The Role of AI and Machine Learning in IoT App Capabilities

The Role of AI and Machine Learning in IoT App Capabilities

In the last few years, the Internet of Things has significantly changed how we live and do business. This technology relies on data collection, connectivity, and valuable insights to improve and simplify various daily processes.

Machine learning and artificial intelligence are inseparable parts of IoT apps, improving the connectivity and responsiveness of smart devices. Among others, through ML and AI, you can automate numerous complex processes that would otherwise take you hours, and even days, to finish.

While the technology is still developing, users can notice its enormous impact. Machine learning, for example, is vital for faster data analysis and the creation of predictive models. On the other hand, artificial intelligence can improve processes based on the new inputs that it acquires over time.

Nowadays, companies are racing to implement AI and ML in as many IoT apps as possible. Today, you can see this technology in healthcare, logistics, agriculture, retail, and many other industries. In this article, we explain how machine learning and artificial intelligence affect IoT software and what to expect in the future.

IoT and AI

As mentioned, AI can significantly improve the performance of various IoT devices. Even better, you can implement this technology with minimal technical requirements. In other words, an IoT device doesn’t have to be that complex to utilize artificial intelligence and machine learning.

One major benefit of AI is that it can understand how humans interact with each other. The technology is fantastic at recognizing our speech patterns allowing users to issue commands at a distance. What’s better, it can adjust to different languages, so you can always use your mother tongue when using an IoT device.

Another reason why all of this works is because the Internet of Things devices can collect enormous quantities of data. Given that IoT devices can communicate with each other, they can gather information from several sources helping users monitor numerous processes from a single dash.

Unfortunately, as the Internet of Things can only gather data but not interpret it, you need another technology. In other words, you need AI to implement the data previously collected within the IoT network. With artificial intelligence, each device can significantly improve its functionality and provide a better, more versatile service.

IoT and ML

Unlike artificial intelligence, machine learning can utilize the data to make predictions and establish patterns. Most importantly, it can make reasonable conclusions based on the insights it was fed. Together with AI, ML can continuously improve processes and acquire new “skills.”

The most important role of machine learning pertains to data analytics. With this functionality, companies can acquire enormous quantities of data properly categorized for their particular industry. Machine learning systems can convert this data into real-world insights that can be utilized for various business purposes.

Many IoT devices use machine learning for maintenance purposes. By reading data gathered from sensors, an IoT app can assess the state of equipment. Based on that, the software can suggest the best time for scheduled maintenance. That way, companies can improve performance while also optimizing maintenance routines.

In the last few years, there has been more and more emphasis on predictive analysis. This concept is valuable for all industries but shines for retail. With it, brands can gain insights about every potential customer and suggest products based on their preferences.

IoT, AI, and ML

While each of these concepts is extremely powerful, it doesn’t work on its own. For example, machine learning and artificial intelligence can’t give you real-time insights if they’re not connected to the internet (which is where IoT devices come into play). Similarly, while machine learning systems can gather data, they might struggle to utilize it in a real-world situations.

Only when you combine the three together can you maximize results for your business. If you wish to learn more about the potential benefits and IoT development process, click here!

IoT apps in practice

IoT devices are interconnected via the internet. Various sensors, digital accessories, and home devices gather information from their surroundings and “feed” data into the network, all of which are stored within a centralized device. When needed, each device within the network can access this data and use it for its specific purposes.

Developers nowadays use this joint technology to create devices for various industries. IoT apps have a wide application and shine for tasks that require heavy automation or reliance on sensors. Here are a few most common ways to use this software:

Manufacturing

Manufacturing was always predicated on streamlining and automation. Using robotics to build cars and other machines isn’t a new concept; it’s something that companies have been developing for several decades.

Nowadays, brands use IoT apps to manage numerous processes from a single dashboard. Given that the production process can be extremely complex, these devices use sensors to track real-time changes. With IoT, management can analyze production floor operations, automate processes, and predict results.

Logistics

Just about any company can benefit from improved logistics. IoT devices allow companies to monitor vehicles and drivers’ behavior and pinpoint potential issues. For example, an IoT app can warn a driver about bad weather or road works.

With these devices, management knows where each vehicle is at all times. This makes it easier to predict delivery times, which is vital when working on strict deadlines. Ultimately, better logistics leads to less time spent on the road and higher customer satisfaction.

Consumer behavior

The combination of machine learning and artificial intelligence has been sending shockwaves throughout the retail industry. The combined technology tracks user behavior over time to predict consumer habits.

Brands can now track all web interactions, including visits to certain sites, clicks on social media posts, and other forms of interactions. Based on that, IoT apps can determine what does a person like and dislike. So, the next time they visit a store, they are shown a list of items that might interest them based on their past browsing.