The first edition of the DLIoT Workshop aims at covering state of the art and advancements in technologies, methodologies, and applications for DL (Deep Learning) and IoT (Internet of Things). It encourages the exchange of research knowledge and findings on the design and investigation of DL and IoT.
Topics of interest include, but are not limited to :
- Modeling, Design, Implementation, and Simulation of IoT Systems
- IoT and Cyber–Physical Systems
- Architectures, Methodologies, and Infrastructures for IoT Systems
- Big Data Analytics and Ambient Intelligence
- Consciousness, Awareness, and Artificial Intelligence in the IoT
- DL and IoT
- Recent trends and advances in DL-based IoT
- DL architecture for IoT security
- DL experiments, test-beds and prototyping systems for IoT security
- Context-Aware DL-based approaches for IoT
- Activity recognition in a smart home/city using DL
Original work must be submitted that is not published or under submission elsewhere. Contributions may be submitted in one of the following forms:
- Demos and Posters (1-2 pages).
Technical demonstrations (demos) and posters showing/ presenting innovative and original research are solicited. Demos and posters should describe original work in progress through 1 to 2 pages. Contributions should be submitted in PDF format, using the IEEE conference publishing template either in LaTeX or Word (http://www.ieee.org/conferences_events/conferences/publishing/templates.html), via the easychair workshop submission website: https://easychair.org/conferences/?conf=citcs2019.
Review Process and Publication
The submissions will be peer reviewed by at least two members of the program committee. The authors of accepted Papers will have to improve their paper based on reviewers’ comments and will be asked to send a camera-ready version of their manuscripts. At least one author of each accepted work has to register, and present his work. Accepted papers will be part of the DLIoT workshop proceedings.
- Dr. Ouarda Zedadra
- Dr. Karima Benhamza