Aperiodic Nonrandom Triggers for Vehicular Telematics Data Queries
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Solution Overview
Problem
Conventional vehicular telematics systems lack efficient approaches for monitoring normal vehicle operations, as they either rely on periodic or random data transmissions that do not correlate with the vehicle's current state, leading to inefficient data harvesting and management.
Innovation Solution
A vehicular telemetry apparatus that initiates querying, logging, and data transmission in response to operationally-salient changes detected by sensors, using aperiodic and non-random triggers based on sensed vehicular conditions, allowing for selective and relevant data collection and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If periodic data transmission is used, then data coverage is maintained, but redundant data transactions increase and bandwidth is wasted
Solution Approach 1:
The system dynamically adjusts data transmission timing based on real-time vehicle operational state. Instead of fixed periodic intervals, the telematics device continuously monitors vehicle sensors and triggers data transmission only when operational changes are detected, making the transmission schedule adaptive to actual vehicle conditions rather than static
Solution Approach 2:
The system changes the transmission parameter from fixed time intervals to event-driven triggers based on vehicle operational parameters. By monitoring changes in vehicle state parameters (engine on/off, gear changes, braking events), the system determines when data transmission is necessary, transforming the transmission logic from time-based to condition-based
2Loss of energy
If random data transmission is used, then bandwidth is reduced, but data coverage and operational monitoring are compromised
Solution Approach 1:
The system implements feedback by continuously monitoring vehicle operational state and using this information to determine transmission timing. Sensors provide real-time feedback on vehicle conditions, and this feedback loop enables the telematics device to intelligently decide when data transmission is necessary, ensuring both bandwidth efficiency and operational coverage
Solution Approach 2:
The system performs preliminary monitoring of vehicle operational state before triggering data transmission. By continuously sensing and evaluating vehicle conditions in advance, the system prepares to transmit data at the optimal moment when operational changes occur, ensuring data is captured when most relevant without unnecessary transmissions
3Loss of information
If continuous monitoring is implemented, then operational relevance is maximized, but data transaction volume and processing load increase
Solution Approach 1:
The system extracts only the essential operational changes from continuous vehicle monitoring data. Instead of transmitting all monitored parameters continuously, the system identifies and extracts only those operational state changes that are significant (engine start/stop, gear shifts, braking events), filtering out redundant information while maintaining operational relevance
Solution Approach 2:
The system segments continuous vehicle operation into distinct operational events or states. By dividing the continuous monitoring stream into discrete, meaningful events (each representing a specific operational change), the system enables targeted data transmission for each event rather than continuous data flow, improving transaction efficiency
Data Source
AI summary
A vehicular telemetry apparatus, operable to initiate a telemetry processing operation in response to an aperiodic, nonrandom trigger signal cued by a sensed, operationally-variable vehicular condition. A trigger unit provides the trigger signal which in turn switches the telemetry apparatus from a resource-conserving idle state to a state in which a session is initiated, so that operationally salient variations in information on changes in vehicle sensor data are detected and processed.