Remote Supervision via Automated Screen Capture Analysis
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Solution Overview
Problem
Remote supervision of dispersed and outsourced workers is challenging due to the difficulty in accurately tracking their work hours and task engagement, leading to potential overbilling and fraud, as traditional supervision methods are time-consuming and costly.
Innovation Solution
Implementing remote supervision software on client devices to periodically capture screenshots, analyze user activity, and generate activity logs that differentiate between billable and non-billable tasks, with processing occurring on either the client or server device to determine idle and busy periods, enabling accurate compensation and auditing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If self-reporting by remote users is used, then ease of operation is improved, but reliability of work tracking deteriorates
Solution Approach 1:
The system uses the client device's existing screen capture functionality to automatically generate supervision data without requiring additional user actions. The device serves itself by capturing its own screen state and providing this data to the supervision system, eliminating the need for manual time tracking while maintaining ease of operation.
Solution Approach 2:
The patent replaces manual self-reporting mechanisms with automated electronic screen capture and analysis. Instead of users manually recording time, the system uses software to capture screen images, identify active windows, and automatically determine work status, substituting mechanical/manual processes with electronic automation.
2Reliability
If traditional supervision methods are used, then reliability of work tracking is improved, but productivity deteriorates
Solution Approach 1:
The system replaces traditional manual supervision with automated screen capture analysis. The server automatically receives screen captures, identifies active applications and windows, and determines work status without human intervention, maintaining reliable tracking while dramatically improving productivity by eliminating manual review processes.
Solution Approach 2:
The supervision system uses the client device's own screen capture capability to generate supervision data autonomously. The device captures its screen state and transmits it to the server, which automatically processes the data to determine work status, eliminating the need for external human supervisors and thereby improving productivity.
3Measurement precision
If manual time tracking is used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system replaces manual time tracking with automated screen capture analysis. The server receives periodic screen captures, automatically identifies active windows and applications, and determines billable versus non-billable time without human intervention, maintaining precise measurement while eliminating the time loss associated with manual tracking.
Solution Approach 2:
The system performs preliminary screen captures at predetermined intervals to automatically record work activity. By capturing screen states in advance and analyzing them systematically, the system maintains precise time measurement without requiring users to manually track time, thereby reducing time loss.
Data Source
AI summary
A server device may receive a series of at least two screen capture representations of a graphical user interface on a client device. A first active window for a first screen capture representation of the series and a second active window for a second screen capture representation of the series may be determined. The first screen capture representation may have been screen captured by the client device at a first time and the second screen capture representation may have been screen captured by the client device at a second time. A first application associated with the first active window and a second application associated with the second active window may be identified, at least one of which may be a pre-determined target application. Based on the identified applications, an activity log for the client device may be determined.