[AISWorld] CfP: AIoT 23[EXTENDED DEADLINE JULY 29], The First International Workshop on the Integration between Distributed Machine Learning and the Internet of Things.

[Fabio Busacca]

**Apologies for cross-posting**
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*The First International Workshop on the Integration between Distributed 
Machine Learning and the Internet of Things (AIoT)
October 23, 2023, Washington, USA
In conjunction with ACM MobiHoc 2023
Workshop Website: https://sites.google.com/view/aiot2023/home
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*Call for Papers*

Distributed and federated learning are nowadays popular techniques, as 
they promise to minimize the amount of unnecessary data streamed for 
processing and to move decisions closer to the data sources thus 
enabling faster, ideally real-time analytics. Moreover, the usage of 
distributed and federated learning techniques reduces the security risks 
associated with moving data and sustains energy-efficient total execution.

The integration between Distributed/Federated Learning mechanisms and 
the Internet of Things poses a series of whole new challenges, such as 
compression of models to be transmitted over unreliable channels, 
optimization of the network lifetime, management of the scarce 
computation, communication and storage resources, to name a few.

AIoT, the First International Workshop on the Integration between 
Distributed Machine Learning and the Internet of Things,  is 
specifically meant to gather new ideas, contributions, and experiences 
on the integration of Distributed and Federated Machine Learning with 
long-range IoT systems. The workshop solicits original papers dealing 
with the open challenges in the integration between 
Distributed/Federated Learning and IoT, including theoretical works and 
practical experiences over emulated and/or real testbeds. Contributions 
on the optimization of Machine and Deep Learning over embedded IoT 
devices are also welcome.

Topics include, but are not limited to:

  * Efficient Machine Learning in the IoT
  * Hardware for Machine Learning and Deep Learning in the IoT
  * Network Layer technologies to support Machine Learning in the IoT
  * Protocols to support Distributed Machine Learning in the IoT
  * Edge computing and IoT for distributed/federated learning
  * Experimental validation of distributed machine learning for IoT
  * Testbeds and tools for distributed machine learning in IoT
  * Privacy-preserving data sharing and aggregation in
    distributed/federated learning
  * Datasets and applications of distributed/federated learning in IoT
    (eg. spectrum sensing, healthcare, smart cities, and transportation)
  * Scalability and performance issues in IoT and distributed/federated
    learning
  * Emerging trends, challenges, and future directions in IoT and
    distributed/federated learning


*Important Dates*

  * Paper submission: July 12, 2023 July 29, 2023 (11:59pm US Eastern Time)
  * Acceptance notification: August 5, 2023
  * Camera ready and registration: August 26, 2023
  * Workshop date: October 23, 2023


*Submission Instructions*

Papers should be submitted via the HotCRP submissing website 
(https://aiot23.hotcrp.com/).

Submissions must be original, unpublished work, and not currently under 
consideration elsewhere. Papers should not exceed 6 pages (US letter 
size) double column including figures, tables, and references in 
standard ACM format. Papers must be submitted electronically in 
printable PDF form. Templates for the standard ACM format can be found 
at this link: 
http://www.acm.org/publications/article-templates/proceedings-template.html 
. If you are using LaTeX, please refer to the sample file 
“sample-sigconf.tex” after you download the .zip templates file and 
unzip it. Note that the document class “\documentclass[sigconf]{acmart}” 
should be used. No changes to margins, spacing, or font sizes are 
allowed from those specified by the style files. Papers violating the 
formatting guidelines will be returned without review.

All submissions will be reviewed using a single-blind review process. 
The identity of referees will not be revealed to authors, but author can 
keep their names on the submitted papers, on figures, bibliography, etc.


*Dual Submission Policy*

Accepted papers will appear in the conference proceedings published by 
the ACM. Warning: It is ACM policy not to allow double submissions, 
where the same paper is submitted to more than one conference/journal 
concurrently. Any double submissions detected will be immediately 
rejected from all conferences/journals involved.


*Workshop chairs*

  * Fabio Busacca (University of Catania)
  * Tony Quek (Singapore University of Technology and Design)
  * Ivan Seskar (Rutgers University)
  * Ilenia Tinnirello (University of Palermo)


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