Telematics Machine Usage Monitoring for Risk-Linked Resources
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Solution Overview
Problem
Operators of machines, such as motor vehicles, often misrepresent or underrepresent their usage, leading to inaccurate risk assessments and potential misallocation of resources, necessitating a need for secure and accurate remote monitoring systems.
Innovation Solution
A system comprising sensors proximate to the machine, a control unit, and a back-end application server that calculates operator and machine scores based on sensor data, dynamically updating risk relationship identifiers and resource amounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If operators self-report machine usage, then data collection is simple and low-cost, but data accuracy deteriorates due to misrepresentation or underrepresentation
Solution Approach 1:
The patent replaces manual self-reporting (mechanical/human system) with automated electronic sensors and telematics systems that directly measure machine usage parameters. This substitution eliminates human bias and misrepresentation while maintaining ease of data collection through automated digital tracking.
Solution Approach 2:
The patent introduces an intermediary telematics system between the operator and the data collection process. This intermediary automatically captures usage data through sensors and transmission devices, preventing direct operator manipulation while keeping the system simple to implement.
2Measurement precision
If remote monitoring systems are implemented, then usage data accuracy is improved, but system complexity increases
Solution Approach 1:
The patent employs multi-functional telematics devices that perform multiple tasks: monitoring machine usage, tracking location, detecting operational parameters, and transmitting data. This consolidation reduces overall system complexity compared to implementing separate systems for each function.
Solution Approach 2:
The patent merges sensor components, processing units, and communication modules into integrated telematics systems. By combining these elements into unified devices, the system achieves accurate remote monitoring while minimizing the number of discrete components and simplifying installation.
3Measurement precision
If dynamic resource allocation based on multiple scores is implemented, then resource allocation accuracy is improved, but computational requirements and processing time increase
Solution Approach 1:
The patent calculates operator behavior scores, machine operation scores, and machine characteristics scores in advance based on historical and real-time data. These pre-calculated scores are stored and quickly retrieved for dynamic resource allocation decisions, reducing processing time when updates are needed.
Solution Approach 2:
The patent implements a feedback mechanism where scores are continuously updated based on new sensor data and usage patterns. This allows the system to maintain accurate resource allocation decisions through incremental updates rather than complete recalculations, reducing processing time while improving accuracy over time.
Data Source
AI summary
Embodiments may monitor utilization of a machine. A risk relationship data store may contain electronic records that represent a plurality of risk relationships with an enterprise. A device located proximate to the machine includes a plurality of sensors, each sensor configured to monitor at least one parameter (e.g., acceleration, speed, mileage, run-time and location sensors, etc.). A back-end application computer server may calculate an operator behavior score and a machine operation score based on sensor signals. The computer server may also determine a machine characteristics score and an amount of utilization associated with the machine. A risk relationship identifier associated with the machine is identified, and the computer server may automatically and dynamically update a resource amount associated with the risk relationship identifier based on the operator behavior score, the machine operation score, the machine characteristics score, and the amount of utilization associated with the machine.