Inclusive and Human Centric Manufacturing. Development of Deep Learning Algorithms for Visual Recognition in Manufacturing Environments. Integration of Computer Vision with Human-Centric Analysis

Department

Department of Management and Production Engineering, Politecnico of Turin

Main research activities/topics/projects

The research will focus on developing intelligent systems to enhance operator inclusivity and productivity through automated visual recognition and performance evaluation, with emphasis on:

• Development of Deep Learning Algorithms for Visual Recognition in Manufacturing Environments: This research will involve designing and optimizing deep learning models, particularly Convolutional Neural Networks (CNNs), for processing and analyzing visual data captured from manufacturing processes. The aim is to automatically identify and classify objects, defects, and operational patterns in real-time, improving quality control and production efficiency.
• Integration of Computer Vision with Human-Centric Analysis: This area focuses on combining computer vision techniques with human operator monitoring, leveraging CNN-based algorithms to assess physical actions, gestures, and work-related movements. This will allow for a deeper understanding of operator behavior, task execution, and ergonomic conditions, particularly in neurodiverse-friendly environments.

The candidate will participate in advanced research to develop novel deep-learning techniques for real-time visual analysis and human interaction in manufacturing. 

Working language

English

Special entry requirements

Proficiency in deep learning (especially CNNs), computer vision, and real-time data processing. Experience with programming (Python, Java, or C), signal processing, and data analysis. Familiarity with AI-driven human-centric analysis, industrial IoT, and cloud computing. 

Duration in months (min-max)

Phd Sanswhich: 2-6