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How the Internet of Things Is Leveraging AI to Gain a Competitive Advantage

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How the Internet of Things Is Leveraging AI to Gain a Competitive Advantage

The International Data Corp reveals that without AI integration, IoT-deployed data will have “limited value.”

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Internet of Things Leveraging AI To Gain Competitive Advantage



The Internet of Things (IoT) has evolved from a futuristic business buzzword and can now unleash vast potential. With the evolving technology landscape, IoT technology is getting smarter, and therefore, more companies are incorporating AI (like machine learning, deep learning, genetic algorithms, advanced learning) with IoT applications to generate an advanced output.

The fast ability to wring data makes AI more valuable. This has made most of the giant organization excited to pour hefty investments in IoT because AI is sure to bring a sensation in the field IoT.

Facts and Figures at Glance

  • Increase in the venture capital funding of AI-focused IoT startups can be expected.
  • Acquisitions of AI-focused IoT startups is expected to boom.
  • Vendors of IoT platform — Amazon, Oracle, and Microsoft to name a few — taking the leads to integrate AI capabilities
  • As per Gartner, more than 80 percent of enterprise IoT projects will be in the market by 2018 and will include AI components, up from only 10 percent today.
  • Large organizations across industries are already leveraging or exploring the power of AI with IoT to deliver innovative solutions and products (offerings that make the operation more productive and efficient).

Let's Emphasize Intelligent IoT

In general, IoT is defined as the network of physical devices capable of sending and receiving data across the Internet. This comprises wearables and mobile devices, medical devices that are connected, smart home appliances, and the sensors.

The connected things can be interconnected into an ecosystem in which they interact with one another and with decision agents via the Internet or a private network. However, the real opportunity for innovation comes when things are intelligently connected when the data is fed into an AI-based algorithm for autonomous decision-making and machine learning.

In order to gain new insights from the interconnected things, applying AI to IoT will improve the relationship allowing cognitive engines for more natural interaction.

AI Unleashing IoT Potential

Artificial intelligence technology plays a growing role in IoT applications and deployments. Both investments and acquisitions in startups that merge AI and IoT have scored higher since a couple of years ago. Major vendors of IoT platform software are exploring prospects to integrate AI capabilities such as machine learning-based analytics.

Market Trends

IoT app development companies are expecting to present revolutionary services and application in the near future. And, of course, it will be among the biggest outcome created merging IoT and AI. Further, most of the standalone businesses will undergo reinvention to become part of integrated networks.

According to IBM, the spending on IoT worldwide hit approx $772.5 billion in 2018, a 15 percent increase over 2017. Much of that spending came from enterprises. 66 percent of executives are now comprising IoT into their operating models, according to a recent study by the IBM Institute for Business Value.

AI plays a crucial role in making IoT applications more advanced and having better deployments. Further, taking into account the investments and acquisitions in startups integrated with AI and IoT, there has been remarkable growth. 

Machine learning is an AI technology that takes has ability and competence to automatically detect patterns and oddities in the data that smart sensors and devices generate, including information such as temperature, pressure, humidity, and the quality of air. Generally, when we compare the traditional business intelligence tool with machine learning, it was clear that the operational predictions gained by ML were up to 20 times fast with great precision.

Other AI technologies, like speed recognition or computer vision, play a crucial role in interpreting data into a useful piece of information, which is too much for one human to perform alone.

AI applications for IoT enable companies to avoid unplanned downtime, increase operating efficiency, and enhance risk management.

Advantages

Manage Costly Unplanned Downtime

For sectors like manufacturing, oil, gas, and other similar industries, unplanned downtime results in equipment breakdown, which can be a costly affair.

Predictive maintenance using analytics prevents equipment failure before downtime, which can be utilized to schedule a maintenance procedure. Clearly, this showcases the power of AI and IoT and how they can be utilized to restore any damage. Machine learning makes it possible to identify the pattern in the constant stream of data to predict equipment failure.

For instance, in their survey, Deloitte found predictive maintenance very useful to manage the time to plan maintenance, i.e. 20-50 percent (this means that the equipment uptime increased the availability by 10-20 percent and reduced overall maintenance costs by 5-10 percent).

Increase in Operational Efficiency

It is no doubt that AI-powered IoT is aiding operational efficiency. Similar to machine learning predictions, AI also helps in shaping operational conditions and allows us to identify the parameters required to streamline processes. This is done by crunching constant streams of data, which are highly impossible for one, single human.

Improve Products and Services

Upgrading IoT with AI will directly help to create new products and services. With the advancement of time, natural language processing is getting better with near-constant human-machine interaction.
For instance, AI-controlled drones and robots are new opportunities for monitoring and inspection.

Moreover, if we talk about fleet management, it is reinvented via AI. This can monitor every possible data point, which helps to reduce unplanned downtime. For instance, Cloudera claims 40 percent cut downtime for fleet vehicle monitored by their Navistar device.

Improvise in Risk Management

Today, we can see a number of useful applications created pairing IoT with AI that help organizations understand and predict a variety of risks, enabling automated and rapid responses like managing workforce safety, financial losses, etc.

Conclusion

There is no denying that the future of IoT will be AI. It's also expected that, in the near future, it will be difficult to find an IoT implementation without AI. The International Data Corp reveals that AI will support IoT efforts, and without AI integration, the deployed data will have “limited value.”

Topics:
iot ,ai ,artificial intelligence ,data ,machine learning ,smart data ,algorithms ,risk management

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