International Workshop on Behavioral Data-driven Futures
Bridging behavioral Insights, machine learning, and IoT
Machine Learning (ML) and the Internet of Things (IoT) play a central role in numerous technologies and applications, and their impact on our lives is set to continue evolving in the coming decades. ML and IoT are commonly employed to create computer systems that emulate human intelligence. A significant shift in the use of ML is the transition from a tool driven by human commands to a machine inference engine that derives new insights from vast amounts of data. However, one may often wonder how these systems can be fed with behavioral data.
The importance of behavioral data stems from its dynamic nature, allowing for the tracking of behavior evolution across various dimensions. It offers the opportunity to automate the activation of new strategies based on real-time actions performed by targeting entities. In the field of medicine, for instance, real-time behavioral data prove valuable in reaching healthcare professionals across multiple use cases, including introducing new devices or therapies to the market and influencing prescription decisions.
The BeDaF workshop aims to delve into the increasing significance of ML and IoT concepts within key applications and technologies that drive intelligent systems based on behavioral data. This session provides an interdisciplinary platform for researchers and developers to showcase the latest advancements in research, as well as prototypes or deployed systems across diverse domains such as medical diagnosis, intelligent decision-making, knowledge engineering, computer vision, and more. The specific objectives of this session are as follows:
- Develop a comprehensive understanding of behavioral data analysis techniques through insights shared by leading ML and IoT experts;
- Gain a thorough update on the latest applications of Internet of Behaviors and Internet of Things (IoB and IoT) application that facilitate the identification of individuals’ future behaviors;
- Explore the practical application of behavioral data across various industries;
- Witness the successful integration of ML approaches with IoT in decision-making processes driven by behavioral data.
In summary, the BeDaF workshop seeks to explore the growing synergy between ML, IoT, and behavioral data, highlighting technological advancements, use cases, and opportunities within these emerging domains.
Suggested topics include, but are not limited to:
- Social Computing, and Applications
- Computational models of social phenomena
- Social Behavior and Social network analysis
- Internet of Things in Agriculture
- Strategic IoT and IoB solutions for smart agriculture
- Multi-Agent systems and behavioral simulation
- Preventive Medicine and Public Health
- Patient Behavioral Analysis and Smart Healthcare
- Medical Behavioral Data Analysis
- E-learning behavior data
- Integrated Water resources management (IWRM)
- Food production and safety
Each submission should be at most 8 pages in total, including bibliography and well-marked appendices, and must follow the IEEE double columns publication format available at:
Paper submission will only be online via SITIS 2023 EasyChair submission system.
Only pdf files will be accepted. Submissions not meeting these guidelines risk rejection without consideration of their merits. All submitted papers will be carefully evaluated based on originality, significance, technical soundness, and clarity of expression by at least two reviewers and then will be checked for plagiarism and self-plagiarism by IEEE. The organizers will examine the reviews and make final paper selections.
All the papers accepted for the workshop will be included in the conference proceedings. The proceedings will be published by the IEEE Computer Society (pending approval) and referenced in the IEEE Xplore Digital Library, Scopus, DBLP and major indexes.
The proceedings of the previous editions of SITIS are available here.
At least one author of each accepted paper must register for the workshop. The workshop registration fees are determined by the SITIS organizers. Both in-presence and remote presentations are allowed. Further details are available here. A single registration for the workshop or the conference allows attending both events.
Abdelaziz EL Fazziki, Computer Science Department, Faculty of Sciences Semlalia, Cadi Ayyad University, Morocco
Hasna El Alaoui El Abdallaoui, Computer Science Department, Faculty of Sciences Semlalia, Cadi Ayyad University, Morocco
- Mohammed Sadgal, Cadi Ayyad University, Morocco
- Zahi Jarir, Cadi Ayyad University, Morocco
- Ernesto Damiani, Milan University, Italy
- Kokou Yetongon, Bourgogne University, France
- Djamel Benslimane, Lyon1 University, France
- Sadoq Benyahya, Tallinn University of Technology, Estonia
- Bellatrache Ladjel, Poitiers University, France
- Richard Chbeir, Pau et de l’Adour University, France
- Moussannif Hajar, Cadi Ayyad University, Morocco