Dynamic Data Pre-processing for Mobile Resource Scheduling
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Solution Overview
Problem
Current systems for automatic allocation of mobile resources to tasks are not fully automated, leading to suboptimal short-term schedules due to manual adjustments for influencing factors like technician availability and traffic conditions, which can result in inefficiencies and reliability issues, especially during emergencies.
Innovation Solution
A system with two data processing units: one for resource allocation and another for preprocessing dynamic data to generate street-by-street routes and adjust schedules based on real-time factors like weather and traffic, ensuring the most recent information is used without altering the allocation processing unit, and integrating dynamic data into the resource allocation system to improve schedule quality and precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustments are made for influencing factors like technician availability and traffic conditions, then flexibility in handling real-time changes is improved, but automation level deteriorates and schedule optimality worsens
Solution Approach 1:
The system enables self-service automation where the allocation unit automatically processes dynamic data (technician availability, traffic conditions, weather) and adjusts schedules without manual intervention. The pre-processing unit continuously monitors influencing factors and feeds them to the allocation unit, which autonomously optimizes schedules while maintaining full automation.
Solution Approach 2:
The system implements continuous feedback loops where the pre-processing unit monitors real-time conditions (traffic, weather, technician status) and feeds this information back to the allocation unit. This feedback mechanism enables the system to automatically adapt schedules to changing conditions while maintaining high automation levels.
2Ease of operation
If manual adjustments are made for influencing factors, then ease of operation is improved, but manufacturing precision deteriorates
Solution Approach 1:
The system replaces manual mechanical adjustment processes with automated computational processing. The pre-processing unit and allocation unit use algorithms to automatically process dynamic data and generate optimized schedules, substituting human manual operations with precise automated systems that eliminate errors while maintaining ease of use.
Solution Approach 2:
The automated allocation system performs schedule optimization autonomously without requiring manual operations. The system self-adjusts schedules based on processed dynamic data, eliminating the need for manual interventions while achieving high precision through computational algorithms.
3Speed
If straight line distance is used for travel time estimation, then calculation speed is improved, but measurement precision deteriorates
Solution Approach 1:
The pre-processing unit performs preliminary calculations of travel times using optimized algorithms that consider actual road networks and traffic conditions. By pre-calculating and storing route information before allocation, the system achieves both high calculation speed and precise travel time estimates without requiring complex real-time computations during schedule generation.
4Measurement precision
If dynamic data processing is added to improve schedule accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments complex data processing into two specialized units: a pre-processing unit that handles dynamic data collection and initial analysis, and an allocation unit that focuses on schedule optimization. This segmentation allows each unit to specialize in specific tasks, improving overall accuracy while managing complexity through functional separation.
Solution Approach 2:
The pre-processing unit acts as an intermediary between raw dynamic data and the allocation unit. It processes and filters incoming data (traffic, weather, technician status) into standardized formats that the allocation unit can efficiently use, reducing the complexity burden on the allocation unit while maintaining high data quality for accurate scheduling.
Data Source
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AI summary
A system for automatic allocation of mobile resources to tasks comprises at least one database (3) which is arranged to store for each mobile resource (5) at least one corresponding skill (6) and equipment (7) as well as street-level data (9) defining roads between a current location of the mobile resources and the distant locations of the tasks (8), and dynamic data (11) which have a potential impact on the performing of the tasks (8). A first data processing unit (1) is arranged to perform the allocating of the mobile resources (5) to the tasks (8) by allocating the skills (6) to the tasks (8) and to the equipment (7) and to generate for at least one of the mobile resources (5) an individual schedule (10a, 10b, 10c) including a street-by-street route along the roads to the respectively allocated tasks (8). A second data processing unit (2) is provided which is arranged to continuously pre-process the dynamic data (11) in order to determine which of the street-level data (9), the mobile resources (5) and the tasks (8) are affected by the dynamic data (11) and to what extent, and to amend the affected data (5, 8, 9) accordingly.