IoT Asset Tracker Evaluating Vibration and Speed Data
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Solution Overview
Problem
Current IoT/M2M solutions fail to effectively track the job status of assets, including equipment operation and runtime, especially in scenarios where assets are removably attached and lack continuous cellular connectivity, making it difficult to monitor the location, vibration, and speed data of assets like lawn mowers or generators.
Innovation Solution
A computer-implemented method and system that utilizes IoT devices attached to assets to receive and evaluate location, vibration, and speed data, integrating a storage database, decision system, and user interface to determine job status based on specified conditions, incorporating machine learning to predict future asset activity and provide real-time job status updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If IoT devices are used to track asset location and activity data, then measurement precision of asset status is improved, but device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The system segments the tracking functionality into separate specialized components: GPS receiver for location data, speed sensor for velocity data, vibration sensor for operational status, and processor for data integration. This segmentation allows each component to be optimized for its specific function while reducing overall system complexity through modular design.
Solution Approach 2:
The IoT device is designed as a multi-functional unit that simultaneously performs location tracking, speed measurement, vibration detection, and job status determination. This universal device consolidates multiple monitoring functions into a single platform, reducing the need for separate tracking systems and simplifying deployment.
2Loss of information
If multiple sensors and data processing are implemented to determine job status, then information completeness about asset operation is improved, but loss of time for data processing and analysis increases
Solution Approach 1:
The system pre-establishes decision rules and thresholds for determining job status conditions before data collection begins. The processor is pre-programmed with logic to immediately evaluate sensor data against these predefined criteria, enabling real-time status determination without complex post-processing analysis.
Solution Approach 2:
The system implements continuous feedback loops where sensor data is constantly monitored and immediately processed to update job status information. This real-time feedback mechanism ensures that status information remains current and complete while minimizing processing delays through automated decision algorithms.
Data Source
AI summary
A computer-implemented method, system and a computer program product for providing job status information of an asset to which an IoT device is attached are disclosed. In an example embodiment, the computer implemented method for providing job status information of an asset to which an IoT device is attached includes receiving job information for one or more jobs; receiving location data, vibration data, and speed data from the IoT device attached to the asset. The method further includes evaluating the location data, vibration data, and speed data with respect to the received job information for the one or more jobs to determine the job status of the asset to which the IoT device is attached based on specified conditions.