What’s Really Happening with IIoT Technology in 2021

What’s Really Happening with IIoT Technology in 2021

Thinking about 2021 is a welcome relief after a difficult year for many people, and a lot of us expect things to get better in the months ahead. That includes the manufacturing sector, which had to contend with supply chain issues, shutdowns, outbreaks, and demand-side challenges and is now looking at ways to work safer and more efficiently in the new year.

In 2021, we’ll see factories, food-service operators, and transportation companies get more out of the sensor networks and remote wireless monitoring capabilities they quickly adopted this year—and we’ll see more companies in these industries add remote sensor systems to stay competitive. But the biggest IIoT-related gains in 2021 may not be the ones that typically make tech news headlines.

Health and safety monitoring will accelerate automation and remote monitoring

Safety for factory workers has been paramount this year, and that will continue through 2021. Many manufacturers have risen to the challenge of operating with social distancing and safety precautions in place to protect their people, and remote sensors and cameras have been important components in making factories safer. Others will need to do the same in 2021 to reduce the risk of outbreaks and shutdowns.

For example, combining camera coverage with door and activity sensors can allow plant security teams to make sure that workers are following safe traffic patterns through the building during shift changes. These sensors can also alert managers if there’s unexpected activity in areas that are off-limits due to disinfection requirements or restricted to key personnel.

The pandemic has accelerated the trend toward automation and remote monitoring in other ways, too. As more facilities adopt these tools to protect their workforce and remain competitive, they’re seeing how easy it is to add sensor capabilities and collect data that they can use to automate and monitor repetitive tasks. This is another way to protect worker health while leveraging efficiency gains. For example, if you can automate and remotely monitor a repetitive task that you used to have 5 people doing in the same room, those people are now free to work on higher value tasks, presumably at a safe distance. We expect this trend to continue through 2021 and beyond.

Integrating sensor and camera data improves safety and efficiency

Another trend we expect to accelerate is pairing multiple types of sensors in the same location, aka sensor fusion. Sensor fusion can overcome one of the biggest challenges of relying on data from one type of device: Whether it’s a video camera, a wireless motion sensor, or a remote temperature sensor, each device provides one kind of data with little or no other context.

For example, a video feed that shows an employee leaving a walk-in cooler door open can’t also show whether the temperature inside the cooler then rose to an unsafe level. If the cooler had a networked  temperature sensor installed, then a manager could review the temperature while the door was left open to see if food safety had been compromised. If the sensor had a threshold set, it could even notify the manager immediately if the temperature went out of safe range—and the video would show the manager why it happened.

Integrating sensor and camera data can show us more than the camera can see on its own. And as remote monitoring of workplaces continues to matter for safety, this type of integration is becoming more valuable to manufacturers, foodservice companies and other employers.

Besides alerting managers to potential safety risks, combined sensor data can also help companies work more efficiently. For example, an air conditioner thermostat in a workspace that’s set to turn on at 68 degrees can stay off if nearby movement activity sensors indicate there’s no one in the room. In a time of economic uncertainty, integrated sensor data can deliver efficiency gains and cost savings to help companies stay viable.

IIoT-supported safety for customers reduces liability for businesses

IIoT sensor networks can also improve customer safety and compliance for businesses like restaurants, transportation companies, pharmacies and clinics that need to store or move products at carefully maintained temperatures.

For example, remote temperature sensors that are capable of monitoring very low temperatures can help preserve the efficacy of temperature-sensitive health care products like vaccines, allergy shot serums and biological treatments for diseases. Standard wireless temperature sensors can reduce the risk of foodborne illness for restaurant and food manufacturer customers. Mobile sensor networks installed in refrigerated trucks can help ensure that food and medications arrive in usable condition.

Preventing harm to customers and patients is a matter of ethics and trust, of course. It can also be a matter of financial survival, especially for businesses that are already dealing with economic uncertainty. A 2018 study in Public Health Reports found that the cost of a foodborne illness outbreak can be as high as $2.6 million—far more than the cost of the technology that could prevent the problem. For these reasons, we expect to see more businesses adopt low-cost sensor systems in 2021 to protect their customers and their revenue.

Predictive maintenance will deliver—for organizations that do the work

Predictive maintenance has been a major topic in the IIoT world and in manufacturing for a few years now. This strategy relies on vibration sensor data, artificial intelligence and machine learning to analyze how a piece of equipment is operating, when it’s likely to start operating outside of its ideal range, and when it will need maintenance for optimal functioning over its life span.

Organizations that do predictive maintenance right typically see a reduction in maintenance costs because they’re only servicing equipment when it needs it, instead of on a calendar or hours-based schedule. They also experience less unplanned downtime.

However, a remote sensor network alone isn’t enough to create an effective predictive maintenance program. PdM relies on machine learning and AI that have to be taught what to look for, and that requires human expertise. A June McKinsey report on IIoT also notes that a robust IT system and scalable IIoT capabilities are also required to build an effective PdM program.

In the year ahead, the manufacturers who get the most value from their PdM programs will be the ones who make a full commitment to getting the IT and machine-learning training right.

Building on the lessons of 2020

As tempting as it may be to close the books on 2020 and leave them closed, this year has offered a lot of lessons in the value of adopting new technology fast, pivoting to meet new demands, and coping with challenges to the standard ways of working. Companies that keep those lessons in mind, and maximize the value of their technology investments, will be ready to handle whatever 2021 brings.

Shopping Cart
Scroll to Top
Talk to Expert