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Machine learning and the IoT: The next step in interconnectedness

By Max Burkhalter
December 27, 2019

The power of the Internet of Things allows society to conduct business like never before. Interconnected devices in the hands of both companies and consumers enables the sharing of information with speed and efficiency that earlier generations couldn't even dream of. Yet, the IoT is only at the beginning of its life. Soon, it will be supplemented by an emerging technology that has the power to completely transform both commerce and operations: artificial intelligence. According to Forbes, the welding of the IoT and machine learning is a match made in heaven, and the possibilities it opens up are practically endless.

Face time

Machine learning can be used to improve countless different aspects of a modern business. As machine-learning methods become more reliable and accessible to the general population, businesses can utilize these innovations for their own use. One area of note is facial recognition; the ability for software to identify individuals based on their facial features is one with huge amounts of potential. Amazon foresees a future where cashiers are unnecessary; instead, facial recognition databases identify customers who shop in stores, record the items they procure and then charge them as they walk out, all without any human intervention. This also gives Amazon a potent weapon in their loss-prevention arsenal. Facial recognition is not only useful for monitoring customers, however. It can also play a role in the efficient management of employed personnel. Identifying the number of people in an office, their roles and even their preferences can allow machine learning programs to tailor aspects of the workplace, such as temperature and lighting, to accommodate those in the building or save energy. In jobs that require a person's presence, facial identification can also remove the need for clocking in or recording attendance, as these IoT-connected cameras can control the gathering of this information itself.

Financial advisement

Machine learning and artificial intelligence can additionally be used in a financial capacity, benefiting both consumers and businesses. Organizations can make use of machine learning to analyze market trends and combine these insights with various metrics, such as customer retention, recent sales and more, in order to run new campaigns and make adjustments to financial operations. According to Deloitte, advanced programs can forecast economic performance, segment hypothetical markets and even identify potential new clients through careful analysis of data that only cutting-edge computing technology can facilitate. A company with all of their financial and marketing data connected through a secure network to a machine-learning program can adjust their resources to new or updated commitments with startling efficiency, when combined with the power of the IoT. All this needs is a small amount of control by a human to guide these programs towards the goals an organization has in mind.

Machine learning can be used to conduct and improve financial operations.Machine learning can be used to conduct and improve financial operations.

Future proofing

Yet facial recognition and financial management is just the tip of the iceberg when it comes to the power of machine learning. As the technology for basic machine-learning techniques improves, such as neural networks and databases used in facial matching, the line between autonomous programs and true AIs grows thinner. "Smart" machine learning, or artificial intelligence, would be able to control various operations of a company as long as the organization's devices are connected to the internet, with next-to-no human interaction besides basic maintenance. For example, an AI, coupled with the IoT, could analyze activity volume at a company's shipping center and make changes depending on needs. Machine learning can teach an AI that not enough forklifts are in use, based on the analysis of past trends and comparisons with current volume. However, at this point, an AI can come to solutions all by itself, choosing a particular course of action based on available information, whether that be scheduling more forklift drivers or slowing production. All of this can be done independently of a human operator; AI is the next step for the IoT, and systems like this are becoming feasible as machine learning and the IoT become more intertwined.

For companies looking to make the most out of the IoT and emerging technologies like machine learning, strong network infrastructure is key. Perle offers high-performance connectivity tools that can help enterprises prepare for the future of business technology. Our industrial-grade Ethernet converters and reliable console servers enable IT admins to focus on what really matters - building a strong framework for IoT integration. Read some of our customer stories to find out how we've helped other companies take full advantage of connected technologies.


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