{"id":1126,"date":"2022-09-14T18:26:25","date_gmt":"2022-09-14T16:26:25","guid":{"rendered":"https:\/\/www.iberamia.org\/iberamia\/iberamia2022\/?page_id=1126"},"modified":"2022-10-18T14:16:03","modified_gmt":"2022-10-18T12:16:03","slug":"workshop-aii","status":"publish","type":"page","link":"https:\/\/www.iberamia.org\/iberamia\/iberamia2022\/workshop-aii\/","title":{"rendered":"Workshop \u00abArtificial Intelligence for Industry 4.0\u00bb"},"content":{"rendered":"

IBERAMIA 2022 WORKSHOP on<\/h2>\n

\u201cArtificial Intelligence for Industry 4.0\u201d<\/strong><\/h2>\n

Organized by CONCHA BIELZA, PhD -Full Professor at Universidad Polit\u00e9cnica de Madrid (Spain), and JAVIER DIAZ-ROZO, PhD -CTO at Aingura IIoT (Spain)<\/h3>\n

Submission Deadline: October 24 15<\/span>, 2022<\/strong><\/h5>\n
Cartagena de Indias, Colombia. November 23, 2022<\/strong><\/h5>\n
\n

The amount of industrial data generated by machine controllers, sensors, actuators, manufacturing systems, smart healthcare devices, etc. is growing exponentially, and AI-based systems able to transform this huge quantity of data into knowledge are pervading our daily lives and industrial companies. AI, cyber-physical systems, the Internet of Things and the physical environment all interact with each other to reach intended goals. AI systems can provide valuable actionable insights towards optimal decisions in problems such as diagnosis, prognosis, predictive maintenance, conditioning monitoring, assets health management, remaining useful life assessment, anomaly detection, etc. Consequences are, among others, to shorten design time, maximize uptime, productivity and efficiency of operations, reduce materials waste, improve production reuse, quality control.<\/p>\n

The workshop goals are bringing industry and academia together for sharing their insights to truly leverage AI for Industry 4.0. and witnessing how every industry may benefit from this revolution. Researchers, technology providers, practitioners of large companies or SMEs, and users are all welcome. Sectors such as aerospace, automation, automotive branch, chemistry, civil engineering, consumer services, cybersecurity, energy, finance, healthcare, information technologies, manufacturing and telecommunications can share theirexperience, discuss the latest solutions and innovation needs, gaps, opportunities and challenges. This wide view of AI and industry ecosystem fits the Iberamia spirit and fosters AI adoption.<\/p>\n

Submissions include methodological contributions and case stu dies of machine learning, deep learning (or AI in general) within the industrial domain. A non-exhaustive list of techniques and applications is:<\/p>\n

Techniques:<\/p>\n

\u2022 Big data analytics
\n\u2022 Cloud computing in Industry 4.0
\n\u2022 Challenges in implementation of AI for fully functional smart industries
\n\u2022 Data streams, concept drift and model updating
\n\u2022 Deep, supervised, unsupervised and reinforcement learning
\n\u2022 Edge computing embedded AI
\n\u2022 Model ensemble
\n\u2022 Explainable AI in industry
\n\u2022 Industrial Internet of things
\n\u2022 Soft computing for industry<\/p>\n

Applications:<\/p>\n

\u2022 Anomaly and novelty detection
\n\u2022 Advanced control systems
\n\u2022 Condition monitoring
\n\u2022 Energy management
\n\u2022 Fault diagnosis detection, isolation and identification
\n\u2022 Human Machine Interface
\n\u2022 Machine vision
\n\u2022 Machine-to-Machine communication
\n\u2022 Prognostics and health management
\n\u2022 Smart sensors and actuators<\/p>\n

Important dates and submission procedure:<\/strong><\/h5>\n