[AISWorld] Call for Participation - IEEE 18th International Conference on Intelligent Environments (IE 2022)

[Sergio Ilarri]

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  			Call for Participation

  IEEE 18th International Conference on Intelligent Environments (IE2022)

			June 20-23, 2022 - Biarritz, France
		
			In cooperation with IEEE Systems, Man, and Cybernetics Society

	        https://ie2022.iutbayonne.univ-pau.fr/
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Important News
~~~~~~~~~~~~~~
- Accepted papers list now online 
(https://ie2022.iutbayonne.univ-pau.fr/accepted-papers/)
- Registrations are now open 
(https://ie2022.iutbayonne.univ-pau.fr/registration/)
=> early bird deadline: *May 15, 2022*
- Hybrid mode (online/on-site)
=> We strongly encourage you to join the many participants who have 
already confirmed their presence on site to facilitate exchanges and 
moments of conviviality. In particular, we hope to meet on site 
participants from nearby countries.

Scope
~~~~~

Intelligent environments refer to physical spaces in which information 
and communication technologies are woven with sensing/acting 
technologies in order to create interacting spaces enhancing occupants’ 
experience. The ultimate objective of such environments is to provide 
services to occupants, enrich their activities but also to develop their 
awareness.

As in previous years, IE will host a dozen workshops and tutorials in 
the most current fields related to smart environments. Also, special 
sessions, demos, posters and an industrial forum will be organised as 
usual by the IE community.

Topics include but are not limited to:
- Advances in theories for the design, implementation, integration and 
evaluation of smart spaces,
- Novel architectures and middleware for the integration of devices, 
edges, and clouds
- Software facilities to develop, deploy, monitor, update applications 
for smart spaces,
- Interaction techniques using voice, gesture, eyes, etc. in smart spaces,
- Robotic technologies in smart spaces to assist human or to manage 
resources,
- Planning solutions to better use limited resources in smart spaces,
- Machine learning techniques for novel applications, including 
federated learning, few shot learning, etc.
- Solutions to deal with transversal properties including security,
- Privacy, availability, transparency, or explainability in smart spaces.
- Novel applications in smart homes, smart building, smart cities, smart 
plants and smart grid


Invited talks
~~~~~~~~~~~~~

Opportunistic Collaborative Learning in Pervasive Computing Applications
Christine Julien [ON-SITE, confirmed]

Smartphones, wearable devices, and other computational units that are 
ubiquitous in our environments are imbued with increasingly more complex 
sensing, computational, and communication capabilities. These devices 
can generate (and distribute) vast quantities of data that can be used 
to build sophisticated machine learning models for a variety of 
applications, e.g., classification and recommendation. Opportunistic 
collaborative learning (OppCL) is a framework for individual devices in 
pervasive computing environments to train a deep learning model that 
caters to the device’s personalized needs. In OppCL, each device 
maintains a local, personalized model. When the device encounters 
another device via peer-to-peer communication, it shares its model 
parameters and asks the neighbor to train the model using the neighbor’s 
local data. This talk will present the motivation and use cases behind 
the creation of OppCL and a basic model for collaboratively training 
personalized models using opportunistically available neighboring 
devices (and their data!). The talk will discuss multiple schemes for 
incorporating encountered model updates as well as techniques for 
handling heterogeneity in the pervasive computing environment, including 
bandwidth and latency constrained communication links as well as 
computationally constrained neighboring devices. The talk will also 
include presentations of practical implementations for OppCL in both 
large scale simulation and in real world devices. The talk will close 
with a look forward into open challenges and opportunities in employing 
OppCL to diverse pervasive computing applications.


Towards Distributed Intelligence in Future Edge Computing
Jiannong Cao [ON-LINE, confirmed]

The emerging advanced IoT applications in connected healthcare, 
industrial internet, multi-robot systems, and other areas demand higher 
intelligence of the connected devices, larger scale of the systems, and 
better decision-making leveraged by analyzing the data being 
continuously generated and the advancement of AI technologies. In this 
context, centralized cloud computing would face high data transmission 
cost, high response time, and data privacy issues. The edge cloud 
paradigm seeks to alleviate these inefficiencies by moving the 
computation and analytics tasks closer to the end devices. It 
facilitates the evolution of IoT from instrumentation and 
interconnection to distributed intelligence. This talk focuses on future 
collaborative edge computing where edge nodes share data and computation 
resources and perform tasks by leveraging distributed intelligence. It 
covers the major problems in distributed collaboration at the edge we 
are currently studying, namely collaborative task execution, distributed 
machine learning, and distributed autonomous cooperation. Solutions need 
to address the challenging issues such as distributed data sources, 
conflicting network flows, heterogeneous devices, consistency, and 
mutual influence during the training.



Reflections on trustworthy and ethical technology from a Human Computer 
Interaction perspective
Maria-Antonietta Grasso [ON-SITE, TBC]

The objective to help people flourish has​​ been a part of the agenda of 
the Human Computer Interaction community since its early days. Current 
concerns around the impacts of technology and its ethics make these 
early endeavours even more relevant and prominent​. The reasons are many 
and relate to issues of broad societal concern such as sustainability, 
work organisation and perpetration of social inequities. In this talk I 
will first discuss emerging attributes that help to assess a technology 
as trustworthy and ethical. I will then draw on some examples of 
projects we have carried out in our industrial lab to explain how we 
included a value orientation in our research and will propose some 
concrete methodologies we have found useful.



Program Chairs
~~~~~~~~~~~~~~
Song Guo, Hong-Kong PolyU, China
Philippe Lalanda, UGA, France

General Chairs
~~~~~~~~~~~~~~
Schahram Dustdar, TU Wien, Austria
François Portet, UGA, France

Local Chair
~~~~~~~~~~~
Philippe Roose, LIUPPA/E2S, University of Pau, France