If you’ve read about the Internet of Things (IIoT), it seems that it’s all perfectly laid out already. The future will contain sentient robots, and your homes and personal lives will be more efficient and comfortable than ever before. Your milk will never sour again, because your smart fridge will dump it into your smart trashcan before it goes bad. The IoT will make you more productive than ever before, by automatically predicting the next step of well, everything.
The media hype is, as usual, at the leading edge of what is already settling into a trend. But as anyone responsible for equipment health knows, the Industrial IoT counterpart is transforming equipment into intelligent machines that can predict their own needs. But implementing an IIoT strategy requires a plan.
Reasons Why IIoT Adoption is on the Rise
Defined by the German government in 2013 as a part of ‘Industry 4.0,’ smart factories employ four primary methods to automate and more efficiently communicate: the cloud, cognitive computing, IoT connectivity and a combination of physical and virtual systems. While the theory is well-established, the actual smart facility is just now becoming a reality. The convergence of several trends happening in modern industry right now will bring about an uptick in IIoT adoption including:
- Sensing Capabilities: The various sensor technologies and capabilities that are essential to the IIoT are becoming increasingly affordable. As prices continue to drop over the next few years, more factories will be able to afford the implementation of connected technologies. Once the threshold has been crossed at which the ROI is far greater than the cost of sensors and installation, we will see a rapid increase in IIoT implementation. At the current escalation of affordability, we are on a fast-track to reaching this tipping point. The IIoT will become an out-of-the-box experience, rather than a massive custom effort requiring special projects, dedicated teams, rooms full of servers and prohibitively expensive sensors.
- Connectivity: The bandwidth required to transfer data back and forth from machine to the cloud is increasing exponentially, as more devices come online. This in conjunction with the fact that network prices are dropping, will take us to places we couldn’t imagine in the past. Similar to sensor costs, greater connectivity means that facilities will no longer need to host their own server farms to process data and facilitate communication.
- Cloud-based Insights and Machine Learning: A main motivation for implementing an IIoT strategy is to optimize the decision-making process when it comes to maintaining connected machines. With compute-and-data-intensive processes moving to the cloud, operational costs are again reduced and made more feasible. The ability to compute large amounts of data has been made dramatically easier in the last few years, leading to less of a dependence on large teams of statisticians. Moving to advanced artificial intelligence and machine learning capabilities are driving more internal facility insights and changing the future with data-driven actions.
Currently, IIoT applications need customization around connectivity, sensor suites, cloud computing integrations and analytics. Early adopters of IIoT programs at facilities are met with multiple challenges: gleaning insights from their existing machines, finding innovative ways to get all legacy machines online, establishing a clearly-defined plan for deriving conclusions from a sea of data.
Instead of building a custom implementation, partner with first movers and benefit from their domain expertise. It takes a lot of time and specific expertise to get a thing right if it’s not in your wheelhouse. For the IIoT to become an integral component across the board, there must be a common language and solutions for using sensors, the cloud and connectivity.
In the meantime, there is a plethora of data available if harnessed strategically. While waiting for the IIoT to become the status quo, those who act now will acquire first-mover advantages and usher in the smart facility of the future.
About the author: Gal Shaul is a Co-Founder of Augury and currently serves as its Chief Technology Officer. Gal has extensive experience in signal processing, software engineering and embedded systems. Prior to founding Augury Systems, Gal was the Head of Software development at EndyMed, a medical devices start-up.
Edited by
Ken Briodagh
