Artificial Intelligence and Advanced Technologies for Next-Generation Sensors and Computer Vision

Artificial Intelligence and Advanced Technologies for Next-Generation Sensors and Computer Vision
Details
Research Project Number:
RP-NASS-2026-023
Academic Lead:
MINH LONG HOANG
Co-academic leads:
Deadline:
July 25, 2026
MINH LONG HOANG

Name: MINH LONG HOANG
Affiliation: University of Parma
E-Mail: minhlong.hoang@unipr.it 
Website: https://personale.unipr.it/en/ugovdocenti/person/241243 
Orcid: https://orcid.org/0000-0002-3622-4327
Research Interests: Microcontroller, Smart sensors, Sensor fusion, Signal processing, AI, Internet of Things.  

Research objectives:

This Research Project covers the following topics:

1. Applications for AI, Sensors and Computer Vision in various fields such as healthcare, automation and industry.
 
2. Novel AI models, algorithms, and learning paradigms that enhance sensing accuracy, perception robustness, data interpretation, and scene understanding.
 
3. Novel developments in next-generation sensor technologies, including multi-modal sensing, miniaturized and embedded sensing platforms, and emerging hardware innovations.
 
4. Interdisciplinary research on the integration of AI, sensing, and vision systems for real-world applications across domains such as autonomous systems, robotics, healthcare, smart manufacturing, transportation, security, and environmental monitoring.
 
5. Foster contributions that address challenges related to data fusion, uncertainty quantification, explainability, scalability, low-latency inference, energy efficiency, and system reliability.
 
6. Research bridging theory and practice, including benchmarks, real-world deployment, datasets, reproducible pipelines, and industry case studies

Keywords:

  • Sensors
  • AI
  • Computer Vision
  • Signal Processing
  • Advanced Technology

Expected Outcomes:

Academic: Peer-reviewed publications

Digital Technologies Research and Applications (DTRA)

DTRA Journal Cover
ISSN:
2754-5687
Frequency:
Quarterly
E-mail:
dtra@ukscip.com
Indexing: Scopus, Google Scholar, OpenAlex, OpenAIRE, Scilit

Publisher: UK Scientific Publishing Limited

Submit an Article

Note:

-  Manuscripts under this research project are intended for publication in the above journals.

-  Academic Lead, Co-AL, and potential contributors may choose the appropriate journal for submission according to the needs. When submitting, please select “Research Project”​ in the OJS (Open Journal Systems) backend.

- For any questions (e.g., paper submission details, process), please contact :
   Research Project Coordinator: Cecilia
   Email: cecilia@nassg.net