Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI

Behrooz Azadi; Bernhard Anzengruber-Tanase; Georgios Sopidis; Michael Haslgrübler; Alois Ferscha

doi:10.1145/3770501.3770529

Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI

Behrooz Azadi
, Bernhard Anzengruber-Tanase
, Georgios Sopidis
, Michael Haslgrübler
, Alois Ferscha

Institute of Pervasive Computing

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

Original language	English
Title of host publication	IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025
Editors	Stefan Nastic, Florian Michahelles, Sashko Ristov, Patrizio Dazzi, Florian Wolling
Publisher	Association for Computing Machinery, Inc
Pages	237-244
Number of pages	8
Edition	1
ISBN (Electronic)	9798400715952
DOIs	https://doi.org/10.1145/3770501.3770529
Publication status	Published - 12 Dec 2025
Event	15th International Conference on the Internet of Things, IoT 2025 - Vienna, Austria Duration: 18 Nov 2025 → 21 Nov 2025

Conference

Conference	15th International Conference on the Internet of Things, IoT 2025
Country/Territory	Austria
City	Vienna
Period	18.11.2025 → 21.11.2025

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

Fields of science

102 Computer Sciences

JKU Focus areas

Digital Transformation

Access to Document

10.1145/3770501.3770529

Cite this

Azadi, B., Anzengruber-Tanase, B., Sopidis, G., Haslgrübler, M., & Ferscha, A. (2025). Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI. In S. Nastic, F. Michahelles, S. Ristov, P. Dazzi, & F. Wolling (Eds.), IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025 (1 ed., pp. 237-244). Association for Computing Machinery, Inc. https://doi.org/10.1145/3770501.3770529

Azadi, Behrooz ; Anzengruber-Tanase, Bernhard ; Sopidis, Georgios et al. / Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI. IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025. editor / Stefan Nastic ; Florian Michahelles ; Sashko Ristov ; Patrizio Dazzi ; Florian Wolling. 1. ed. Association for Computing Machinery, Inc, 2025. pp. 237-244

@inproceedings{5da6d590399d4c128314044ba3e25774,

title = "Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI",

keywords = "EmbeddedAI, Energy Efficient IoT, Neuromorphic Hardware, Spiking Neural Networks",

author = "Behrooz Azadi and Bernhard Anzengruber-Tanase and Georgios Sopidis and Michael Haslgr{\"u}bler and Alois Ferscha",

note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 15th International Conference on the Internet of Things, IoT 2025 ; Conference date: 18-11-2025 Through 21-11-2025",

year = "2025",

month = dec,

day = "12",

doi = "10.1145/3770501.3770529",

language = "English",

pages = "237--244",

editor = "Stefan Nastic and Florian Michahelles and Sashko Ristov and Patrizio Dazzi and Florian Wolling",

booktitle = "IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025",

publisher = "Association for Computing Machinery, Inc",

edition = "1",

}

Azadi, B, Anzengruber-Tanase, B, Sopidis, G, Haslgrübler, M & Ferscha, A 2025, Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI. in S Nastic, F Michahelles, S Ristov, P Dazzi & F Wolling (eds), IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025. 1 edn, Association for Computing Machinery, Inc, pp. 237-244, 15th International Conference on the Internet of Things, IoT 2025, Vienna, Austria, 18.11.2025. https://doi.org/10.1145/3770501.3770529

Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI. / Azadi, Behrooz; Anzengruber-Tanase, Bernhard; Sopidis, Georgios et al.
IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025. ed. / Stefan Nastic; Florian Michahelles; Sashko Ristov; Patrizio Dazzi; Florian Wolling. 1. ed. Association for Computing Machinery, Inc, 2025. p. 237-244.

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

TY - GEN

T1 - Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI

AU - Azadi, Behrooz

AU - Anzengruber-Tanase, Bernhard

AU - Sopidis, Georgios

AU - Haslgrübler, Michael

AU - Ferscha, Alois

PY - 2025/12/12

Y1 - 2025/12/12

KW - EmbeddedAI

KW - Energy Efficient IoT

KW - Neuromorphic Hardware

KW - Spiking Neural Networks

UR - https://www.scopus.com/pages/publications/105025589831

U2 - 10.1145/3770501.3770529

DO - 10.1145/3770501.3770529

M3 - Conference proceedings

AN - SCOPUS:105025589831

SP - 237

EP - 244

BT - IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025

A2 - Nastic, Stefan

A2 - Michahelles, Florian

A2 - Ristov, Sashko

A2 - Dazzi, Patrizio

A2 - Wolling, Florian

PB - Association for Computing Machinery, Inc

T2 - 15th International Conference on the Internet of Things, IoT 2025

Y2 - 18 November 2025 through 21 November 2025

ER -

Azadi B, Anzengruber-Tanase B, Sopidis G, Haslgrübler M, Ferscha A. Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI. In Nastic S, Michahelles F, Ristov S, Dazzi P, Wolling F, editors, IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025. 1 ed. Association for Computing Machinery, Inc. 2025. p. 237-244 doi: 10.1145/3770501.3770529

Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI

Conference

UN SDGs

Fields of science

JKU Focus areas

Access to Document

Other files and links

Pro²Future II: Pro²Future II - Cognitive and Sustainable Products and Production Systems of the Future

Streaming AI - Föderierte Geräte-AI für die Digitale Transformation in der Industrie

Pro2Future - Products and Production Systems of the Future

Cite this

Towards an Energy-Efficient and Sustainable IIoT using Embedded Neuromorphic AI

Conference

UN SDGs

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

Pro²Future II: Pro²Future II - Cognitive and Sustainable Products and Production Systems of the Future

Streaming AI - Föderierte Geräte-AI für die Digitale Transformation in der Industrie

Pro2Future - Products and Production Systems of the Future

Cite this