Energy Data Classification at the Edge: A Comparative Study for Energy Efficiency Applications

Date

2023

Advisors

Journal Title

Journal ISSN

ISSN

1386-7857

Volume Title

Publisher

Springer

Type

Article

Peer reviewed

Yes

Abstract

As the global economy is increasingly influenced by energy policy and efficiency, the opportunities of energy data classification are broadening. Performance metrics, especially for Deep Learning (DL), have motivated the accelerated development of computing hardware. In particular, High-Performance Edge Computing (HPEC) has an important role in complementing cloud computing in the collection, pre-processing, and post-processing of big data in a more privacy-preserving manner. Yet, such opportunities bring challenges concerning the selection of hardware platforms and classification algorithms. Therefore, in this article, we aim to carry out a comparative study that examines the merits, performance and efficiency metrics, and limitations of notable HPEC platforms centered around a DL classification framework. In this implementation, a novel 2D Gramian Angular Field (GAF) energy data classifier is presented and run on a publicly available dataset. Following, a DL classifier is trained and exported as a lightweight counterpart for validation on several commonly used HPEC platforms, namely the Jetson Nano, ODROID-XU4, Coral Dev Board, and the BeagleBone AI. Current results show competitive computational performance among the reviewed platforms, as fast as ~8 msec per classified image.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link

Keywords

Energy efficiency, high performance edge computing, artificial intelligence, data lake, deep learning, internet of energy, Gramian angular fields

Citation

Alsalemi, A., Amira, A., Malekmohamadi, H. and Diao, K. (2023) Energy Data Classification at the Edge: A Comparative Study for Energy Efficiency Applications. Cluster Computing

Rights

Research Institute

Institute of Artificial Intelligence (IAI)