LP-OPTIMA:用于低功耗嵌入式系统的物联网资源的规范性维护和优化框架.
Alexios Papaioannou1,2, Asimina Dimara1,2,3, Charalampos S Kouzinopoulos1
1Centre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece.
Sensors (Basel, Switzerland)
|April 13, 2024
概括
本研究介绍了用于低功耗嵌入式系统的AI故障检测模块. 这种新的方法显著提高了故障耐受性和维护,在现实世界测试中实现了超过98%的性能.
科学领域:
- 计算机工程 计算机工程
- 嵌入式系统 嵌入式系统
- 人工智能的人工智能
背景情况:
- 低功耗嵌入式系统对于数据收集和交换至关重要,但由于故障预测和监控的局限性,它们面临维护挑战.
- 现有的资源管理框架缺乏针对低功耗嵌入式系统故障的特定协议.
- 识别故障和实施定制反应机制仍然是复杂的.
研究的目的:
- 解决低功耗嵌入式系统中的维护和故障检测缺口.
- 提出一个三边框架,包括利益相关者指导,自动控制和人工智能驱动的故障检测.
- 提高这些系统的可靠性和容错性.
主要方法:
- 制定一个三边框架,定期规定利益相关者和自动控制机制.
- 实施备份AI故障检测模块.
- 设计和开发使用ARM Cortex核心进行评估的三种新型自主嵌入式系统.
主要成果:
- 人工智能故障检测模块在现实测试中表现出色.
- 在开发的嵌入式系统中,评估指标始终超过98%.
- 这种方法在提高故障耐受性和维护能力方面被证明是有效的.
结论:
- 拟议的AI故障检测模块显著提高了低功耗嵌入式系统的可靠性.
- 三边框架为系统维护和故障预防提供了全面的解决方案.
- 开发的方法对于关键的嵌入式应用程序是非常有效和可靠的.
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