The role of Artificial Intelligence in the IoT

Problems

The Internet of Things (IoT) is the network of devices, home appliances, and other items embedded with electronicssoftwaresensorsactuators, and connectivity which enables these things to connect and exchange streams of data. This big data can be analyzed from the business value perspective, which will create better human-machine interface that is useful for the users.

Solution

Artificial Intelligence will play an important role to take useful actions from a large amount of digital data. An AI technology brings the ability to automatically identify patterns and detect variation in the data that smart sensors and devices generate.

IoT Platform

Automobile industries are incorporating artificial intelligence—in particular, machine learning—into their Internet of Things applications and seeing capabilities grow, including improving operational efficiency and helping avoid unplanned downtime.

Artificial intelligence and Internet of Things

Artificial intelligence is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. It is a software module to perform complicated jobs efficiently with zero human interference. AI will observe, learn, plan, manage, and control objects using natural processing languages and this technology will enable machines to learn based on experience and produce reliable, concurrent solutions similar to a human being.

Internet of Things (IoT) is something where a group of devices, systems, and machines are connected through an internet ecosystem. This could be a LAN or a WAN or a Cloud-based setup. Patterns7 IoT platform helps enterprises to monitor device performance in real-time. With expanded capabilities of smart, connected devices and the data they generate is creating a new era of opportunities. Industrial IoT platform helps you to connect, manage, analyze and create an experience for the connected world. Patterns7tech is leading IoT solution provider in India in Energy and Manufacturing domain

The current data usage via the Internet of Things

Currently, IoT and its associated devices mostly use the conventional mechanism to send, receive, and process the data. For example, a robot from the smart manufacturing industry 4.0 sends a large amount of data continuously, or an energy asset from the connected industry sends huge data. In the above cases, all this huge amount of one-sided data might not be useful unless data insights are created through AI.

How artificial intelligence can help

In order to avoid the failure to handle specific data generated from an energy asset or the critical collective data of a robot machinery unit, AI can come to the rescue. The end user will get customized and useful data through machine learning algorithms. Billions of devices with the great number of purposes will be connected. This is where AI will play a significant role and more complex applications will come under its domain.

The AI key to unlock IoT potential

The powerful combination of AI and IoT technology is helping iot solution providers to avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management.

1. Avoiding costly Unplanned Downtime.

In a number of sectors, unplanned downtime resulting from equipment breakdown can cause heavy losses. For instance, according to one study for industrial manufacturing in total, unplanned downtime costs $50 billion per year, with equipment failure being the cause for 42 percent of the outages.1

Predictive maintenance using analytics to predict equipment failure ahead of time in order to schedule orderly maintenance procedures can mitigate the damaging economics of unplanned downtime. Because of AI technologies particularly machine learning can help identify machine usage patterns and anomalies and make predictions based on large sets of machines generated data, they are proving to be particularly useful in implementing predictive maintenance.

2. Increasing Operational Efficiency.

AI-powered IoT can help to improve operational efficiency. This is due in part to the power of machine learning to generate fast and precise predictions and deep insights—and to AI technologies’ ability to automate a growing variety of tasks.

3. Enabling new and improved Products and Services.

IoT technology coupled with AI can form the foundation of improved and eventually entirely new products and services as well. For instance, for GE’s drone and robot-based industrial inspection services, the company is looking to AI to automate both navigations of inspection devices and identification of defects from the data captured by them. This could result in safer, more precise, and up to 25 percent cheaper inspections for the client.2
Patterns7 Technologies is continuously innovating around IoT and AI to offer product services based on predictive analytics.

4. Enhancing Risk Management.

A number of applications pairing IoT with AI are helping organizations better understand and predict a variety of risks as well as automate for rapid response, enabling them to better manage worker safety, financial loss, and cyber threats.

Combining AI and the Internet of Things, 3 Useful Examples

The following AI and IoT combinations are useful examples of how these two broad concepts collide. It’s important to note that many so-called “IoT” devices wouldn’t make this list. By the criterion, we’re selecting for (connected devices that leverage artificial intelligence), a device isn’t “smart” merely by virtue of being controllable via an iPhone app. Below are some useful examples:

1 – Remote Energy Consumption Monitoring, SMART Energy

SMART Energy Solution monitors your energy assets performance in real-time. Monitor real-time energy consumption and alert notifications on Mobile apps. Meter data is continuously read and displaying the graphical representation of consumption on the web and mobile apps. (Smart Energy)

2 – Asset Performance Management, SMART Manufacturing

Patterns7 Industrial IoT platform monitors machine performance in real-time. It helps to improve the efficiency, manage losses and make data-driven decisions. With the right tools & technologies, we help factories to transform for the better. Read more to know how Patterns7tech is helping clients.

3 – Realtime production loss reporting, SMART Manufacturing

Based on real-time cycle data from the machines or robots, hourly production is monitor through the mobile app. Any production loss would help the operation team to take timely action. APM Asset Performance Management solution can help to control losses and increase ROI. Read more to know how Patterns7tech is helping clients.

Some useful artificial intelligence platforms

A lot of innovative products based on AI are being developed today and its count is ever increasing. Currently, the research community, students, and commercial developers are using or developing a lot of AI-based platforms. Some of the useful tools or platforms are given below:

  • Google machine learning APIs.
  • Amazon’s DSSTNE (Deep Scalable Sparse Tensor Network Engine)
  • Apache Spark MLlib and Singa
  • Caffe
  • Open Neural Networks Library (OpenNN)
  • OpenAI
  • Amazon Machine Learning

References:

  1. Intelligent IoT – Deloitte
  2. Artificial Intelligence, IoT & Beyond Artificial Intelligence Paradigm | HCL Blogs

Endnotes

  1. IndustryWeek in collaboration with Emerson, “How manufacturers achieve top quartile performance,” WSJ Custom Studios, accessed December 7, 2017. View in article
  2. Wylie Wong, “NVIDIA’s AI supercomputers help ‘augment’ human site inspectors,” DataCenter Knowledge, September 7, 2017. View in article

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