## 2 Materials and Methods
### Method
#### 2.6.3 Device Installation and Configuration  
Once the appropriate devices have been selected, performing a correct installation and configuration is essential to guarantee proper operation in the IoMT system. For this, it is necessary to prepare the space where the devices will be installed, ensuring that it meets the temperature, humidity, and ventilation requirements essential for the correct operation of the equipment. The next step is to configure the network in which the devices will be connected, ensuring that it meets the necessary security and bandwidth requirements for the proper functioning of the IoMT system [29]. At the security level, the network is protected by implementing a firewall and a security protocol, such as WPA2. Next, it should be verified that the network has sufficient bandwidth to handle the data transfer from the selected devices. This work requires a speed of at least 50 Mbps to support the data collected by the devices [30]. Finally, the network has been configured to allow the connection of the selected devices. Each device must have a unique IP address on the network. In addition, privacy and network security settings must be configured to ensure that patient data are kept confidential and not accessible to unauthorized persons [31]. Once the network configuration is complete, the selected IoMT devices can connect and transmit data to the central system. For implementing IoMT systems, it is recommended to use a scalable and secure cloud architecture that allows for the storage, processing, and analysis of large volumes of data generated by connected medical devices. Table 3 presents the advantages and disadvantages of three private clouds that were analyzed for the development of the method, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Each option has advantages and disadvantages, so the best choice must be carefully evaluated based on the specific needs and requirements of the IoMT system to be implemented. In this proposal, a cloud data analysis platform architecture using GCP is used, as presented in Figure 4. Google Cloud IoT Core connects and manages IoMT devices in the cloud securely and efficiently. Cloud Pub/Sub allows for the transmission and processing of data from IoMT devices in real time. Cloud Dataflow transforms and processes the data in real time and sends it to BigQuery for storage and further analysis. BigQuery stores and analyzes large volumes of data generated by IoMT devices and allows for complex queries and data visualizations [32]. Google Data Studio is used to visualize and present the analyzed data. Cloud Storage stores the backup data and configuration files of IoMT devices. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Platform** & **Advantages** & **Disadvantages** \\ \hline \multirow{4}{*}{AWS} & Wide range of services, good & The steep learning curve, complexity in the configuration of some services, possibility of high costs if there is no proper management \\  & integration with IoT devices, scalability, high availability, flexibility in payment & Less a range of services than AWS, the possibility of high costs if there is no proper management \\  & model, and strong security & \\ \hline \multirow{4}{*}{GCP} & Good integration with IoT devices, a wide range of services, scalability, high availability, flexibility in payment & Lower adoption than AWS and Azure, steep learning curve, and the potential for high costs if not properly managed \\  & models, and strong security & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison chart of cloud platforms for the medical internet of things.