## 3 Materials and Methods
### Development Environment and Tools
#### 3.3.3 Data Processing Frameworks  
_Edge and Fog Computing: Raspberry Pi as a Gateway_  
The Monit4 Healthy system employs edge computing paradigms to enhance data processing efficiency and reduce latency. Raspberry Pi serves as the central gateway, collecting sensor data and transmitting it to cloud infrastructure via Wi-Fi. The Raspberry Pi 4 Model B, equipped with wireless LAN and Bluetooth connectivity, plays a pivotal role in health monitoring applications by aggregating sensor readings, performing preliminary data processing, and ensuring real-time monitoring. This setup enhances system scalability, efficiency, and responsiveness, thereby improving both the accuracy and accessibility of patient data. With low power consumption (~2.5 W during typical operation) and optimized data transmission, the Raspberry Pi 4 Model B ensures energy-efficient performance, making it well suited for continuous health monitoring scenarios. Its capability to process and filter data locally before transmission significantly reduces network congestion and minimizes latency [73]. _Cloud Computing for Monit4 Healthy System: ICIPRO IaaS_  
ICIPRO--a significant cloud-based initiative designed to modernize and improve public services in Romania by leveraging cloud computing technology--provides Infrastructure as a Service (IaaS), offering virtualized computing resources, storage, and network connectivity through its secure cloud infrastructure. The platform is built on high-performance hardware, including servers, routers, and firewalls, ensuring reliability and scalability for systems like the Monit4 Healthy system, which runs on a virtual machine (VM). ICIPRO provides high availability and load balancing, reducing downtime and improving system resiliency. VMs in this cloud run in a redundant data center environment, minimizing the risk of failure [74]. _Network Isolation and Security_  
ICIPRO implements Network Virtualization using Generic Routing Encapsulation, ensuring complete network isolation for the Monit4 Healthy system from other cloud tenants. A total of 10 Gbps of connectivity between hardware components provides low-latency and high-speed data transfers, essential for real-time health monitoring applications. Built-in firewall rules and virtual network segmentation enhance data security and prevent unauthorized access. ICIPRO integrates a System Center Data Protection Manager to offer continuous data backup and disaster recovery for critical health monitoring data [74]. Figure 6 shows the ICIPRO dashboard controlling a virtual machine running Ubuntu, along with a terminal window--a Command Line Interface (CLI) running a Django development server using the \"python3 manage.py runserver 0.0.0.0.0:8088\" command--showing both system resource utilization and real-time CLIs. This architecture enhances predictive diagnostics and enables timely medical interventions, optimizing patient outcomes in a digitally connected healthcare ecosystem [75]. In addition to technical measures, data privacy and regulatory compliance are essential aspects of the Monit4 Healthy system. The integration of cloud-based data transmission ensures low-latency, high-throughput, and encrypted data exchange, adhering to healthcare standards such as GDPR and, where applicable, HIPAA. Data privacy is maintained by implementing secure data transmission protocols, user authentication, and access control mechanisms within the system. The ICIPRO cloud infrastructure, where data are stored and processed, enforces strict security and privacy policies, including encrypted data transfer, controlled access, and secure storage, supporting compliance with GDPR and HIPAA principles related to health data confidentiality, integrity, and availability. In accordance with GDPR requirements, the system operates based on explicit informed consent from users, including healthcare professionals and patients, for data collection and processing.