aspect of the present invention, there is provided an apparatus comprising a memory configured to store first-type sensor data, at least one processing core configured to compile a message based at least partly on the first-type sensor data, to cause the message to be transmitted from the apparatus, to cause receiving in the apparatus of a machine readable instruction, and to derive an estimated activity type, using the machine readable instruction, based at least partly on sensor data

A method and computer program product are disclosed. The method includes tracking a distance travelled on a set of tires, determining a threshold, determining whether the distance travelled has exceeded the threshold, and notifying the user that the distance travelled has exceeded the threshold. The computer program product includes code to perform tracking a distance travelled on a set of tires, determining a threshold, determining whether the distance travelled has exceeded the threshold, and notifying the user that the distance travelled has exceeded the threshold.

A method and computer program product are disclosed. The method includes tracking a distance travelled on a set of tires, determining a threshold, determining whether the distance travelled has exceeded the threshold, and notifying the user that the distance travelled has exceeded the threshold. The computer program product includes code to perform tracking a distance travelled on a set of tires, determining a threshold, determining whether the distance travelled has exceeded the threshold, and notifying the user that the distance travelled has exceeded the threshold.

Techniques provided herein are directed toward virtually extending an updated set of output positions of a mobile device determined by a VIO by combining a current set of VIO output positions with one or more previous sets of VIO output positions in such a way that ensure all outputs positions among the various combined sets of output positions are consistent. The combined sets can be used for accurate position determination of the mobile device. Moreover, the position determination further may be based on GNSS measurements.

The present embodiments relate to systems and methods for using a blockchain to record information related to the lifecycle of a vehicle associated with a Vehicle Identification Number (VIN), or other vehicle identifier. For example, the VIN lifecycle process may be used to ensure the transferability of title, including when information relevant to transferability is not easily determinable, such as after a collision occurs. The systems and methods may include the reception of a mileage report corresponding to a vehicle and updating a blockchain to associate the vehicle with mileage information. The systems and methods described herein may allow for using a blockchain which gives the option for private information, and permissioned participants in the blockchain. In particular, the systems and methods allow for a distributed consensus amongst businesses, consumers, and authorities, as to the validity of information and transactions stored on the blockchain.

In accordance with one implementation of the present disclosure, a new approach for identifying a stepping event is proposed in indoor navigation. Generally speaking, a first signal fragment and a second signal fragment respectively within a first time window and a second time window in an acceleration signal stream are obtained, here the acceleration signal stream is collected from an acceleration sensor associated with a moving user, the first time window being shorter than the second time window. A first amplitude feature and a second amplitude feature are determined for the first and second time windows based on the first and second signal fragments, respectively. A stepping event of the user is identified based on a deviation between the first and second amplitude features. With the above implementation, the stepping event is identified in a more effective an accurate way, and thus accuracy of the indoor navigation is increased.

According to one aspect, uncertainty prediction based deep learning may include receiving, using a memory, a trained neural network policy π trained based on a first dataset in a first environment, implementing, via a controller, the trained neural network policy π in a second environment by receiving an input and generating an output y, calculating an uncertainty array U[T] for a time window T, wherein the uncertainty array is indicative of a level of uncertainty associated with an output sample distribution of the output across the time window T based on a temporal divergence, an entropy H, a variational ratio VR, and a standard deviation SD of the output y, and executing, via the controller and one or more systems, an action based on the uncertainty array U[T], such as discontinuing use of the trained neural network policy π.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating vehicle intent predictions using a neural network. One of the methods includes obtaining an input characterizing one or more vehicles in an environment; generating, from the input, features of each of the vehicles; and for each of the vehicles: processing the features of the vehicle using each of a plurality of intent-specific neural networks, wherein each of the intent-specific neural networks corresponds to a respective intent from a set of intents, and wherein each intent-specific neural network is configured to process the features of the vehicle to generate an output for the corresponding intent.

Provided herein is a system comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: obtaining a previous pose of a vehicle; acquiring one or more previous readings corresponding to one or more wheel encoders during the previous pose; acquiring one or more readings corresponding to one or more wheel encoders acquired after the previous pose; and adjusting the previous pose based on the one or more readings to obtain a current pose.