Khaled Boussetta
The visiting researcher must hold a PhD in measurement engineering and have at least 15 years of experience in research, academia, and industry. Their main areas of expertise must include measurement engineering, IoT, robotics, and electrical/electronic systems. We are particularly interested in IoT metrology and digital calibration, and in direct contributions to emerging standards for reliable IoT measurements, an essential field for Industry 4.0 and smart systems. Expertise in ISO 17025 accreditation for laboratories would be an advantage.
UNIVERSITE PARIS 13
Enhancing the Reliability and Energy Efficiency of Medical IoT Networks: A Joint Optimization of Data Aggregation and LoRaWAN Link Parameters for Scalable Patient Monitoring. Main Research Goal: To design and validate a novel, integrated framework that simultaneously optimizes data aggregation strategies and LoRaWAN communication parameters (such as spreading factor, bandwidth, and transmission power) to significantly enhance the reliability, energy efficiency, and scalability of Medical Internet of Things (MIoT) networks for continuous patient monitoring. This overarching goal can be broken down into several key, interconnected objectives: 1. Develop a Joint Optimization Model: To create a mathematical or computational model that does not treat data aggregation and communication link settings as separate problems, but rather optimizes them in tandem. The model's objective function will aim to minimize energy consumption while meeting strict reliability (e.g., Packet Delivery Ratio) and latency constraints required for medical data. 2. Enhance Network Reliability for Critical Data: To ensure a high probability of successful data transmission from patient-worn sensors to the network server, which is non-negotiable in a medical context where data loss could impact patient safety. 3. Maximize Energy Efficiency: To drastically extend the battery life of MIoT sensor devices. This is crucial for long-term, unobtrusive patient monitoring, improving patient comfort, and reducing maintenance costs. 4. Ensure Scalability: To create a solution that performs robustly as the number of monitored patients (network nodes) within a hospital ward or healthcare facility increases, preventing network congestion and collapse. 5. Validate with Medical Use-Cases: To test and evaluate the proposed framework using realistic medical monitoring scenarios (e.g., vital signs transmission like ECG, SpO2, blood pressure) to prove its practical applicability and performance gains over existing methods.
This research offer provides a robust, synergistic environment critical for addressing the complex, multi-objective optimization challenge of the proposed project. The host institution offers resources directly applicable to the project: Access to a LoRaWAN test bed dedicated to experimental research. Specialized MIoT/health data: availability of simulated data traces from continuous monitoring applications, providing the information needed to train and validate optimization models. Interdisciplinary expertise: Wireless networks and IoT protocols: for mastering LoRaWAN link parameters and aggregation functions. Optimization: for developing the integrated framework and solving the joint optimization problem. Expected benefits for the visiting researcher: -In-depth technical expertise: the invited researcher will gain practical expertise in joint multi-objective optimization using real-world wireless network constraints. -Potential for high-impact publication: Successful validation of the integrated optimization framework is expected to yield results that can be published in a leading conference or peer-reviewed journal in the fields of wireless communications or MIoT. -Professional specialization: The project offers unique specialization in IoT reliability and efficiency in the healthcare field. Benefits and expected results for the host institution -Validation of the integrated framework: a fully validated software framework that simultaneously optimizes LoRaWAN link parameters and data aggregation functions, thereby proving the feasibility of the project's central research hypothesis. -Quantitative performance metrics: Concrete data and metrics quantifying achievable gains in energy efficiency (e.g., extended battery life) and reliability (e.g., packet delivery rates, reduced latency) in various realistic MIoT load scenarios. -Research visibility: Accelerating results will strengthen the institution's position in the competitive field of sustainable and reliable wireless networks for critical applications.
The maximum possible
The host institution has a long and solid tradition of welcoming visiting researchers. The inter-university collaboration that will be carried out with this invitation will be positioned within the framework of a bilateral cooperation project currently underway, PHC GILIBERT entitled “Monitoring metrological data using low-cost IoT measuring devices in indoor environments,” funded by Campus France and the Lithuanian Academy of Sciences. This ongoing project ensures that the proposed collaboration will be based on concrete and immediate scientific activities. It ensures the continuity and synergy of the project, as the research stay will be used to advance the common objectives of this project, accelerating results and joint publications in the field of IoT metrology.