Sensor-Based Employee Task Identification
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Solution Overview
Problem
It is challenging to accurately track and record employee tasks performed in the field, leading to incomplete or inaccurate timesheets, which complicates accounting, invoicing, and compliance with regulations, as different tasks may be billed at different rates and governed by various regulations.
Innovation Solution
A method and system that utilize sensor data from workspace devices, including geolocation and motion sensors, to determine the closest task category matching the sensor data, allowing for real-time tracking of employee tasks, generation of invoices, and compliance reports, and triggering alerts for regulatory violations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If employee timesheets are manually completed, then employees can report their tasks, but the timesheets are often incomplete or inaccurate
Solution Approach 1:
The system automatically generates task records by comparing sensor data with task definitions, eliminating the need for manual employee input. The sensor data self-determines task categories, start times, and locations, creating accurate and complete timesheets without relying on employee reporting
Solution Approach 2:
The patent replaces the manual mechanical process of filling out timesheets with an automated sensor-based system. Sensors continuously collect data and the system automatically processes this information to generate task records, substituting human effort with automated detection and processing
2Productivity
If manual task tracking is used, then employees can report tasks, but it complicates accounting, invoicing and reporting compliance
Solution Approach 1:
The system automatically generates invoice-ready task records with all necessary information including task categories, start and end times, locations, and billing rates. This self-generating capability eliminates manual compilation and reduces the complexity of compliance tracking
Solution Approach 2:
The system continuously monitors sensor data and automatically updates task records, providing real-time feedback on task completion status. This continuous monitoring and automatic updating simplifies compliance tracking by maintaining current information without manual intervention
3Measurement precision
If sensor data is collected from workspace devices, then task identification accuracy improves, but data processing complexity increases
Solution Approach 1:
The system pre-processes sensor data by continuously collecting and storing it in a normalized format, and pre-defines task categories with their corresponding sensor data patterns. This preliminary preparation reduces the complexity of real-time task identification by having data ready for immediate comparison and matching
Data Source
AI summary
A method may include obtaining first sensor data from first sensors of first workspace devices and a first timestamp corresponding to the first sensor data. The first sensors of each workspace device may include a geolocation sensor. The first workspace devices may include an employee device corresponding to an employee. The method may further include obtaining task categories. Each task category may include a sensor data pattern. The method may further include calculating, for each task category, a first task distance between the sensor data pattern and the first sensor data. The method may further include determining a first task category based on the first task category having the first task distance that is shortest. The method may further include creating, based on the first task category, a first task instance with a start time equal to the first timestamp. The first task instance is assigned to the employee.