In the course IST 615, aptly named Cloud Management, I prepared a project that dealt with with using cloud services as a tool for internet connected home appliances. It allowed me an unique opportunity to work on a cloud platform for the task of data storage, machine learning and dashboard-ing
Throughout this project, I concentrated on developing an IoT prototype framework utilizing Azure Cloud Services. The goal was to create a functional IoT hub to which devices can connect to exchange data. Because I wanted to illustrate the operation of both sensors and switches in my model, effort was concentrated on adding monitoring tools such as data logging and dashboards to enable visualization and time-series analysis in future.
The objectives of the project were as follows
The device connects to the IoT Hub in the cloud to send and receive data.
Log any sensor data coming to Hub to have historical sensor data.
Perform analysis on the data stream.
Create a dashboard to track real-time data of device state and sensor data.
The technologies used to accomplish this project were as follows:
Azure IoT Hub, a cloud-based managed service that acts as a central message hub for IoT apps and the devices to which they are connected. You may connect millions of devices and their backend systems in a safe and secure manner. Almost any device with the right connection protocol can be connected to an IoT hub. Device-to-cloud telemetry, uploading files from devices, and request-reply techniques to control your devices from the cloud are all supported communications patterns. Monitoring is also supported by IoT Hub, which allows you to keep track of device creation, device connections, and device failures.
Azure Stream Analytics is a real-time analytics and complex event-processing engine designed to analyze and process large amounts of fast streaming data from multiple sources at the same time. Patterns and relationships can be identified in data extracted from a variety of input sources, including devices, sensors, clickstreams, social media feeds, and applications. These patterns can be used to initiate workflows and trigger actions such as creating alerts, feeding information to a reporting tool, or storing transformed data for later use.
Azure SQL Database is a fully managed platform as a service (PaaS) database engine that handles most database management activities without the need for user participation, such as upgrading, patching, backups, and monitoring.
Power BI is a collection of software services, apps, and connections that collaborate to generate coherent, visually engaging, and interactive insights from disparate data sources. The data was a hybrid of cloud-based and on-premises data. Power BI enabled me to quickly connect to data sources, view and locate what matters, and share it with whoever I wanted.
Since this undertaking was an individual effort, all parts of it were researched, programmed and executed by myself. It was
