Introduction and Research Topics
The RT se consacre aux défis des réseaux sans fil contraints et aux systèmes d’aide à la décision. His research aims to overcome technological barriers related to security, à l’efficacité énergétique et à la fiabilité des transmissions dans des environnements de plus en plus connectés et mobiles.
Resource Management and Decision Support
This first area of research applies primarily to the fields of smart buildings (smart buildings), e-health, and the Internet of Things (IoT). The team is developing :
Energy optimization: algorithmic solutions to reduce bandwidth consumption and extend the lifespan of sensor networks.
Cybersecurity: the integration of blockchain technology and detection mechanisms to counter malicious nodes and secure routing.
Artificial Intelligence: early detection algorithms for medical emergencies and big data processing solutions (Hadoop, Hive) for large-scale data collection
Autonomous communication systems
Focused on autonomous vehicles, drones (UAVs), and industrial networks, this area focuses on the efficiency and speed of data exchange :
Mobility and Routing: development of protocols for vehicular networks (VANET) based on predictive indicators of link failure.
Latency and Reliability: optimization of channel access techniques to ensure ultra-short transmission delays, which are essential for the safety of autonomous vehicles.
Distributed Perception and Digital Twin: designing communication solutions to improve vehicle control through enhanced perception of their environment, as well as creating digital simulations to assess the sustainability of urban mobility.
Team members
Permanent members
Research Activities
No news for now.
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Fed-DCSRW: a privacy-preserving, dynamic client selection framework for heterogeneous federated learning via roulette wheel mechanism (2026) ArticleCluster Computing
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International Journal of Computing and Digital Systems
No project for now.
Research and Doctoral studies
Approche d’Apprentissage fédéré mutli-objectif : vers une gestion de l’énergie efficiente et adaptative dans les bâtiments intelligents
Aline ABBOUD
Directeur(s) de thèse : Abdelhafid ABOUAISSA - Ahmad SHAHIN
Conception d’un regroupement intelligent et d’une consommation d’énergie équilibrée dans un réseau de capteurs à l’aide de l’apprentissage automatique
Mohammadreza KAGHAZGARAN
Directeur(s) de thèse : Abdelhafid ABOUAISSA - Jaafar GABER
De la multidiffusion dans les réseaux filaires au réseaux sans fil auto-mobiles
Benoît Hilt
Contact the team
Team Leader
Pr Abdelhafid ABOUAISSA
- Nous écrire
- Téléphone
RT Team
- IUT Colmar, 34 rue du Grillenbreit, 68000 Colmar
From the Colmar train station:
- Take Line 4 to the Grillenbreit stop.
From Highway A35:
- Take the D201 toward “Rue du Rhin”; the University of Technology is a 5-minute drive away.