Towards Green Edge Intelligence

Sami Ben Cheikh; Stephan Sigg

doi:10.1145/3627050.3630737

Towards Green Edge Intelligence

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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Abstract

This study presents our ongoing activities, along with a demonstration that showcases the integration of these endeavours into a real-world application. We demonstrate the integration of IoT devices with energy harvesting systems, as well as the incorporation of deep learning techniques into IoT devices. Finally, we consider the utilization of radio frequency (RF) technology for gesture detection and classification, based on deep learning algorithms.

Original language	English
Title of host publication	IoT 2023 - Proceedings of the 13th International Conference on the Internet of Things
Publisher	ACM
Pages	197-199
Number of pages	3
ISBN (Electronic)	979-8-4007-0854-1
DOIs	https://doi.org/10.1145/3627050.3630737
Publication status	Published - 22 Mar 2024
MoE publication type	A4 Conference publication
Event	International Conference on the Internet of Things - Nagoya, Japan Duration: 7 Nov 2023 → 10 Nov 2023 Conference number: 13

Conference

Conference	International Conference on the Internet of Things
Abbreviated title	IoT
Country/Territory	Japan
City	Nagoya
Period	07/11/2023 → 10/11/2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 13 Climate Action

Keywords

Cloud computing
E-Health
Edge intelligence
Internet of Things
Smart Cities
Wireless power transfer

Access to Document

10.1145/3627050.3630737

IoT_2023_paper_7879Accepted author manuscript, 115 KB

Cite this

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title = "Towards Green Edge Intelligence",

abstract = "This study presents our ongoing activities, along with a demonstration that showcases the integration of these endeavours into a real-world application. We demonstrate the integration of IoT devices with energy harvesting systems, as well as the incorporation of deep learning techniques into IoT devices. Finally, we consider the utilization of radio frequency (RF) technology for gesture detection and classification, based on deep learning algorithms.",

keywords = "Cloud computing, E-Health, Edge intelligence, Internet of Things, Smart Cities, Wireless power transfer",

author = "\{Ben Cheikh\}, Sami and Stephan Sigg",

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doi = "10.1145/3627050.3630737",

language = "English",

pages = "197--199",

booktitle = "IoT 2023 - Proceedings of the 13th International Conference on the Internet of Things",

publisher = "ACM",

address = "United States",

note = "International Conference on the Internet of Things, IoT ; Conference date: 07-11-2023 Through 10-11-2023",

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AU - Ben Cheikh, Sami

AU - Sigg, Stephan

N1 - Conference code: 13

PY - 2024/3/22

Y1 - 2024/3/22

N2 - This study presents our ongoing activities, along with a demonstration that showcases the integration of these endeavours into a real-world application. We demonstrate the integration of IoT devices with energy harvesting systems, as well as the incorporation of deep learning techniques into IoT devices. Finally, we consider the utilization of radio frequency (RF) technology for gesture detection and classification, based on deep learning algorithms.

AB - This study presents our ongoing activities, along with a demonstration that showcases the integration of these endeavours into a real-world application. We demonstrate the integration of IoT devices with energy harvesting systems, as well as the incorporation of deep learning techniques into IoT devices. Finally, we consider the utilization of radio frequency (RF) technology for gesture detection and classification, based on deep learning algorithms.

KW - Cloud computing

KW - E-Health

KW - Edge intelligence

KW - Internet of Things

KW - Smart Cities

KW - Wireless power transfer

UR - https://www.scopus.com/pages/publications/85189361076

U2 - 10.1145/3627050.3630737

DO - 10.1145/3627050.3630737

M3 - Conference article in proceedings

SP - 197

EP - 199

BT - IoT 2023 - Proceedings of the 13th International Conference on the Internet of Things

PB - ACM

T2 - International Conference on the Internet of Things

Y2 - 7 November 2023 through 10 November 2023

ER -

Towards Green Edge Intelligence

Abstract

Conference

UN SDGs

Keywords

Access to Document

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