GPS Workforce Tracking with Privacy Masking and Idle Segmentation
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Solution Overview
Problem
Current systems fail to effectively monitor and analyze the movement and idle segments of mobile workforce members, such as service men and salespersons, who visit multiple customer locations, leading to difficulties in tracking time and productivity.
Innovation Solution
A system and method that utilizes GPS signal data from smartphones and tablets to classify movement and idle segments, transforming the data into time-on-site indicators, allowing for real-time tracking and visualization of the type, duration, and timing of each segment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If GPS signal data is collected and analyzed to identify movement and idle segments, then workforce visibility and productivity tracking are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent segments GPS trajectory data into distinct movement and idle segments based on velocity thresholds and time duration criteria. This segmentation transforms continuous GPS data into discrete, analyzable units that can be easily processed and visualized, resolving the contradiction by making complex data manageable through structured division.
Solution Approach 2:
The patent introduces an intermediary processing layer that converts raw GPS coordinates into meaningful movement segments. This intermediary layer filters and interprets GPS data, transforming it into actionable insights about workforce activity without requiring direct complex analysis of raw data, thus reducing system complexity while maintaining productivity tracking capability.
2Measurement precision
If detailed GPS tracking is implemented to monitor task persons, then measurement precision of location and time is improved, but loss of information due to data volume increases
Solution Approach 1:
The patent extracts only the essential information from GPS data streams - specifically whether the task person is in movement or idle state, location coordinates, and time stamps. By extracting only relevant data points and discarding redundant information, the system maintains high measurement precision while reducing data volume and management burden.
Solution Approach 2:
Instead of filtering GPS data to remove what is not needed, the patent inverts the approach by selectively capturing only the essential movement/idle state information from the beginning. This inversion strategy reduces data generation at the source while maintaining precise tracking of workforce activity patterns.
3Speed
If real-time GPS data processing is performed to identify movement segments, then responsiveness and workforce monitoring capability are improved, but use of energy by the tracking system increases
Solution Approach 1:
The patent implements periodic evaluation of GPS data at scheduled intervals rather than continuous processing. The system periodically checks whether the task person has transitioned between movement and idle states by comparing current GPS data with previous states, enabling real-time monitoring capability while reducing energy consumption through interval-based processing.
Solution Approach 2:
The patent changes the processing parameter from continuous coordinate analysis to discrete state transition detection. By monitoring changes in velocity and position thresholds rather than processing every GPS coordinate in real-time, the system achieves responsive workforce monitoring with reduced computational energy requirements.
Data Source
AI summary
GPS signal data is converted into movement and idle indicators and is classified as a task-related or privacy event. The task data database lists personnel, location-situs, projected time-of-arrival, time-on-site and other task data. When GPS-location matches task situs, time-on-site data is generated. A movement-ON notes end-of-task. The method gathers pre-set privacy event data from the task person or the task person can, in real time, set ON a privacy block. In real time, the privacy block masks the idle ON and movement ON status until an end-of-privacy time. The method classifies, in real time, idle ON, movement ON and publishes this data on a daily calendar beyond any privacy block. The method also accepts a privacy block re-classification. In real time, status postings note traffic delays, vendor assistance, equipment needed, and co-worker needed indicator. An accounting recovery code can be assigned to the status indicators for billing and accounting purposes.