Internet of Things (IoT) technologies have contributed to innovating the industrial sectors of manufacturing, energy, and utilities, helping businesses make the most of their operational data. The IoT, with the advent of home automation, and connected devices is improving people’s quality of life. The next milestone is its union with Artificial Intelligence (AI), resulting in even better-performing networks of devices. Let’s learn more about AIoT and its evolution together.
What is AIoT?
Artificial Intelligence of Things (AIoT) is the combination of Artificial Intelligence (AI) technologies and Internet of Things (IoT) infrastructure. The goal of AIoT is to create more efficient IoT operations, improve human-machine interactions, and enhance data management and analysis.
To get a clearer view of AIoT, we need to start with what IoT is. The Internet of Things (IoT) is the collection of a network of physical devices connected through the use of sensors, software, and technologies. The purpose is to enable these devices to exchange data and information.
As for Artificial Intelligence, on the other hand, we talk about the science of training systems to emulate human activities through learning and automation.
Therefore, the combination of AI and IoT means that devices can analyze data and make decisions without direct human involvement.
AIoT is transformative and mutually beneficial for both types of technology, as AI adds value to IoT through machine learning capabilities and improved decision-making, while IoT adds value to AI through connectivity, signaling, and data exchange.
What are the benefits of adopting AIoT?
AIoT is an efficient solution for companies, which are increasingly adopting this technology. Prominent among the many benefits is increased revenue.
According to an IDC study sponsored by SAS with support from Intel and Deloitte, 34% of the companies involved in the study that had adopted AIoT technologies did so specifically to increase their revenue.
Other benefits include:
- Increased operational efficiency, where AIoT devices can analyze data to reveal patterns and insights to make the system more efficient.
- Adjustment capabilities, where data can be leveraged to detect faults allowing the system to make necessary adjustments
- Data analysis is performed by AI, so employees can focus on other tasks while saving time and costs
- Scalability is the increase in the number of devices connected to an IoT system that can be scaled up to optimize existing processes or introduce new functionality.
AIoT use cases
As we have seen, the combination of the Internet of Things and intelligent systems makes AIoT a powerful and important tool for many applications. AIoT represents a very useful tool for businesses, but not only. There are many use cases in everyday life as well, let’s find out together which ones.
In marketing, AIoT can be leveraged for smart retail. Through a camera system, equipped with computer vision, facial recognition can be used to recognize customers when they enter the store.
The system will be able to collect a large amount of customer data, such that it can accurately predict consumer behavior, and then use that information to define marketing strategies.
Traffic monitoring with drones
Several uses of AIoT can be exploited in smart cities. Among all of them, a practical example is the possibility of monitoring traffic with drones. This will enable changes to the flow of traffic in real time, such as reducing its intensity.
Drones, which are deployed to monitor a very large area, will collect traffic data that AI-directly the device can analyze by determining how to reduce congestion, change speed limits, or the timing of traffic lights without having to involve any humans.
Another area where Artificial Intelligence and the Internet of Things intersect is in smart offices. Through a network of environmental sensors, the presence of staff within the office can be detected and the temperature and lighting needed can be adjusted accordingly with the aim of greater energy savings.
Another use case in smart offices is controlling office access through facial recognition. The combination of connected cameras and AI that can compare images taken in real-time can determine the presence of employees in the office without them even punching in.
Enterprise fleet management and autonomous vehicles
Monitoring vehicles in a corporate fleet is significantly easier with AIoT. Fuel costs can be reduced, vehicle maintenance can be tracked, and drivers’ driving behavior can be verified.
But not only that, but AIoT today is also being used for autonomous vehicles, with autopilot systems that depend on IoT devices such as radar, GPS, or cameras combined with AI making decisions based on transmitted data.
Using AIoT effectively in business and customer service models will enable immediate and lasting competitive advantages. Click To Tweet
The future of AIoT
These are just a few of the AIoT use cases, but that does not detract from the fact that we may discover more and more in the future. Through AI integration, the IoT creates a significantly more accurate and intelligent system.
In addition, AIoT continues its development through the inclusion of 5G, which is designed to enable faster data transfer from IoT devices.
AIoT could thus help solve existing operational problems, making business and daily life processes easier and more effective.