Dealing with Mountains of IoT Data: An IIoT World Webinar Reflection

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We’ve made the case many times that instrumentation is critical for understanding changes in the physical and virtual worlds. During this recent webinar, panelists discussed the challenges and opportunities of integrating IoT sensors into existing infrastructure, ensuring data quality and accuracy, and leveraging sensor data for operational efficiency and productivity.

Moving past manual processes

Despite spilling so much ink about digital transformations and Industry 4.0, many industrial and manufacturing processes remain manual. On one hand, this makes sense. These machines and systems are expensive, complex, and last for a long time. If it’s not broken, don’t fix it.

But what if you could make this equipment last even longer? Panelists discussed the advantages of instrumenting industrial environments, i.e., putting sensors on things. Industrial manufacturers can gain valuable insights by harnessing the vast amounts of data generated by IoT sensors.

Manufacturers often face challenges when adopting IoT technology. They often have apprehensions about new technology and the enormity of the data generated by IoT sensors. However, the panelists believe these challenges can be overcome by understanding the underlying problems technology can solve and by integrating this data into automated platforms.

As Balaji Palani, VP of Product Marketing at InfluxData, pointed out, a time series database, like InfluxDB, can effectively manage the increasing volume of IoT data generated by these sensors. This allows manufacturers to consolidate data from various sources and summarize it for easy analysis and decision-making. “Data is the currency. There is a lot of equipment out there on industrial floors and stuff like that where you want to collect that data,” he said.

Kelsey Hickock, Market Development Manager for Applied Industrial Technologies, further suggested that manufacturers must focus on specific pain points that IoT can help solve and start small with IoT implementation. This enables them to see the benefits of IoT, build confidence, and then scale up gradually. “Start really small, whether that be, if you end up wanting to monitor something, look at starting with one machine or one line and deploy one piece of hardware that could collect maybe five data points,” she advised.

Managing all that data

Industrial operators must be ready to manage the large volumes of data that IoT sensors generate. Data quality management is critical for actionable insights in Industry 4.0.

IoT sensors tend to be more rugged and durable than conventional sensors, making them ideal for industrial environments. They also offer better connectivity and easier integration with IoT platforms. However, ensuring data quality and managing the vast amount of data generated by these sensors can be challenging. Kelsey Hickock suggested that manufacturers can overcome these challenges by using automated tools for preprocessing the data, continuous monitoring, and leveraging the power of edge computing.

Balaji Palani explained the capabilities of InfluxDB in managing the immense quantity of time series data produced by IoT sensors. He also mentioned that it provides flexibility because of the option to include more details using tags. “The beauty about InfluxDB, again, not every tool can do this, but one of the things that InfluxDB does very well is you don’t need to define this data before you can start to collect your data,” he explained.

As for metadata and best practices, Palani noted that tags add context to data in InfluxDB, allowing users to create a more sophisticated understanding of the data. “All of these additional contexts: things like, which machine? Where is it? Is it coming from this sensor, this PLC? Any additional context under which circumstances this data is emitted can be appended to what we call tags,” he said.

InfluxDB is also able to collect data from multiple sources, consolidating data in a central hub and eliminating data silos. Some IoT sensors come with their own infrastructure and data hubs, but by leaning into APIs, open source tools, and standard protocols, industrial operators can build custom data pipelines to ensure the data they need gets to where it needs to be. A plugin-based, open source data collection tool like Telegraf can do a lot of this heavy lifting.

Turning data into intelligence

The panelists agreed that Industry 4.0 and IoT sensors offer manufacturers distinct advantages and business opportunities, including process optimization, real-time monitoring, and predictive maintenance. Palani pointed out that having a system where all of the data can be accessed and acted on uniformly can increase visibility throughout an organization, lower operation costs, and accelerate business value.

Kelsey Hickock noted that manufacturers that effectively harness and act upon sensor data can realize potential business opportunities such as optimizing production processes, reducing waste, improving quality, enhancing overall efficiency, and even generating new business models. “Leveraging your data to transition from selling products to offering services… manufacturers may pay based on the usage, as opposed to owning the equipment,” she suggested.

Getting started

Getting started with this kind of transformation can seem daunting. The speakers emphasized the importance of starting small and scaling gradually with IoT implementations. By focusing on specific pain points that IoT can help solve, manufacturers can see the immediate benefits, build confidence, and then scale up accordingly. This approach can help manufacturers overcome the initial hurdles and apprehensions towards adopting IoT technology.

For more information on InfluxDB and how it works in Industry 4.0, check out this e-book about modernizing data historians.

Watch the full webinar.