## 3 Methodology
### Prototype Implementation and Testing of Proposed Model Using Real-Time Database
#### 3.6.1 Sensing of Real-Time Data through a Proposed Framework  
This node contains gadgets that capture user data both actively and passively. The user first enters their static profile information. The IOT devices offer active collection, in which the user monitors their levels of glucose, blood pressure (BP), and SPO2. The smartwatch and smartphone allow passive collection; they automatically track their steps, caloric outflow, activity type, and duration. Additionally, one can upload its physical reports through smartphones. We utilized an ESP32 based gateway that has built-in Bluetooth and Wi-Fi. Our gateway takes data from all three sensors ( Spo2, heartbeat, and blood pressure) and sends data to the AWS cloud using Wi-Fi, and receives data from our handheld device via Bluetooth. Our gateway provides independence to elderly users who do not use mobile phones. Signing into their respective mobile apps allows users to access this information. Figure 9 depicts the data gathered from each of the devices for a single volunteer individual \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**S.no** & **Layers (Type)** & **Filters** & **Output Shape** & **Param** \\ \hline
5. & Flattening & - & (None, None, 64) & 0 \\
6. & Bi-LSTM & - & (None, 128) & 66,048 \\
7. & Dropout & 50\% & (None, 128) & 0 \\
8. & Dense & & (None, 1) & 129 \\
9. & Classification & & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 6: _Cont._  
Figure 8: Data integration using real-time proposed framework. in this study. The various device sensors on Android smartphones and smartwatches are used to automatically collect and aggregate activity data and present the fitness history to consumers via the mobile application. The Google vendor API monitors movements, activities, and heart rates, as well as calculating the calories burnt and steps taken by using gyroscope and accelerometer sensors on smartphones and smartwatches, as well as an added heart rate sensor on smartwatches. In the proposed framework AWS server retrieves patient information from the mobile app as well as other mobile applications, e.g., Google Fit, every hour by connecting to the AWS cloud using Server Less API gateway (AWS), and it requires only one-time credential authentication. For authentication purposes, we required the OAuth 2.0 protocol to connect with the mobile application API [12]. It is standard protocol for connection with the various devices online, desktop, and mobile application authorization. This is the security protocol that is utilized for both Google services and API data interaction. A one-time authentication strategy was used to reduce the intr  
Figure 9: Visualization of real-time data through mobile application. medical professionals or caregivers to authenticate themselves with the online application every time they wish to monitor their data. When registering for the first time, the user connects to their mobile app account over the API to approve access to vendor cloud API privileges for the framework. The user was provided this one-time, two-step method through the mobile app, and they do not need to repeat it. If required, the user may include optional parameters such as skin fold thickness, number of pregnancies, and pre-existing medical concerns into the online application. The server obtains and stores the unique user authentication token for each vendor API. In order to keep the token continually updated, the server connects to the cloud API of the respective vendor and automatically renews the token before its expiry date. This is accomplished by configuring a server-side automated method to update tokens depending on the expiry settings of each vendor API token. AWS server then creates additional matrices depending on the other data that have been acquired, such as age, gender, height, and weight, among other things, that have been previously gathered. User data are aggregated on a daily basis by the server and ordered according to the time stamp of data collection, even if it occurs on the same day.