Real-time IoT platform for smart environmental monitoring : a case study of Rakkaranta Resort
Hlaing, Ye Thu (2025)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025060621095
https://urn.fi/URN:NBN:fi:amk-2025060621095
Tiivistelmä
This thesis presented the design architecture and implementation of an Internet of Things (IoT) analytics dashboard for Rakkaranta Resort, which monitors environmental metrics and enhances the overall customer experience. The project integrated a production-level DevSecOps pipeline for the iterative, secure, and scalable software development and deployment life cycle.
An integrated methodological approach was adopted, combining system architecture, software design patterns, and prototyping. The system was developed on Azure cloud infrastructure integrated with IoT sensor networks to collect real-time environmental data, such as temperature, humidity, and water level. Data acquisition was managed via the MQTT messaging protocol and Telegraf agent, with time-series data stored in the InfluxDB database. The backend was developed using a Node.js architecture, while the frontend leverages the Next.js framework for server-side rendering.
The DevSecOps pipeline was composed of vulnerability scanners and SonarCloud code quality checking, ensuring security compliance and maintainable code. The pipeline was built using Docker, GitHub Actions, and Azure Container Registry. This custom IoT application tailored to the Finnish Resort scenario can significantly facilitate both development and operational workflows. Future recommendations include the physical integration of sensor hardware and role-based authentication between guests and staff.
An integrated methodological approach was adopted, combining system architecture, software design patterns, and prototyping. The system was developed on Azure cloud infrastructure integrated with IoT sensor networks to collect real-time environmental data, such as temperature, humidity, and water level. Data acquisition was managed via the MQTT messaging protocol and Telegraf agent, with time-series data stored in the InfluxDB database. The backend was developed using a Node.js architecture, while the frontend leverages the Next.js framework for server-side rendering.
The DevSecOps pipeline was composed of vulnerability scanners and SonarCloud code quality checking, ensuring security compliance and maintainable code. The pipeline was built using Docker, GitHub Actions, and Azure Container Registry. This custom IoT application tailored to the Finnish Resort scenario can significantly facilitate both development and operational workflows. Future recommendations include the physical integration of sensor hardware and role-based authentication between guests and staff.