IoT technologies have sprung up to collect data from anything you can imagine, from the status of the fan in a building's air conditioning unit to the noise level of the lathe on a factory floor. Businesses have sprung up turning that data into insights, and those insights into actions that drive value. For example, monitoring the sensors in the buildings on the Microsoft Puget Sound campus, and in the equipment attached to those buildings, has helped Microsoft reduce electrical consumption by over 20 percent. Generally speaking, securely connecting sensors to a cloud-based system with analytics and dashboards is a recipe for improving operations and the environment.
There are two primary ways sensors can connect to the cloud-based system. The most common way is for some separate application to query the sensor for the data, either directly from the cloud or using a on-premises gateway to query the sensor and push the data to the cloud. The other way is for a sensor with more compute power to create a direct connection to the cloud and push the data. Which of these methods is used depends upon the capabilities of the sensor, and the enterprise architecture into which the data is to be pumped. Two concerns that are top of mind with either of these methods are the cost-performance and the security of the data.
Consider the common scenario of monitoring the quality of the air inside or outside of buildings. It is important for understanding the environment and for enabling building owners to provide a healthier place for people to live and work. Sensors are available on the market which measure the levels of harmful chemicals and particles in the air, and the task for the enterprise is to select a sensor and how to get those readings into a centralized system or dashboard that allows the enterprise to take whatever actions are appropriate based upon the levels detected.
Most of the existing air quality sensors are standalone devices that can only respond to queries. The disadvantage of this method in the context of a large enterprise monitoring environment is that it requires a separate application (a gateway) to issue those queries and forward the data. This introduces additional cost and management effort, as well as potentially increasing security risks if the gateway needs to be accessed remotely (for example over RDP). A company by the name of Sysinno has an alternative to this, with an air quality sensor that can directly and securely connect to the cloud without the need of a local gateway using an onboard Azure Sphere chip from Microsoft. The onboard Azure Sphere thus reduces operating cost and complexity, and it does so in a highly secure manner.
We've written a whitepaper to show how to build an end-to-end solution using the Sysinno iAeris air quality sensor and a number of Azure IoT elements. In addition to showing how to configure the Sysinno detector to send data to Azure IoT Hub, the paper shows how to write an Azure function to send the data to SQL Server, and how to create Power BI and Time Series Insights (TSI) dashboards to display real-time and historical data. At this point, the air quality data could be consumed by any enterprise monitoring system, and furthermore be accessed by a tool such as Dynamics 365 Field Service for generating maintenance work orders or building-wide alerts to occupants. More broadly, the whitepaper shows how to easily build an end-to-end workflow for capturing, storing, and displaying certain types of IoT data. You could use the code shown to display room temperatures, occupancy, noise levels, traffic, or almost any other data for which you have a sensor.
To read the article and see the code, please follow this link to the Sysinno website.