Now 3388 visitors
Today:0 Yesterday:0
Total: 136728 212S 50P 5R
2026-10-21, Week 43
Member Login
TACT Journal Homepage
Call for Paper
Committee
Find My Paper
Author Homepage
Statistics & History
Welcome Message
Paper Procedure
FAQ
Paper Archives
Outstanding Papers
Program & Proceedings
Presentation Platform
Hotel & Travel Info
Photo Gallery
Scheduler Login
Seminar
Archives Login
Sponsors


















Online Q&A Session
Paper Number Author:
Paper Title
Keyword
Q&A Number **Select your question number !!
Questioner eMail:
Question
Answer
by
Author
Save Q&A

* Edit or answer any Q&A by selecting Q&A number Hyper Link below + Write button (Save)
ICACT20250032 Question.1
Questioner: jianms@nfu.edu.tw    2025-02-14 오후 3:25:30 		ICACT20250032 Answer.1
Answer by Auhor mamadouba92@gmail.com   2025-02-14 오후 3:25:30
Chrome Click!!
since the real time data is desired for remote health monitoring, could you comapring that using the wearable device for 4G or 5G LET communication for the health data transmission with your system? The Fledge-based system offers significant advantages over direct 4G/5G transmission from wearable devices: it enables local data pre-processing which reduces latency and network load, ensures better reliability through local storage and processing capabilities when connectivity issues arise, and provides enhanced multi-level security. However, a direct 4G/5G solution has the advantage of being simpler to deploy (without fog computing infrastructure), offers greater mobility, and direct cloud connectivity. The choice between these two approaches will therefore depend on the specific project needs - Fledge being more suitable for complex medical monitoring requiring local processing and enhanced security, while direct 4G/5G transmission is better suited for basic remote monitoring.
ICACT20250032 Question.2
Questioner: lcf1024@mail.ntou.edu.tw    2025-02-17 오전 1:20:49 		ICACT20250032 Answer.2
Answer by Auhor mamadouba92@gmail.com   2025-02-17 오전 1:20:49
Chrome Click!!
Please elaborate the technique features of the proposed Fledge platform in detail. The Fledge platform offers a hybrid Fog-Cloud architecture combining modular microservices (North/South Services, Orchestrator) for flexible real-time health data management. It integrates various sensors (temperature, ECG) and protocols (MQTT, OPC-UA, Modbus), with edge preprocessing (RMS/FFT filters) reducing latency by 40%. Secured by two-factor authentication, end-to-end encryption, and multi-level access control, it ensures interoperability through plugins (LoRa, Kafka) and real-time alerts (Slack). Its interface visualizes vital parameters (blood pressure, temperature) and allows for scalable extensibility, while integrating lightweight AI models at the edge and advanced analytics in the cloud, offering a robust solution for urban connected health challenges.
ICACT20250032 Question.3
Questioner: benjikone@yahoo.fr    2025-02-18 오전 1:59:06 		ICACT20250032 Answer.3
Answer by Auhor mamadouba92@gmail.com   2025-02-18 오전 1:59:06
Chrome Click!!
Your study highlights the advantages of using Fledge for real-time health data management. Given the growing role of AI in predictive healthcare, do you plan to integrate machine learning algorithms directly within the Fog layer to enhance anomaly detection and patient monitoring? What challenges do you foresee in such an integration? Thank you for this relevant question. Indeed, we plan to integrate machine learning algorithms at the Fog layer, in line with the research perspectives outlined in our paper. Implementing ML algorithms at the Fog level will enable immediate anomaly detection on vital data before transmission to the cloud, thus providing a faster response to critical situations. Furthermore, our study shows that Fledge already demonstrates excellent performance in edge data processing. Adding ML capabilities would further optimize this process by filtering relevant data. However, several challenges arise. Fog devices have limited computing resources compared to the cloud, which will require fine-tuned optimization to maintain the real-time performance demonstrated in our results. Monitoring critical parameters such as hypertension also requires a delicate balance between accuracy and processing speed. The integration of these new capabilities must be done while preserving the efficiency of our current microservices architecture. Our experimentation with real sensors provides a solid foundation for this evolution. We are considering a gradual approach, starting with targeted applications such as blood pressure anomaly detection before extending to more complex models. This approach aligns with our vision of a more efficient and patient-centered urban healthcare system, which is particularly crucial in the Senegalese context.
ICACT20250032 Question.4
Questioner: benjikone@yahoo.fr    2025-02-18 오전 2:03:14 		ICACT20250032 Answer.4
Answer by Auhor mamadouba92@gmail.com   2025-02-18 오전 2:03:14
Chrome Click!!
Your study demonstrates the efficiency of Fledge in reducing latency and securing real-time health data. However, interoperability with existing healthcare infrastructures remains a challenge. What strategies do you propose to ensure seamless integration of Fledge with hospital information systems (HIS) and electronic health records (EHR) while maintaining compliance with data protection regulations? Our study on the Fledge platform indeed reveals excellent performance in terms of latency reduction and health data security. Regarding interoperability with existing infrastructures, we propose several concrete strategies. First, Fledge’s microservices architecture, as illustrated in Figure 1 of our paper, offers remarkable flexibility through its North and South Service components. These services enable the integration of multiple communication protocols (OMF, GCP, OPC-UA, MQTT, HTTPS, Kafka), which are essential for interfacing with existing hospital systems. To ensure seamless integration with HIS and EHR systems, we recommend using standardized connectors at the North Service level. This approach, mentioned in our methodology section, allows secure data transmission to centralized systems while maintaining the benefits of edge processing. Regarding compliance with data protection regulations, our architecture already incorporates robust security mechanisms, including a multi-level authentication and authorization system. We propose enhancing these mechanisms by implementing end-to-end encryption and ensuring complete traceability of access to sensitive data. The experiment conducted in our mobile health laboratory demonstrates the viability of these strategies, particularly in home care settings, where interoperability and data protection are crucial for ensuring continuity of care.