Configurable IoT Edge Device Data Filtering
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Solution Overview
Problem
IoT devices face challenges in efficiently managing telemetry data transmission, often requiring specific code and deployment-specific configurations, leading to high communication, computation, and storage costs, as well as bandwidth wastage by sending all data to the cloud at sample rates.
Innovation Solution
Configurable edge devices are programmed to send only requested subsets of telemetry data at determined frequencies, eliminating the need for solution-specific code and allowing for efficient data filtering, buffering, and transmission, thereby reducing bandwidth usage and operational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If IoT devices send all telemetry data to the cloud at sample rates, then data completeness is improved, but bandwidth usage and communication costs increase
Solution Approach 1:
The patent applies preliminary action by configuring edge devices in advance to perform data filtering, buffering, and selective transmission. The edge devices are pre-configured with rules to determine which telemetry data should be sent to the cloud and at what frequency, eliminating the need to send all raw data at sample rates. This preliminary configuration resolves the contradiction by ensuring data completeness for required parameters while reducing overall bandwidth consumption through intelligent pre-processing at the edge.
Solution Approach 2:
The patent extracts only the necessary subset of telemetry data from the complete data stream at the edge device level. Instead of transmitting all generated telemetry data to the cloud, the system extracts and transmits only the specific data types and frequencies required by the application. This extraction principle directly addresses the contradiction by maintaining data completeness for required parameters while significantly reducing bandwidth usage for unnecessary data transmission.
2Manufacturing precision
If IoT devices are configured with solution-specific code, then deployment precision is improved, but device complexity and ease of deployment worsen
Solution Approach 1:
The patent applies dynamics by making the edge device configuration dynamic and adaptable rather than static and solution-specific. The system allows runtime configuration of telemetry data collection parameters, enabling the same edge device to adapt to different deployment scenarios without requiring different code. This dynamic configuration approach maintains deployment precision while reducing device complexity by eliminating the need for multiple solution-specific codebases.
Solution Approach 2:
The patent implements universality by designing a single, generic edge device platform that can serve multiple different IoT solutions and deployment scenarios. The universal edge device uses configurable parameters and rules to adapt to various requirements without requiring solution-specific code. This multi-functionality resolves the contradiction by achieving deployment precision through configuration rather than specialized code, thereby reducing overall device complexity.
3Loss of information
If all telemetry data is transmitted to the cloud, then data availability is improved, but computation and storage costs increase
Solution Approach 1:
The patent applies segmentation by dividing the data processing function between edge devices and cloud infrastructure. Instead of transmitting all raw telemetry data to the cloud for processing, the system segments the workload by performing filtering, buffering, and selective transmission at the edge device level. Only the necessary subset of processed data is sent to the cloud, maintaining data availability for required parameters while significantly reducing cloud computation and storage costs.
4Loss of time
If IoT devices send data at sample rates, then data freshness is improved, but bandwidth consumption and costs increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the transmission frequency and data selection parameters at the edge device level. Instead of transmitting all data at the maximum sample rate, the system changes transmission parameters based on data importance, current state changes, and configured requirements. This allows the system to maintain data freshness for critical parameters by transmitting them at appropriate intervals while reducing communication costs by not transmitting all data at maximum frequency.
Data Source
AI summary
The disclosed technology is generally directed to communications in an IoT environment. For example, such technology is usable in IoT communications. In one example of the technology, one or more types of telemetry data to be collected from a first IoT device is determined. A send frequency corresponding to at least one of the one or more types of telemetry data to be collected from the first IoT device is determined. A first automatic configuration to a configurable device is sent. The configurable device is at least one of the first IoT device or an intermediary device in communication with the first IoT device, such that, upon execution of the first automatic configuration, the configurable device automatically sends telemetry data of the determined one or more types of telemetry data to the IoT solution service at the determined send frequency.