As the internet of things gets bigger and smarter every day, artificial intelligence plays a significant role in enhancing its deployments and applications among other important features. The value of AI in this field is notable in its ability to rapidly wring comprehensions from files or data. This piece takes a look at some of the ways in which AI transforms industrial IoT.
1. Unlocks the Potential of IoT
Artificial intelligence has a way of unlocking the full potential of the internet of things. Over the past few years, companies that have incorporated AI in their operations have witnessed increased productivity because of machine-based learning analytics.
AI technology offers exceptional machine learning abilities including smart devices and sensors that can easily generate information such as;
- Humidity levels
- Vibration
- Air quality
- Sound
- Temperature and pressure among other industry based and data related insights
Compared to manual or traditional tools used in the industry to detect anomalies, AI is very efficient. What’s more, it is accurate and offers a better insight that helps industries to employ quality operating risks.
2. Managing unforeseen costly downtime
Many industries including manufacturing options can suffer huge losses in the event of unforeseen downtime. Such occur from the breakdown of machines and related equipment. In the event of emergency maintenance, the industries also suffer huge losses. With AI machine learning, it becomes easy for industries to identify any anomalies or unusual patterns that signal system failure.
With predictive strategies, companies can easily plan for machine maintenance and prevent downtime. This further increases machine or equipment uptime significantly by more than 20 percent. It further reduces maintenance costs by up to 10 percent.
3. Enhances operational efficiency
AI also plays a crucial role in enhancing operational efficiency in the industrial sector. This is attributed to AI machine learning ability to predict failures and identify areas that need to be adjusted to keep industry operations running. For example in a shipping industry, machine learning systems can identify that regular cleaning of ships hulls can lead to increased profitability and productivity. The process helps to ensure machines run smoothly and efficiently, hence preventing costly downtime processes.
4. Enhances the creation of quality products and services
Incorporating AI in IoT can lead to the creation of quality products and services. AI comes with capabilities such as natural language processing (NLP) that is getting better by the day. It is a feature that allows people to interact with machines other than the need for human operation through AI controlled drones and robots. Therefore, it enhances inspections and monitoring processes.
What’s more, there are many machines and vehicles that are being enhanced through AI. They have the ability to measure different data points in trains, trucks, planes, and automobiles thus creating more efficiency in routing. In fleet management, AI has transformed operations as it can reduce operational tasks by more than 40 percent.
5. Risk management
AI also transforms industrial IoT by allowing organizations to predict and have a better understanding of how to manage possible risks. This is done in a highly automated process thanks to modern IoT mobile app development technologies. Through the automated process, organizations can respond swiftly in the event of accidents, enhance the safety of employees, and prevent cyber risks as well as financial losses.
Today, AI applications include technologies that can detect a wide range of fraudulent behaviors, potential hazardous behaviors from employees and possible crime scenes right on time.
6. Natural complement
AI is known as a natural complement to the world of IoT. It has exceptional predictive capabilities that help to provide quality and better offerings. This further allows industries to achieve a competitive edge in entrepreneurship. Today, you will find that AI machine learning capabilities have been incorporated into different industrial platforms including;
- Microsoft Azure.
- GE Predix.
- PTG Thing Worx.
- IBM Watson IoT.
- Amazon AWS IoT among others.
Furthermore, it is possible for industrial IoT to take advantage of AI technology to add more value to IoT deployments that were not specifically designed with the advancements in mind. Often, IoT deployments generate constant data flow that helps machines to identify patterns that lead to increased profitability.
In addition, AI comes with useful features including;
- Sensor data monitoring to enhance operational efficiency.
- AI-based analytics for self-learning and it offers actionable insights to boost industrial productivity.
- Offers alerts and notifications in the event of operational anomalies.
- Comes with mobile-enabled features that extend applications to employees whenever there is a need for alerts.
- It also comes with a highly customized dashboard that provides more visibility into asset performance.
- It provides instant updates for tasks and workflow that also enhances control of equipment more remotely.
7. Research and Development
AI can also be used efficiently in research and development in industrial IoT. This is crucial for operations and maintenance department. This is because it helps in identifying possible errors and in employing the best technologies to ensure machines are fully operational. It also helps in product development and it testing such before it is implemented into full production.
Author Bio: Nasrullah Patel Co-founded Peerbits, one of the leading IoT app development company the USA, in 2011 which provides Blockchain app development services. His visionary leadership and flamboyant management style have yield fruitful results for the company. He believes in sharing his strong knowledge base with a learned concentration on entrepreneurship and business. Web: https://www.peerbits.com
Author Bio: More on this topic: Will the IoT Be Secure? 3 Factors That Impact Security (Part 2 of 5)
