International Workshop on Machine Learning and Internet of Things Based Intelligent Systems


Machine Learning (ML) and the Internet Of Things (IoT) are at the center of many technologies and applications and artificial intelligence-based systems will continue to revolutionize almost every aspect of our lives in the coming decades. Generally, ML and IoT are used to build computer systems that replicate human intelligence. The fundamental change in the use of ML is the transition from a human command-driven tool to a machine inference engine that learns new information from huge amounts of data. This change is extremely important because it results in the software being increasingly able to develop and refine its instructions to perform tasks without the need for a human being to provide decisions. This workshop aims to discuss how the concepts of ML and IOT have become increasingly important in some of the key applications and technologies that implement intelligent systems. It provides an interdisciplinary forum for researchers and developers to present the latest advances in research work as well as prototyped or fielded systems in different fields (medical diagnosis, intelligent decision making, Knowledge engineering, computer vision, etc.)

On the other hand, smart decision-making is a crucial, yet challenging mission in enterprise management. It is still made based on a reactive approach rather than on facts and proactive approaches. This is often due to underprovided data, the unknown correlation between data and goals, conflicting goals, and weak defined strategy. Enterprise success depends on fast and well-defined decisions taken by relevant policymakers and business actors in their specific areas. MIBIS workshop can be seen as a collection of decision support technologies and tools for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. From there to completely revolutionize decision support systems, traditional architectures are beginning to be affected, and new applications can be met: the use of unstructured data, sensor data, machine learning and crowdsourcing, huge data volumes to be managed with the enterprise information system integration. Intelligence has always been seen as a separate element of the information system of the company, but with Big Data, this is changing. The workshop welcomes high-quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of ML and IoT applications.

Suggested topics include, but are not limited to:

  • Intelligent Decision Support Systems
  • Intelligent Transport Systems
  • Precision Agriculture and Smart Water Resources Management
  • Machine Learning and Deep Learning-based Applications
  • Machine learning and decision support systems
  • Clinical decision support systems
  • Knowledge-based clinical decision support system
  • Real-time decision making, forecasting, and fraud detection using big data
  • Image Analysis and Computer Vision Applications
  • Management of big data in specific areas
  • Managing big data for information-driven business models
  • Methodologies for innovations to handle large data sets

Workshop Co-Chairs

Abdelaziz EL Fazziki, Cadi Ayyad University, Morocco
Hasna El Alaoui El Abdallaoui, Cadi Ayyad University, Morocco

Program Committee

  • 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