More Conference Papers
Integrating Deep Learning Models for QoS Optimization in IoT Using the oneM2M Platform
A. Zyane, J. Et-Tousy
FiCloud 2025 — 12th International Conference on Future Internet of Things and Cloud
Istanbul, Türkiye
This work investigates deep-learning models for QoS optimization on the oneM2M platform. It evaluates their ability to recognize service-quality states from network and resource measurements and to support intelligent adaptation in IoT environments.
Data-Driven Optimization of IoT-Monitored Agricultural Fleet Logistics: Case Study of COPAG Cooperative
J. Et-Tousy, A. Zyane, H. Jamiri
LOGISTIQUA 2025 — 16th International Conference on Logistics and Supply Chain Management
Casablanca, Morocco
This study uses IoT monitoring data to optimize agricultural fleet logistics in a case study involving the COPAG cooperative. The proposed analysis supports improved routing, resource allocation, operational visibility, and transport performance.
Machine Learning and Virtualization Approach for Detecting DDoS Attacks in oneM2M IoT Standard with QoS Impact Analysis
J. Et-Tousy, A. Zyane
AI2SD 2025 — 7th International Conference on Advanced Intelligent Systems for Sustainable Development
Tangier, Morocco
This paper combines machine learning and virtualization to detect DDoS attacks in oneM2M IoT environments. It also analyzes how attacks and mitigation mechanisms affect QoS indicators such as latency, success rate, CPU usage, and memory consumption.
oneM2M-Based Adaptive Loss Recovery Mechanisms for Enhancing Scalability and QoS in IoT Networks
S. Abourriche, J. Et-Tousy, A. Zyane, A. Ghammaz
IRASET 2025 — 5th International Conference on Innovative Research in Applied Science, Engineering and Technology
Fez, Morocco
This work proposes adaptive loss-recovery mechanisms for oneM2M-based IoT networks. It compares recovery behavior under changing traffic conditions and evaluates improvements in scalability, reliability, and quality of service.
A TimeGAN Approach for Restoring 12-Lead ECG from Single-Lead Data
J. Et-Tousy, S. Et-Tousy, S. Ait El Aouad, A. Zyane
DATA 2025 — 6th International Conference on Digital Age & Technological Advances for Sustainable Development
Tangier, Morocco
This paper applies TimeGAN to reconstruct multi-lead electrocardiogram signals from single-lead input. The generative approach learns temporal dependencies in ECG data to produce realistic 12-lead representations for downstream clinical analysis.
A Comparative Study of Loss Recovery Mechanisms Within HTTP and MQTT for QoS and Scalability in IoT Using the oneM2M Standard
J. Et-Tousy, S. Abourriche, A. Zyane, A. Ghammaz
COCIA 2025 — 3rd International Conference on Connected Objects and Artificial Intelligence
Casablanca, Morocco
This paper compares loss-recovery mechanisms in HTTP and MQTT within oneM2M IoT deployments. The experiments analyze their effects on QoS, message reliability, resource utilization, and scalability under varying traffic and loss conditions.
A Machine Learning Approach for DDoS Attack Detection in oneM2M Architecture: Impact on Quality of Service Parameters
J. Et-Tousy, H. Jamiri, A. Zyane
NISS 2025 — 8th International Conference on Networking, Intelligent Systems and Security
Tangier, Morocco
This paper presents a machine-learning approach for detecting DDoS attacks in a oneM2M architecture. It studies attack impact on latency, success rate, CPU, and memory, and integrates detection with adaptive QoS monitoring.
Automated QoS Enhancement in oneM2M: Traffic-Oriented Approach for MQTT and HTTP Based on IoT SLA Variations
J. Et-Tousy, A. Zyane
ICACTCE 2024 — 4th International Conference on Advances in Communication Technology and Computer Engineering
Marrakech, Morocco
This paper proposes a traffic-oriented mechanism for automated QoS enhancement in oneM2M systems using MQTT and HTTP. The method adapts protocol and traffic-management decisions according to variations in IoT service-level-agreement requirements.
Enhanced 12-Lead ECG Reconstruction from Single-Lead Data Using WaveNet
J. Et-Tousy, S. Et-Tousy, S. Ait El Aouad, A. Zyane
MAIH 2024 — International Conference on Mobility, Artificial Intelligence and Health
Marrakech, Morocco
This work investigates WaveNet-based reconstruction of a 12-lead electrocardiogram from single-lead data. The model captures temporal signal characteristics to generate additional leads and support more accessible cardiac monitoring.
Integration of MQTT and CoAP Protocols in oneM2M for IoT Applications
J. Et-Tousy, A. Zyane
ICAISE 2024 — 6th International Conference on Artificial Intelligence and Smart Environment
Errachidia, Morocco
This paper studies the integration of MQTT and CoAP protocols into oneM2M for IoT applications. It evaluates protocol behavior and their suitability for communication scenarios with different latency, reliability, and resource constraints.