How AI Will Impact IoT


The internet of things (IoT) — the collection of sensors and devices that speak to one another via the internet to gather data — is already helping organizations make smarter business decisions, improve efficiency, reduce costs, and more. These benefits have naturally caused a surge in IoT devices, and IoT’s growth isn’t expected to stop anytime soon.

But with this spike in IoT devices comes an inundation of data, and organizations are looking for help analyzing it to gain insight and intelligence, as well as managing the devices themselves. 

Enter artificial intelligence (AI). 

AI is already being employed to find insights in the data gathered by IoT applications, and it’s expected to grow significantly over the coming years as more and more organizations recognize its potential. Here are some trends to be aware of, as well as a few of the benefits we can expect from AI-powered IoT.

AI and IoT Trends at a Glance

  • AI powered over 40% of the digital transformation initiatives in 2019. (Source)
  • Over 50% of all IoT spending in 2020 will be made up by business investment. (Source)
  • The AI industry will be worth $190 billion by 2025. (Source)
  • While there were 10 billion IoT devices in 2018, there will be more than 64 billion by 2025. (Source)
  • By 2025, IoT could potentially create between $4 and $11 trillion in economic value. (Source)

What to Expect From AI and IoT

Increased Operational Efficiency

One of the primary benefits of AI-powered IoT is a boost in operational efficiency. Machine learning is able to process constant flows of data and identify patterns that go undetected by simple gauges and the human eye, thus predicting operating conditions and adjusting them in real time to ensure ideal outcomes.

The insights that machine learning shares may not always make sense initially. For example, the machine learning devices for a shipping fleet operator suggested that they could increase profitability by cleaning their ships’ hulls more frequently — a task that’s both time-consuming and expensive. Although it seemed counterintuitive, the math proved that the fuel efficiency gained by keeping the hulls smooth and clean greatly offset the added cleaning expenses.

Predictive Maintenance

Just as machine learning can predict operating conditions, it can also predict equipment failure before it actually happens by identifying patterns in the data provided by machines. This ability, called predictive maintenance, makes it possible to schedule maintenance ahead of time to prevent unforeseen downtime. In industries where downtime from equipment failures can be costly, predictive maintenance is crucial.

By some estimates, predictive maintenance can decrease maintenance expenses by 5 to 10%, increase equipment availability and uptime by 10 to 20%, and decrease maintenance planning times by 20 to 50%.

Improved Risk Management

Equipment failures aren’t the only risk machine learning can predict: IoT-AI applications are already tracking data from law enforcement surveillance to determine where crimes will take place ahead of time, identifying car insurance premiums by reviewing driving patterns, detecting fraud at ATMs, and finding stress conditions that are potentially dangerous for factory workers.

This foresight allows organizations to create more efficient and effective emergency response plans, thus better managing cyber threats, financial loss, and employee safety.

Superior Products and Services

In addition to enhancing existing processes, the combination of AI and IoT can also create new products and services. 

For example, robots and drones controlled by AI open up new opportunities for inspection and monitoring, and natural language processing (NLP) continues to improve machine-human conversation. 

AI is also reinventing commercial fleet management by monitoring all measurable data points in a fleet of automobiles, trucks, trains, or planes to identify quicker scheduling and routing and minimize unplanned downtime. According to Cloudera, Navistar devices monitoring its fleet of vehicles have reduced downtime by as much as 40%.

What About Security?

Companies across all industries obviously have a lot to gain from the meeting of AI and IoT, but certain precautions are also necessary in order to make the most of this digital transformation. With the benefits to be expected from AI-powered IoT will come a surge in connected IoT devices, and with this surge will come an equal amount of new opportunities for security breaches.

While many modern security options are offering companies visibility into all their endpoints (a feat that sounds simple but is becoming increasingly complex, given the number of connected devices), the real challenge is actually securing them. Companies that want to benefit from AI-powered IoT without potentially catastrophic cyber risk should instead look to network security solutions designed for the industrial IoT, such as the Airwall™ from Tempered Networks.

Rather than merely giving you visibility into your endpoints, the Tempered Networks’ Airwall uses host identity protocol (HIP) to cloak every endpoint, making your entire network invisible to lateral movement and external threats. 

With solutions such as this, organizations can realize the full potential of AI-backed IoT without jeopardizing their security, finances, reputation, and future viability.

Submitted By: 
Name: Estee Woods




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TechFond - Latest Technology | Analysis | Enterprise | Startups | Product Reviews | How Tos: How AI Will Impact IoT
How AI Will Impact IoT
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