Predictive Location Tracking for Wireless Notification Delivery
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Solution Overview
Problem
Conventional wireless systems face challenges in delivering notifications to mobile communication devices when they are not connected to the network, as the location of the device is unknown, leading to inefficiencies in resource usage and notification delivery.
Innovation Solution
A communication management resource predicts the current location of a mobile communication device based on its prior location history and time of notification, initiating wireless transmissions from likely locations to ensure timely delivery of notifications, even when the device is in an idle mode or not connected to the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the mobile communication device is not connected to the network (idle mode), then the device cannot receive notifications, but the network does not know the device location leading to inefficient resource usage
Solution Approach 1:
The system performs preliminary location tracking when the device is connected, storing location history and movement patterns in advance. When the device goes idle, this pre-collected data is used to predict current location without requiring active connection, enabling notification delivery while avoiding continuous resource consumption.
Solution Approach 2:
The system creates a virtual representation of the device's location behavior through location history and movement patterns. This copy of location information allows the network to predict and reach the device even when not directly connected, decoupling notification delivery from active connection status.
2Reliability
If the network tracks the device location continuously, then notification delivery is reliable, but resource consumption increases
Solution Approach 1:
Instead of continuous tracking, the system uses periodic location updates that occur when the device connects to the network. Location history is updated at these periodic intervals, and movement patterns are analyzed based on this periodic data, reducing resource consumption while maintaining sufficient location accuracy for prediction.
Solution Approach 2:
The system uses the device's own movement patterns and location history to predict its current location. The device effectively serves its own location tracking needs by providing historical data that the network analyzes to predict future positions, eliminating the need for continuous active tracking resources.
3Reliability
If the network attempts to notify the device at random locations, then the device might be reached, but notification delivery efficiency decreases
Solution Approach 1:
The system uses historical location data and movement patterns as feedback to continuously improve location prediction accuracy. By analyzing past device behavior, the system refines its prediction algorithms to more accurately forecast current device location, reducing the time and attempts needed to deliver notifications.
Solution Approach 2:
The system pre-calculates predicted locations based on historical patterns before notification is needed. When a notification arrives, the system can immediately query pre-computed location predictions rather than searching randomly, significantly reducing notification delivery time while maintaining high reliability.
Data Source
AI summary
A communication management resource receives notification of an incoming communication (such as from a calling party) directed to a mobile communication device in a wireless network environment. In response to receiving the notification, the communication management resource predicts a current location of the mobile communication device based on a prior history of tracking the mobile communication device and a time of receiving the call alert. The communication management resource initiates wireless transmission of the call alert in a wireless signal from a first wireless base station at the predicted current location.