Blending AI in the Internet of Things
Tags: data, datascience, iot, aiot
Published: 2022-10-21 06:24:30

Data Science and Artificial intelligence (AI) are two of the most trending buzz word in the technology world. And the infusion of these two technical aspects in IoT will no doubt leverage certain essential benefits like predicting future circumstances and increasing decision-making capabilities.

Here we will show why AI and IoT need to work together. But, before coming straight to the topic, let's understand the basics of both concepts quickly.

## **What is IoT?**

IoT, or the Internet of Things, is a massive network between multiple devices that lets those devices communicate and exchange information. The concept of a smart home, for example, is only possible due to [IoT](https://en.wikipedia.org/wiki/Internet_of_things), where all the devices, right from toothbrushes to electronic appliances, will be connected.

## **What is AI?**

The concept of AI refers to a system that can mimic the working of human beings and even improve themselves based on historical data. Self-driving cars, Alexa, and Siri in our life are examples of applications of AI.  

## **Why IoT and AI – Data Science Together Make the Perfect Match?**

As stated earlier, AI and IoT are definitely at the top of the list when discussing trending technologies. Also, according to Forbes, the number of IoT connections is expected to reach 3.5 billion in 2023.  

Combining both AI and IoT creates a perfect match. The concept of IoT manages the devices in the network, while AI focuses on making the devices learn from their experience. The fusion of these technologies lets machines and gadgets make the most intelligent decisions without human intervention. 
 

## **How AI Enhances IoT-Based Systems?**

The application of IoT opens up the door to various opportunities when used with the concept of AI. The success in the same will result in creating an advanced level of automation that won't require even the slightest human intervention. Let's understand the application with the help of an example.

In case when a loaded truck arrives at a warehouse with goods, a warehouse worker will insert a code and allow the truck to enter the premises. This can be automated with the help of AI and IoT, and the usage of the bar code concept will provide access to the truck automatically. With this, there won't be a requirement for an extra worker at a gate, and the truck would not be required to stop and wait for permission. 

With more such uses, the question isn't whether or not to use AI but to what extent AI can be used with IoT to maximize the benefits. With this, we'll see some of the exclusive benefits of AI-enabled IoT systems. 

## **Why Use AI-Enabled IoT Systems?**

With each passing day, these two concepts are gaining more and more importance in the tech world. The application of Data Science and AI in IoT provides incredible benefits, some of which are mentioned below:  

### **Increased Efficiency**

The vast amount of data in IoT devices can be easily analyzed by [data science and artificial intelligence](https://fingertips.co.in/data-science-with-ai-certification-course) algorithms like linear, logistic regression, random forest, and much more. Data science and artificial intelligence identify important hidden patterns which are difficult to locate by humans on such massive datasets. 

Finally, with the help of AI, IoT can conclude which methods are time-consuming and need updates. This will ultimately help in increasing the overall operational efficiency.  

### **Reliable Disaster Recovery**
AI-enabled IoT systems provide an additional layer of security to the devices. The devices are prone to various risks like financial loss, cyber-attacks, etc., which can be identified by AI-enabled IoT systems well in advance. 

This detection not only helps avoid the risk but also helps in easy recovery from risk if the situation can't be avoided. Thus every business enterprise should have AI-enabled IoT systems built to prevent possible risk situations. 

### **Better Scalability Prospects**
The most common IoT devices are mobile phones and computers. These two devices generate a massive data set that gets communicated via the network. Due to the amount of data, this might become a slow process. 
The AI-enabled IoT systems involve low-cost sensors that analyze and compress the devices' data. Due to data science and artificial intelligence algorithms, the data size reduces, allowing more devices to connect and increasing scalability.
 

### **Reduced Overhead Expenditure**
Due to certain benefits like increased operational efficiency, early disaster recovery, and increased scalability, AI-enabled IoT systems helps in saving certain overhead expenditure. 
The implementation of such intelligent devices helps in saving cost as well as efforts on handling the data concerns and problems. 

With this being said, let's see one of the important real-life implications of AI-enabled IoT systems, i.e., self-driving cars. 

### **Real-Life Implications**
AI-enabled IoT devices are already changing the working of various sectors like retail, manufacturing, wholesale, autonomous vehicles, and many more. Below we'll see some of the implications of the concept.

### **Self-Driving Cars**

The concept of self-driving cars is thrilling and exciting for everyone. The idea is booming due to IoT, data science, and artificial intelligence. It successfully predicted the movements of a driver and a pedestrian in multiple situations, which helped them make accurate and vital decisions. AI-enabled IoT devices also consider other essential factors like speed, time, road conditions, weather, etc. 

Not only self-driving cars but AI-enabled IoT systems also help in the whole automotive industry by predicting failing parts, detecting defective parts, a reminder for maintenance required, etc. 

### **Manufacturing Sector**
Sensor devices already collect large volumes of data on the production process in most plants in highly industrialized nations. IoT makes industrial and production robots intelligent by enabling them to recognize trends and foresee damage before they occur. 
For every manufacturer, preventative repair and supply disruption are probably the largest source of money saves.

### **Retail Sector**

Retail consumers' travels to the checkout line can be mapped using the information obtained by face detection cameras and other sensors. Data like this can be used by management to plan store layouts to maximize customer experience, predict the likelihood of staff shortages, as well as provide insights into consumer behavior in the store.

## **Final Thoughts**
All in all, AI, when applied to IoT, creates a win-win situation. The concepts of data science and artificial intelligence make sense of the vast data sets to make the devices smarter for IoT. 

The world will function as a vast collection of interconnected [data-gathering systems](https://www.techopedia.com/definition/11311/data-collection-system-dcs) in an AIoT future that will automatically improve upon one another by identifying patterns and finding connections that would need months or even years of cooperation and study on our part.