Moving Object Problem Resolution Through Skill-Based Personnel Selection
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Solution Overview
Problem
Existing technologies struggle to efficiently address problems faced by moving objects in human working environments, such as obstacles or malfunctions, often requiring manual intervention that can be slow or ineffective.
Innovation Solution
An information processing apparatus that acquires information about the moving object and potential problem-solvers, selects a suitable person based on skill and proximity, and notifies them to resolve the issue, optionally adjusting task priorities and providing rewards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If remote operation or security guard calling is used to solve problems faced by moving objects, then the problem can be solved with human intervention, but the response time is slow and task execution is disturbed for a long duration
Solution Approach 1:
The system performs preliminary actions by pre-acquiring attribute information about surrounding persons (skills, positions, availability) and storing it in advance. When a problem occurs, the information processing apparatus immediately queries this pre-acquired data to rapidly identify and notify the most suitable person, eliminating the need for time-consuming on-site assessments or manual searches for available personnel.
Solution Approach 2:
The system replaces the mechanical/manual process of finding and notifying personnel with an automated information processing system. The apparatus automatically queries attribute information, determines the most suitable person based on predefined criteria (skills, position, availability), and sends notifications without human intervention, significantly reducing response time compared to manual remote operation or security guard calling.
2Loss of time
If any available person is notified to solve the problem, then the response time is reduced, but the problem may not be solved effectively due to lack of relevant skills
Solution Approach 1:
The system applies local quality by selecting persons based on their specific attribute information (skills, knowledge, experience) that matches the problem type. Instead of uniformly notifying any available person, the apparatus queries and compares individual attributes against problem requirements, ensuring that the notification is directed to the person with the most relevant local expertise for that specific problem.
Solution Approach 2:
The system changes the selection parameter from simple availability (binary state) to a multi-dimensional assessment including skill level, knowledge area, experience, and current workload. By querying and comparing these varying parameters, the apparatus determines the most suitable person rather than just the first available person, thereby maintaining high problem-solving effectiveness while still achieving rapid notification.
Data Source
AI summary
A moving object information acquisition unit acquires information about a moving object under management. If a problem occurs to disturb a task execution by the moving object, a problem information acquisition unit acquires information about details of the problem. A personal information acquisition unit acquires attribute information about at least one candidate of a problem-solving person. A person selection unit selects a problem-solving person from the at least one candidate based on the information about the moving object acquired by the moving object information acquisition unit, the information about details of the problem acquired by the problem information acquisition unit, and the attribute information about the at least one person acquired by the personal information acquisition unit.