The continuous progress of IoT technology will assist in more advanced data analysis

The Internet of Things has always been one of the highly anticipated trends in the digital age. This year, with the emergence of the pandemic, it has changed our way of life and work, thus giving the Internet of Things a new prominent position.

As we enter 2021 and prepare to bid farewell to the turbulent year, let us look ahead to the future and the IoT trends that will drive future business and technological change.

In 2021, companies will begin to realize that IoT is not only a hype or another buzzword, but also a technology with the potential to truly change the industry. Using insights from multiple industry media and our own internal business expertise, we have identified the main trends related to IoT that we expect to see in 2021.

Firstly, it is still about the "edges"

If you venture into the world of the Internet of Things, you may think, "Isn't this a trend in the past few years?" Well, yes, and with good reasons.

With edge computing, data does not need to be sent to the centralized data center on the network, but is processed and analyzed at the edge of the network, thus reducing transmission time and delay. This allows for almost real-time access and analysis of data, which is a tempting driving force for many organizations that require quick response. Edge computing also reduces bandwidth costs because information processing is performed at the source, reducing data traffic to the centralized data center.

Although not a new thing, the importance of edge data processing may continue to grow due to the rise of 5G, the increase in global connected devices, and the growth of generated data.

Secondly, the addition of remote operation cases

In response to the COVID-19 pandemic, many manufacturers, distributors, utilities, and pharmaceutical companies have had to adjust their strategies and quickly track their digital transformation efforts to adapt to new regulations that require remote work.

Previously unconnected assets have been connected for remote operations and continued customer service. It is expected that by 2021, we will continue to see an increase in the adoption rate of IoT and other technologies for use cases related to remote monitoring of devices and assets.

Thirdly, predictive (non reactive) maintenance

According to a research report by Vanson Bourne, 82% of companies have experienced unplanned downtime in the past three years, and the losses caused by downtime may be high, estimated to be equivalent to a loss of $250000 per hour.

From a historical perspective, maintenance has been reactive maintenance aimed at faults, although initially a very cheap solution, it may be the least financially beneficial approach. Subsequently, many organizations adopted preventive maintenance programs that relied on regular planned maintenance of equipment.

Predictive maintenance is a new method of utilizing data collected from control systems and connected sensors. With the correct data, companies can track key indicators of equipment and mechanical wear to predict and prevent unplanned downtime and expensive maintenance costs.

In 2021, we will see a greater shift in strategy towards predictive maintenance to improve operations and optimize costs.

Fourthly, the Internet of Things assists digital twins

The theory of digital twins was first conceptualized in 2002. Digital twins are virtual representations of processes, objects, or systems that function the same as objects in real life. We expect that as connected assets grow, digital twins will also gain traction by visualizing all data points from connected sensors in digital twin format, allowing for a more comprehensive understanding of the performance of physical objects and providing insights into potential issues.

Fifth, more advanced data analysis

The true benefits of the Internet of Things do not come solely from data, but from wise analysis that can generate useful insights and help businesses make informed decisions.

As the amount of generated data increases, analysis will become more important, and advanced solutions driven by artificial intelligence and machine learning will improve the processing of large amounts and various data structures.

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