This paper presents an embedded NILM engine to enable load disaggregation intelligence and explore its potential application as an energy management system. In this sense, the power meter is upgraded to a novel category called cognitive power meter. Therefore, this paper discloses a heterogeneous multiprocessing approach to attend NILM prerequisites and increase household interactivity. The proposed NILM performs the microscopic analysis using the Conservative Power Theory (CPT) for feature extraction; k-Nearest Neighbors (k-NN) for the appliance classification; and the Power Signature Blob (PSB) for energy disaggregation. Results show NILM can be performed on-site, embedded into modern cognitive power meters, and it may support households on providing valuable information concerning appliances' usage for energy management systems.

中文翻译：

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嵌入式 NILM 作为家庭能源管理系统：一种异构计算方法

本文介绍了一种嵌入式 NILM 引擎，以实现负载分解智能并探索其作为能源管理系统的潜在应用。从这个意义上说，功率计升级为一个新的类别，称为认知功率计。因此，本文公开了一种异构多处理方法来满足 NILM 先决条件并增加家庭互动性。提议的 NILM 使用保守幂理论 (CPT) 进行微观分析以进行特征提取；k-最近邻（k-NN）用于设备分类；以及用于能量分解的 Power Signature Blob (PSB)。结果表明 NILM 可以在现场执行，嵌入到现代认知功率计中，它可以支持家庭为能源管理系统提供有关电器使用的有价值的信息。