The industrial revolution was a watershed period in human history. The shift from piecemeal, cottage-industry work to mechanized manufacturing transformed the way humans work. Since the 18th century, successive waves of innovation, such as the assembly line and the computer, continued to alter and change the nature of manufacturing. Today, we find ourselves in the midst of another industrial transformation.
I was intrigued by two recent IoT related survey and reports. They emphasize use cases about efficiencies and return on investments but, surprisingly, there is no mention of people-safety nor productivity. I think it is imperative to place people at the heart of the IoT universe. Today, people related use cases have been greatly understated. We will be doing a great injustice if we continue to ignore the human angle.
Mike Szczys is a Developer Relations Engineer at Golioth. His deep love of microcontrollers began in the early 2000s, growing from the desire to make more of the BEAM robotics he was building. When he’s not reading data sheets, he’s busy as an orchestra musician in Madison, Wisconsin. At Golioth, a commercial IoT development platform, we love using the power of Grafana to easily visualize data from IoT installations where tens, hundreds, or even thousands of devices are reporting back.
In this article you will learn about Node-RED, a popular tool for rapidly gluing together different types of hardware and software. You’ll learn about some of the core concepts of Node-RED and then learn how to make some workflows like storing data from a sensor using an MQTT broker and InfluxDB.
Large applications can produce very large symbol files when debug information is enabled (especially at the higher, more verbose levels of debug info!). This article describes some techniques for reducing debug symbol file sizes! Like Interrupt? Subscribe to get our latest posts straight to your mailbox.
When Rolls Royce Power Systems recently needed to improve its operational efficiency within its manufacturing plants, it didn’t expand its use of a legacy process historian or purchase historian connectors to export data to their business intelligence systems. Instead, it decided to go with a modern time series database, InfluxDB. Graphite Energy, another customer we featured in our recent IIoT announcement, also chose InfluxDB over the legacy process historian vendors. Why?
The question of how to get data into a database is one of the most fundamental aspects of data processing that developers face. Data collection can be challenging enough when you’re dealing with local devices. Adding data from edge devices presents a whole new set of challenges. Yet the exponential increase in IoT edge devices means that companies need proven and reliable ways to collect data from them.
