Edge Computing Device for IoT Control Latency Reduction
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Solution Overview
Problem
Conventional IoT systems face communication latency and bandwidth limitations when using programmable logic controllers (PLCs) that interfere with the operation of IoT-controlled devices, resulting in low temporal resolution and restricted control schemes due to high latency and limited data resolution.
Innovation Solution
A computing device is configured to receive sensor data from IoT devices, identifying subsets for local and remote processing, using machine learning models to generate control instructions and transmit data accordingly, thereby reducing latency and enhancing processing capabilities by distributing tasks between local and remote computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If sensor data is processed locally at the edge computing device, then control latency is reduced and real-time control is improved, but computational complexity and processing capability are limited
Solution Approach 1:
The patent segments the computational tasks into two categories: time-critical control tasks processed locally at the edge computing device, and non-time-critical analytical tasks processed remotely at the server computing device. This segmentation allows the system to achieve real-time control response while utilizing remote computational resources for complex processing, thereby resolving the contradiction between low latency and high computational capability.
2Device complexity
If sensor data is transmitted to remote computing devices, then processing capability is enhanced, but communication bandwidth requirements increase
Solution Approach 1:
The patent extracts only the essential control decisions and minimal sensor data to the remote server, rather than transmitting all raw sensor data. The edge computing device performs preliminary processing and transmits only necessary information, reducing communication bandwidth requirements while still enabling remote computational enhancement for non-time-critical tasks.
3Speed
If all control processing is done locally, then response time is improved, but control scheme complexity is restricted
Solution Approach 1:
The patent introduces a temporal dimension to control processing by separating time-critical and non-time-critical tasks across different locations. Local processing handles immediate response requirements, while remote processing handles complex analytical tasks that do not require immediate response. This dimensional separation allows the system to achieve both fast response times and complex control schemes simultaneously.
Data Source
AI summary
A computing device, including a processor configured to receive sensor data from a control device. The control device may include a control processor configured to execute control instructions to control an actuator of a target electromechanical system and may further include one or more sensors. The processor may identify a first subset of the sensor data and a second subset of the sensor data. The processor may generate first control instructions based on the first subset and transmit the first control instructions to the control processor of the control device. The processor may transmit the second subset to a remote computing device. In response to transmitting the second subset to the remote computing device, the processor may receive a remote processing result from the remote computing device. The processor may generate second control instructions from the remote processing result and transmit the second control instructions to the control processor.