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iWOAR 2026 : 11th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence

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Link: https://iwoar.org/2026/
 
When Sep 10, 2026 - Sep 11, 2026
Where Wiesbaden, Germany
Submission Deadline Jun 25, 2026
Notification Due Aug 1, 2026
Categories    artificial intelligence   human activity recognition   human computer interaction   machine learning
 

Call For Papers

iWOAR is an international workshop with a conference-like format, hosted by Hochschule RheinMain. This year's workshop is being held in Wiesbaden, Germany, on the Hochschule RheinMain campus. The workshop focuses on recognizing human and animal activities using artificial intelligence, with wearable and device-free sensors, as well as related technologies.

All scientific submissions undergo a single-blind peer-review process to ensure that high-quality content is published. Each submission typically receives 2-3 reviews. All submissions are discussed among the program committee members. The designated program committee chairs make the final decision on acceptance or rejection. We invite submissions that target (but are not limited to) the following topics and applications:

• Human Activity /Behavior/Wellbeing Recognition
• Animal Activity and Wellbeing/Welfare Recognition
• Wearable Sensing, Computing and Artificial Intelligence
• Device-free Sensing
• Sensing in Virtual, Mixed, and Augmented Reality
• Affective Computing
• Real-time Activity Recognition
• Human-Computer Interaction
• Human-Centered Intelligence
• Wireless Sensor Networks/IoT
• Context Awareness
• Assistive Technologies
• Active and Healthy Living
• Pervasive & Ubiquitous Computing
• Applications for (Mental) Health, Therapy and Rehabilitation
• Digital Health and Medical Technology
• Occupational Safety, Healthcare and Wellness
• Assisted Production
• Privacy and Ethical Considerations in Human/Animal Sensing

All submissions should follow the Springer LNCS format. Accepted submissions will be published in the iWOAR 2026 Proceedings online in the SpringerLink digital library.

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