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Professur Mess- und Sensortechnik
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Professur Mess- und Sensortechnik 
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Mahdi Mnif
Telefon:
Raum: Reichenhainer Straße 70, Weinholdbau: W283
E-Mail:

Expertise

  • Edge Computing Analytics
  • Tiny Machine Learning (TinyML) for Resource-Constrained Devices
  • Embedded Systems

Research interest

  • Optimizing Edge Computing Workloads
  • Energy-Efficient TinyML Models
  • Edge Analytics for IoT Applications
  • Real-Time Analytics on Edge Devices
  • Human-Machine Interaction at the Edge
  • Security and Privacy in Edge Analytics
  • Edge-to-Cloud Integration
Publikationen: 2

2024

Combinative model compression approach for enhancing 1D CNN efficiency for EIT-based Hand Gesture Recognition on IoT edge devices
Autoren: Mnif, M.; Sahnoun, S.; Saad, Y. B.; Fakhfakh, A.; Kanoun, O.
Quelle: In: Internet of Things. - Elsevier BV. - Volume 28. 2024, 101403
| DOI: 10.1016/j.iot.2024.101403
Erscheinungsjahr: 2024
ISBN/ ISSN: Online ISSN: 2542-6605 ; Print ISSN: 2543-1536

2022

Design of a Wearable Multi-Sensor Node for Human Movement Identification based on RSSI Measurements
Autoren: Mnif, M.; Ben Atitallah, B.; El Houssaini, D.; Sahnoun, S.; Fakhfakh, A.; Kanoun, O.
Quelle: 2022 19th International Multi-Conference on Systems, Signals & Devices (SSD), 06-10 Mai 2022, Djelfa, Algeria, pp. 857-863. - IEEE, 2022
| DOI: 10.1109/ssd54932.2022.9955978
Erscheinungsjahr: 2022
ISBN/ ISSN: Electronic ISBN:978-1-6654-7108-4 ; USB ISBN:978-1-6654-7107-7 Print on Demand(PoD) ISBN:978-1-6654-7109-1 ; Electronic ISSN: 2474-0446 Print on Demand(PoD) ISSN: 2474-0438
Journal Articles (peer-reviewed):1
Conference Papers (peer-reviewed):1