Edge Driver History Tracking for Secure Vehicle Telematics

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Solution Overview

Problem

Current fleet management systems rely on manual and complex processes for associating drivers with vehicles, leading to inefficiencies and increased costs due to the need for cloud-based infrastructure and out-of-band communications.

Innovation Solution

The implementation of automated systems and methods that utilize non-transitory computer-readable media to store and execute instructions for tracking historic driver data on vehicles, reducing manual processing by securely storing and retrieving data on the edge, and minimizing data transmission to the cloud.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If cloud-based infrastructure and out-of-band communications are used to associate drivers with vehicles, then driver-vehicle association can be established, but system complexity and manual processing requirements increase

Engineering Contradiction:

Improvedriver-vehicle association accuracyVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent extracts the driver identification and data storage functionality from the cloud-based back-end system and places it directly on the telematic device (edge device). This eliminates the need for out-of-band communications and manual processing, while maintaining reliable driver-vehicle association through on-device driver identification technology.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The telematic device performs driver identification and data processing autonomously without requiring manual intervention or complex back-end system coordination. The device self-manages driver identification, historic data storage, and scoring calculations, reducing system complexity while maintaining association accuracy.

Inventive Principle:

Principle #25Self-service

2Loss of information

If all vehicle and driver data are stored in the cloud for analysis, then comprehensive data analysis can be performed, but data transmission costs and cloud storage requirements increase

Engineering Contradiction:

Improvedata analysis completenessVSAvoiddata transmission cost

Core Design Contradiction:

Loss of informationVSLoss of energy

Solution Approach 1:

The patent segments the data processing function into two parts: historic driver data is stored and processed locally on the telematic device, while only scoring results and summaries are transmitted to the cloud. This segmentation reduces data transmission costs while maintaining analysis completeness by performing calculations at the edge.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent moves data storage and processing from the traditional cloud-only dimension to include the edge dimension (telematic device). This dimensional shift allows historic data to reside locally, eliminating the need for continuous cloud transmission while preserving analytical capabilities.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Ease of manufacture

If manual processes are used for driver identification and data updating, then system implementation is simpler, but processing efficiency and accuracy decrease

Engineering Contradiction:

Improvesystem implementation simplicityVSAvoidprocessing efficiency

Core Design Contradiction:

Ease of manufactureVSProductivity

Solution Approach 1:

The patent replaces manual mechanical processes with automated electronic driver identification technology. The telematic device automatically identifies drivers using electronic methods (such as smartphone proximity detection), eliminating manual data entry and updating while maintaining implementation feasibility through standardized hardware interfaces.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Extent of automation

If driver identification relies on smartphone detection, then automated identification is achieved, but the system fails when multiple drivers are present in the vehicle

Engineering Contradiction:

Improvedriver identification automationVSAvoiddriver identification accuracy

Core Design Contradiction:

Extent of automationVSMeasurement precision

Solution Approach 1:

The patent uses smartphone proximity detection as a preliminary filtering step to identify potential drivers in the vehicle. When multiple smartphones are detected, the system then applies additional discrimination methods (such as comparing device identifiers with registered driver information) to precisely identify the actual driver, maintaining both automation and accuracy.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250033648A1Systems and methods for tracking historic driver data on the edge

Publication Date: 2025.01.30 MOTER TECHNOLOGIES INC

AI summary

Driver insurance and risk management scores are calculated per driver based on vehicle and driver behavior data collected during driving sessions. Often one vehicle is shared by multiple drivers and one driver can drive multiple vehicles. The present disclosure securely tracks the individual drivers, stores, and retrieves associated driver data for analysis on the edge (vehicle) in near real time. Data collected is analyzed at various time intervals (each trip, daily, monthly) to produce the scores. The goal of the proposed solution minimizes cost associated with data transmission and cloud storage, tracks long term driver driving history on the edge for near real time analysis of driver behavior, minimizes driver distraction due to user device while driving, securely stores and retrieves driver driving data on the edge device associated with the driver, restricts access to the driver driving data, and restricts user device access to servers and telematic units.