Abstract:
Devices, systems, and methods are disclosed to offload the usage of a cellular network by intelligent selection of broadband network connections such as Wi-Fi access points. A Wi-Fi transceiver on a mobile device is activated when certain conditions are met, such as a time, location, recognition of a radiofrequency (RF) environment, etc. The conditions are correlated with a database of known locations in which a one or more Wi-Fi access points are determined to exist. The Wi-Fi transceiver on the mobile device is activated and commanded to connect to a particular Wi-Fi access point. Dynamic intelligence ensures that the appropriate connection method is used, and minimizes handovers to networks or access points that are unreliable or that are predicted to become inaccessible to the mobile device.
Abstract:
The disclosed subject matter provides for received signal strength indicator (RSSI) snapshot analysis. RSSI snapshot analysis can be independent of determining location/map information. An RSSI snapshot can be analyzed in view of historic RSSI information to determine a probability that a local wireless resource correlated with the historical RSSI information is instantly available. Machine learning can be employed to train an inference component to facilitate in determining the probability. In an aspect, the state of a wireless radio can be controlled based on the probability and this can reduce the energy consumption of the user equipment by facilitating intelligent enablement of a wireless radio.
Abstract:
The disclosed subject matter provides for sharing timed fingerprint location information. In an aspect, timed fingerprint location information can be associated with a location of a user equipment. This timed fingerprint location information can be shared with other devices. As such, with proper analysis, these other devices can employ the shared timed fingerprint location information to determine their location. In an aspect, the other devices can determine that they are located at the same location as the user equipment. However, a level of error can be inherent in the location determined from shared timed fingerprint location information. In some embodiments, this error can be compensated for.
Abstract:
The disclosed subject matter provides for sharing timed fingerprint location information. In an aspect, timed fingerprint location information can be associated with a location of a user equipment. This timed fingerprint location information can be shared with other devices. As such, with proper analysis, these other devices can employ the shared timed fingerprint location information to determine their location. In an aspect, the other devices can determine that they are located at the same location as the user equipment. However, a level of error can be inherent in the location determined from shared timed fingerprint location information. In some embodiments, this error can be compensated for.
Abstract:
The disclosed subject matter provides for received signal strength indicator (RSSI) snapshot analysis. RSSI snapshot analysis can be independent of determining location/map information. An RSSI snapshot can be analyzed in view of historic RSSI information to determine a probability that a local wireless resource correlated with the historical RSSI information is instantly available. Machine learning can be employed to train an inference component to facilitate in determining the probability. In an aspect, the state of a wireless radio can be controlled based on the probability and this can reduce the energy consumption of the user equipment by facilitating intelligent enablement of a wireless radio.
Abstract:
The disclosed subject matter provides for sharing a network access credential based on location information. Location information can include timed fingerprint location information. In an aspect, location information can be associated with a location of user equipment. This location information can be correlated with network access credentials. Location information can be used to access a relevant network access credential. The relevant network access credential can be shared with other devices. In an embodiment, sharing a network access credential can be between mobile devices. In another embodiment, sharing a network access credential can be between a remote computing device and a mobile device. Sharing a credential can allow for access to a network without having to generate or input new credentials.
Abstract:
The disclosed subject matter provides for sharing a network access credential based on location information. Location information can include timed fingerprint location information. In an aspect, location information can be associated with a location of user equipment. This location information can be correlated with network access credentials. Location information can be used to access a relevant network access credential. The relevant network access credential can be shared with other devices. In an embodiment, sharing a network access credential can be between mobile devices. In another embodiment, sharing a network access credential can be between a remote computing device and a mobile device. Sharing a credential can allow for access to a network without having to generate or input new credentials.
Abstract:
System(s), device(s), method(s), and user interfaces are provided to enable a subscriber device to report network operation conditions, such as network performance incidents, to receive feedback from the network related to the incident and available or possibly available solutions, and to produce network intelligence suitable for network planning and network performance enhancement. Reporting of network performance incidents can be characterized by location and time of occurrence, wherein these intelligence is provided by the user device. Feedback provided by the network is based on the network performance data received as part of reporting an incident. The reporting described herein enables a network operator to generate network planning intelligence based on actual network performance as experienced at the subscriber level.
Abstract:
Aspects relate to automatically providing updated route and predicted travel time to allow a user to travel a shortest route between a first point and a second point. A route can be planned based on a multitude of route segments, wherein historical data related to speed is known for each of the route segments. Further, the historical data is categorized based on temporal aspects, such as time of day, day of week, as well as other aspects, such as known events that can have an influence on the speed at which each route segment can be traveled. As the user moves along the route, the planned route, as well as an anticipated travel time, are almost continually updated to provide the most up-to-date and accurate data.
Abstract:
The present disclosure provides devices, systems, and methods to utilize relative timing offset information reported by one or more mobile devices. When coupled with AGPS information reported by one or more mobile devices, the offset information is be used to calibrate calculations and subsequently to locate all 3G mobiles with GPS-like accuracy, whether or not a GPS receiver is available on said mobile device being located. A determination of a propagation delay between one or more cell sites and a mobile device is reported to a network and used to calibrate unknown information such as a timing offset, to improve the accuracy of a detected location. The relative timing offset can be applied to determine a location for all other mobile devices within the area served by the known base station. The present disclosure utilizes this method in conjunction with information crowd-sourced from a plurality of mobile devices.