# Smartwatch-Based Monitoring and Alert System for Factory Operators Using Public Cloud Services
## 3 Materials and Methods
### The System Architecture
A modern and intuitive design, along with the way user interactions are handled with the interface, contributes to a pleasant and efficient user experience, reducing the learning curve for new users. * **Flexibility**: The modular architecture and the use of current technologies allow for easy integration of new functionalities and rapid adaptation to changing requirements. Updates can be implemented and distributed without affecting system availability or performance, providing great flexibility in the ongoing evolution of system components. Our proposed architecture was designed after carefully assessing other solutions already present in the literature. Unfortunately, existing solutions focus more on monitoring workers in terms of their wellbeing or safety, which is not the scope of our work, as we are more focused on the human-to-human interaction and the monitoring of activity. Taking that into consideration, we have performed a comparative analysis of similar smartwatch-based monitoring systems in industrial environments, highlighting their architectures and the advantages of our proposed system in Table 2: \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Study** & **Scope of Usage** & **Architecture** & **Advantages of Our Proposed Solution vs. the Study Solution** \\ \hline \hline
[21] & Utilizes wearable sensors and cloud computing to monitor worker health and mitigate risks in industrial settings. & Implements a three-layer cloud architecture (Data Generation, Processing, and Decision-Making). Data is collected from sensors, pre-processed at the fog layer, and sent to the cloud for risk analysis. & Although this system is cloud-based and primarily centered on health monitoring, our solution offers a wider range of industrial functionalities, such as task management, work hour tracking, and secure authentication. By leveraging AWS Lambda and API Gateway, our approach enables faster, event-driven processing while minimizing infrastructure complexity compared to their multi-layered cloud framework. & Our cloud-driven approach, utilizing AWS Lambda, Cognito, and DynamoDB, ensures scalability, automation, and secure authentication, overcoming limitations related to device storage and processing. In contrast to the system reviewed, which focuses solely on notifications, our solution facilitates industrial workflow automation, data analytics, and real-time collaboration through AWS API Gateway and Firebase Cloud Messaging. & While this system uses cloud technology for data storage and processing, it relies on edge computing for real-time processing, limiting scalability. Our cloud-based architecture enables seamless scaling, real-time authentication via AWS Cognito, and broader industrial applications beyond stress detection, such as task management and attendance tracking. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: A comparative analysis of similar smartwatch-based monitoring systems in industrial environments. Our proposed system is a cloud-integrated notifying, monitoring and task management solution tailored for factory environments. It utilizes a server, which can also be deployed in the cloud, alongside AWS Lambda for event-driven processing, AWS Cognito for secure authentication, DynamoDB for scalable data storage, and Firebase Cloud Messaging for real-time notifications. This architecture eliminates factory-side infrastructure dependencies, ensuring cost efficiency, scalability, and seamless synchronization between a web application and a smartwatch application. By leveraging a server and serverless components, the system enables real-time data processing, automated task tracking, work hours recording, and enhanced communication, making it a scalable solution for industrial workflow automation.