Low Power Communications Engine Location Trust Assessment
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Solution Overview
Problem
Always-on communication systems using low power wide area networks (LPWAN) face challenges in managing battery life due to constant connectivity, even during dormant states, as they require continuous power to maintain security and manageability solutions, which can lead to increased power consumption and reduced device lifespan.
Innovation Solution
Implementing a low power communications engine that employs machine learning to assess location trust levels, allowing for selective wake-up of the operating system only when necessary, based on detected location and network security, thereby reducing unnecessary power consumption by limiting data traffic and prioritizing messages accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If always-on connectivity is maintained via LPWAN radio system, then security and management solutions can function continuously, but battery life is burdened due to constant power consumption
Solution Approach 1:
The system transitions from continuous operation to periodic operation by entering sleep states at predetermined intervals. The low power communications engine periodically wakes up to check for incoming messages and then returns to sleep mode, maintaining security and management functionality while significantly reducing power consumption compared to continuous operation.
Solution Approach 2:
The system performs preliminary actions by checking for incoming messages during brief wake periods before entering extended sleep states. This allows the system to prepare for potential security or management tasks in advance, ensuring rapid response capability while minimizing active power consumption time.
2Duration of action of moving object
If the system enters sleep states to conserve power, then battery life is extended, but continuous communications capability is reduced
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring for incoming messages through the low power communications engine. When messages are detected during sleep states, the system receives feedback and immediately transitions to active state to process communications, thus maintaining reliable communication capability while preserving battery life through extended sleep periods.
Solution Approach 2:
The low power communications engine acts as an intermediary between the sleep state system and the active communication system. It maintains a minimal connection to the LPWAN network during sleep states, serving as a mediator that can detect incoming messages and trigger system wake-up without requiring the full system to remain active, thereby balancing battery life extension with communication reliability.
3Use of energy by moving object
If machine learning is used to assess location trust levels and control wake-up, then power consumption is reduced, but system complexity increases
Solution Approach 1:
The system implements self-service by using machine learning algorithms that automatically assess location trust levels and make autonomous decisions about system wake-up without requiring manual configuration or intervention. The low power communications engine self-manages the balance between power consumption and communication responsiveness based on real-time location analysis, reducing the need for complex external control mechanisms.
Data Source
AI summary
An information handling system operating a low power communications engine comprising a wireless adapter for communicating on a low power communication technology network for receiving low power communication technology data traffic for at least one always-on remote management service for the information handling system, a controller receiving a location status of the information handling system via the low power communication technology network indicating a location or network, where the controller executes code instructions for a low power communications engine to assess a location trust level from an environment characteristics analysis engine to determine whether the location status is a trusted zone location or an untrusted zone location utilizing binary classification machine learning based on input variables including data relating to history of activity at the location or on the network learned by the environment characteristics analysis engine from reported operational or network activity, and the controller to trigger an embedded controller to wake a BIOS of the information handling system and forward the incoming low power communication technology data traffic to in-band applications on the information handling system if the information handling system location status is determined to be in one trusted zone location and the controller to ignore the received low power communication technology data traffic if the information handling system location status is in one untrusted zone location.