The described technology is generally directed towards proactive content placement for low latency mobile access. Digital content requested by a mobile device can be sent to network nodes proactively, so that the network nodes have the digital content before it is requested by the mobile device. Mobile device travel predictions can be made to predict future locations of the mobile device. The future locations can be used to determine network nodes for proactive digital content delivery. The digital content for delivery to a network node can also be predicted based on current digital content in use at the mobile device and estimated arrival times of the mobile device into service areas of next network nodes.

A device and method for positioning personal mobility vehicle are disclosed. The positioning method is implemented by a computer and comprises receiving messages from a plurality of auxiliary road side units, obtaining distances between a Personal Mobility (PM) vehicle and the plurality of auxiliary road side units based on the messages, estimating a candidate position of the PM vehicle based on the distances between the PM vehicle and the plurality of auxiliary road side units, receiving correction data from a reference road side unit, correcting the candidate position based on the correction data, and determining the corrected candidate position as a final position of the PM vehicle.

Conventionally, Received Signal Strength Indicator (RSSI)-based solutions have been extensively devised in the domains of indoor localization and context-aware applications. These solutions are primarily based on a path-loss attenuation model, with customizations on RSSI processing and are usually regression-based. Further, existing solutions for distance and proximity estimation incorporate data features derived only from the RSSI values themselves with additional features like frequency of occurrence of certain RSSI values thus are less accurate. Present disclosure provides systems and methods that implement a classification model that uses RSSI as well as temporal features derived from the received data packets. The model uses data from multiple devices in different environments for training and can execute proximity decisions on the device itself. The method of the present disclosure monitoring proximity between a plurality of devices implements/uses an effective protocol for decision aggregation to suppress false positive proximity events generated and further stabilizes device's response.

A system and method for in-person proximity matching that allows a plurality of user electronic devices to identify and match with one another based on a compatibility profile. The matching is done using a near-field communication protocol, such as Bluetooth or Wi-Fi. The invention allows matching of users when they are within the near proximity, which is defined as approximately 1000 meters.

A method includes estimating distances between a user device and an access point based on a series of FTM ranging bursts exchanged between the user device and the access point. The method also includes calculating a variance of the estimated distances and in response to determining that the variance exceeds a threshold, instructing the user device to perform an action that reduces the variance. Other embodiments include a device that performs this method.

Computer-implemented methods, computer-readable storage media storing instructions and computer systems for labeling significant locations based on contextual data can be implemented to perform operations that include determining a location of a computing device, and determining a label for the determined location based on contextual data associated with the significant location. The location can be a significant location that has meaning to a user of the device.

A method for perception-sharing between similarly-situated vehicles that are traveling on a portion of a roadway that is equipped with an intelligent vehicle highway system is described, and includes executing, in a multi-access edge computing cluster in communication with a roadside unit disposed to monitor a roadway, an application-layer routine. The application-layer routine includes collecting real-time data associated with a plurality of objects from each of the similarly-situated vehicles, predicting motion of each of the plurality of objects based upon the real-time data, object-matching the motion of each of the plurality of objects, and executing fusion of the plurality of objects based upon the object-matching of the motion of each of the plurality of objects. Locations of the similarly-situated vehicles traveling on the roadway are identified based upon the fusion of the plurality of objects. The locations are communicated to one of the similarly-situated vehicles.

A real-time application-based cellular system with real-time GPS positioning to notify civilian drivers of the proximity of emergency services vehicles in sufficient time to allow appropriate response. Civilian users receive alerts and information on their personal computing devices, including, but not limited to, tablets and smart phones. No addition or special hardware is required. Only drivers in a moving vehicle with a certain proximity are directly and selectively notified. The system also is able to send other additional customized warning signals to citizens in threatening situations in a non-vehicular context.

Methods, systems, and devices that support techniques for a smart monitoring system are described. A system may monitor a physical environment using a camera-enabled device operating in a first mode of a set of modes. The system may determine one or more parameters based on the monitoring. The parameters may include an identity of an entity, a behavior of the entity, or a setting of the security and automation system, or any combination thereof. The system may perform an operation based on the one or more parameters. The techniques described herein may deter an intruder from an intended action (e.g., theft, property damage, etc.) and/or provide lighting to a user of the security and automation system, among other benefits.

Embodiments of a STA configured for proximity detection by multiple WLAN link tracking are disclosed herein. In some embodiments, the STA performs WLAN sensing using two or more WLAN links with one or more other STAs to track a channel state of each link and performs motion detection based on the tracked channel state of each WLAN link to detect motion in any of the WLAN links. If motion is detected in at least some of the WLAN links, the STA may perform proximity detection to indicate proximity by combining results of the WLAN sensing for each link to determine whether the motion is proximate to the STA or proximate to one of the other STAs.