Abstract:
More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.
Abstract:
Concepts and technologies are disclosed herein for suspending voice guidance during route navigation. A processor that executes a navigation system interface application can detect a deviation from a route between an origin and a destination. The processor can obtain contextual data including a geographic location and a vector. The processor can set a first value of a point-of-interest parameter that indicates whether the geographic location and the vector imply a visit to an expected stop, a second value of a road-type parameter that indicates a type of a current road segment associated with the geographic location, and a third value of a route-distance parameter based on a distance between the geographic location and a nearest point along the route. The processor can determine if voice guidance should be suspended based on the first value, the second value, and the third value.
Abstract:
Methods, computer-readable media and apparatuses for predicting an amount of network infrastructure needed for a new neighborhood are disclosed. A processor generates a plurality of different user profiles based upon demographic data of existing customers, historical utilization data and historical usage data, determines a demographic of a new neighborhood, correlates one of the plurality of different user profiles to the new neighborhood based upon the demographic of the new neighborhood and predicts the amount of network infrastructure to be deployed in the new neighborhood based upon the one of the plurality of different user profiles that is correlated to the demographic of the new neighborhood.
Abstract:
Determining referenced based location information for a wireless radio network is described. Referenced based location information can include determining location reference information and corresponding location offset information based on location information. In an aspect, location information can be timed fingerprint location information. Location offset information can be communicated in a wireless network at a lower operational cost than the associated location information. As such, use of referenced based location information for a wireless network can reduce bandwidth consumption as compared to location information communicated at similar intervals. This is particularly true in large wireless networks. Moreover, the use of referenced based location information for determining timed fingerprint location information can be highly attractive in light of timed fingerprint location information facilitating location information for many non-GPS enabled devices and being associated with significant increases in the frequency and density of location event requests.
Abstract:
Determining referenced based location information for a wireless radio network is described. Referenced based location information can include determining location reference information and corresponding location offset information based on location information. In an aspect, location information can be timed fingerprint location information. Location offset information can be communicated in a wireless network at a lower operational cost than the associated location information. As such, use of referenced based location information for a wireless network can reduce bandwidth consumption as compared to location information communicated at similar intervals. This is particularly true in large wireless networks. Moreover, the use of referenced based location information for determining timed fingerprint location information can be highly attractive in light of timed fingerprint location information facilitating location information for many non-GPS enabled devices and being associated with significant increases in the frequency and density of location event requests.
Abstract:
Aspects of the subject disclosure may include, for example, training a machine learning model on training data, generating, by the machine learning model, a plurality of prediction data records which each has an associated probability, and promoting prediction data records of the plurality of prediction data records having an associated probability exceeding a threshold. The subject disclosure may further include combining the promoted prediction data records with the training data to form new training data, retraining the machine learning model on the new training data and generating, by the machine learning model, new prediction data records. The subject disclosure may further include identifying a real-time condition based on the new prediction data records, the real-time condition being one that requires prompt attention, and resolving the real-time condition. Other embodiments are disclosed.
Abstract:
A sorter receives a list of elements to be sorted. An element of the list is supplied to a selected one of a plurality of processing units to be processed. The selected one of the processing units sends the element to one of a plurality of list element cells, which rank orders the elements among other elements in the same list element storage as well as storing the position of each element from the original list. Each of the plurality of list element cells processes and stores a different range of element values. The element being processed is stored in sorted order in the list element cell that has an element value range that encompasses the value of the element of the list.
Abstract:
Concepts and technologies are disclosed herein for providing and/or interacting with a profile verification service. A processor executing a profile verification service can receive a request to verify a user profile associated with a user of a social networking application. The processor can identify a computing device associated with the user profile, obtain location data that relates to the user profile and the computing device, and identify an activity associated with the computing device based upon the location data. The processor can determine if the user profile is accurate based upon the activity identified. If a determination is made that the user profile is accurate, the processor can verify the user profile. If a determination is made that the user profile is not accurate, the processor can update the user profile.
Abstract:
Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to supplement network coverage with a fleet of autonomous drones are disclosed. Example methods disclosed herein include configuring a first drone with information specifying a size and a target location associated with the coverage area. Disclosed example methods also include, when the first drone reaches the target location, monitoring for communication signals to determine whether a first coverage zone provided by the first drone and a second coverage zone provided by a second drone in a fleet of drones overlap. Disclosed example methods further include autonomously adjusting a position of the first drone to maintain overlapping of the first coverage zone provided by the first drone with the coverage area, but to reduce an amount of overlap of the first coverage zone with the second coverage zone.
Abstract:
Concepts and technologies are disclosed herein for providing and/or interacting with a profile verification service. A processor executing a profile verification service can receive a request to verify a user profile associated with a user of a social networking application. The processor can identify a computing device associated with the user profile, obtain location data that relates to the user profile and the computing device, and identify an activity associated with the computing device based upon the location data. The processor can determine if the user profile is accurate based upon the activity identified. If a determination is made that the user profile is accurate, the processor can verify the user profile. If a determination is made that the user profile is not accurate, the processor can update the user profile.