Salvatore Tedesco
University College Cork, University of Salento, National University of Ireland
Papers
7
Total Citations
390
H-Index
6
About
Salvatore Tedesco is a leading researcher at the intersection of sensing technologies, robotics, and Industry 4.0, whose work has fundamentally advanced how machines perceive and interact with their environments. His most influential contribution is a landmark systematic review on motion capture (MoCap) technology in industrial applications, which has garnered 292 citations and serves as a foundational reference for integrating visual cameras and inertial measurement units into smart manufacturing processes. Tedesco has also made pioneering contributions to RFID systems, developing customized ultra-high frequency tags and reader antennas that enable reliable mobile robot navigation—work that has accumulated over 80 citations across multiple publications. More recently, he has broken new ground by applying deep learning regression models to chipless RFID sensor tags, achieving robust detection of identification and sensor data for the first time. His innovative automated data acquisition methodology, which pairs a Raspberry Pi with a robotic arm, improved measurement efficiency by 98%. Tedesco’s research also extends to wearable human-machine interfaces, including a glove-like device for Industry 4.0 control systems. Through his work at Tyndall National Institute, he continues to shape the future of intelligent sensing and automation.
Research Focus
Key Achievements
Top Papers
- 1Motion Capture Technology in Industrial Applications: A Systematic Review292 citations · 2020
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- 4PLATFORM-ROBUST PASSIVE UHF RFID TAGS: A CASE-STUDY IN ROBOTICS16 citations · 2012
- 5On the use of UHF RFID antenna systems customized for robotic applications13 citations · 2012
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