Edge AI Device for Offline Computing Repair
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Solution Overview
Problem
Remote computer technical support is hindered when a computing device lacks an internet connection, as existing solutions rely on internet access for troubleshooting and repair.
Innovation Solution
A stand-alone embedded IoT edge AI device (EIEAC) is used, which is physically coupled to the computing device, providing independent internet connectivity, data storage, and processing capabilities to monitor and repair issues using tinyML and edge AI, even without an active internet connection on the device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If remote technical support is provided through internet connection, then accessibility and affordability are improved, but support is lost when the computing device cannot support an internet connection
Solution Approach 1:
The system divides technical support functionality into two independent components: a client agent application running on the computing device and a remote assistance application running on the support technician's device. This segmentation allows the support function to operate independently of the computing device's internet connection status, as the remote assistance application can directly connect to the client agent through local network communication.
Solution Approach 2:
The patent introduces a peer-to-peer communication channel as an intermediary between the client agent and remote assistance application. This intermediary enables direct communication without requiring the computing device to maintain an active internet connection, thereby ensuring reliable technical support availability even when the device is offline.
2Ease of operation
If the computing device maintains internet connection for remote support, then technical support accessibility is improved, but device resources and power consumption increase
Solution Approach 1:
The client agent application operates periodically by listening for incoming connection requests from the remote assistance application. Instead of maintaining a continuous active internet connection, the system uses event-triggered communication where the client agent only becomes actively engaged when technical support is actually needed, thereby reducing unnecessary power consumption.
Solution Approach 2:
The system enables self-service technical support by allowing the remote assistance application to directly establish communication with the client agent without requiring the computing device to actively maintain internet connectivity. The device only consumes significant power when actually receiving or providing support, rather than continuously maintaining an internet connection.
Data Source
AI summary
A stand-alone embedded internet of things edge artificial intelligence device (“EIEAC”) may be provided. The EIEAC may be configured to operate independent of the computing device and may be configured to monitor and repair failures occurring at the computing device. The EIEAC may receive computer health data from a client agent application running on the computing device. The EIEAC may include a memory configured to store the computer health data and a battery configured to charge the EIEAC. The EIEAC may include a processor configured to process the computer health data to identify one or more failures using tiny machine learning (“tinyML”). When one or more failures are identified by the processor, the tinyML may be configured to execute instructions on the computer health data for repairing the one or more failures. When unsuccessful, the EIEAC may establish an electronic connection with a remote cloud lookup tower for repairing.