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If we look at them separately, the Internet of Things (IoT) and Artificial Intelligence (AI) are powerful technologies and if we combine them, we get AIoT, Artificial Intelligence Of Things. So AIoT is where AI and IoT meet, bringing intelligence to the forefront. But how does this union come about?
Artificial Intelligence (AI) brings value to The Internet of Things (IoT) through machine learning capabilities, transforming data into useful information, while IoT adds value to AI through connectivity and data sharing.
AIoT (Artificial Intelligence of Things) refers to the union of the Internet of Things (IoT) on the one hand and artificial intelligence (AI) on the other. In other words, AIoT opens the door to a new world in which connected objects now benefit from artificial intelligence techniques. Thanks to AI, IoT has machine learning capabilities. On the other hand, AI benefits from the IoT's information gathering and sharing capabilities.
With it, Artificial Intelligence integrates components such as chipsets, connected to one or more IoT networks. The mutual benefit of these two technologies allows to have a different vision and expand the field of action. Moreover, thanks to the union it is possible to analyze Big Data, make decisions and act on data without human intervention, optimizing processes.
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This is the challenge of the transition from IoT to AIoT. By leveraging the machine learning capabilities of artificial intelligence, the Internet of Things has increased its performance and personalization. Some time ago, connected objects did not understand the value of the information collected and had great difficulty learning from each other. The conclusion was that it was still difficult for connected objects to adapt in real time to a real-life situation.
By leveraging AI and analytics, connected objects can now adapt their decisions within autonomous systems. The applications of AIoT are, in fact, very numerous and work with a large multitude of activity sectors. In the field of energy, for example, AIoT makes it possible to make the operation of a wind turbine completely autonomous, with an orientation of the angle of the blades according to weather conditions, without human intervention.
Brought in to replace home automation, the smart home is one of those sectors that fully benefit from the advent of AIoT. Indeed, the contribution of AI to connected objects allows multiple applications in the development of a smart home. In all areas (energy saving, security, comfort, etc.), AIoT significantly increases the performance of the smart home.
Most companies have invested heavily in AIoT to offer consumers increasingly personalized experiences. Xiaomi announced in January 2019 that it wanted to invest $1.5 billion in this technology within five years. At Google or Apple, devices can, for example, adapt the heating level of the home by themselves, according to external weather conditions and/or according to your habits.
AIoT is a powerful and important tool for many applications. Here are some examples of this:
A camera system connected to a computer can use facial recognition to identify customers as they walk through the store door. It then gathers information about customers, such as their gender or product tastes, and analyzes the data to predict their behavior.
This report will provide information to make decisions about store operations, marketing or optimal product placement. It will also improve cybersecurity, data processing and telecommunications.
In a smart city, there are several practical uses of AIoT, such as traffic monitoring by drones, as real-time monitoring can help smooth traffic flow, thus reducing traffic jams. When drones are deployed to survey a large area, they can transmit traffic data and then AI can analyze it.
This will enable decisions on the most efficient way to reduce traffic jams by adjusting speed limits and traffic light timing, all without human intervention.
It can be used to help monitor vehicles in a fleet, track vehicle maintenance or identify unsafe driver behavior. Thanks to devices such as GPS and other sensors combined with an artificial intelligence system, companies can better manage their fleet.
In addition, it is also used with autonomous vehicles, such as autopilot systems that use radar, sound, GPS and cameras to collect data on driving conditions, as for example in Tesla or Mercedes.
After this, the AI takes over the decision making on the data collected, enabling monitoring over time.
As used with autonomous vehicles, autonomous delivery robots or even drones are other clear examples of this technology. Equipped with sensors that gather information about the environment they pass through and make instant decisions on how to react, thanks to their onboard artificial intelligence platform.
This allows you to control your trip and adapt it if necessary or, in case of force majeure, to be able to react as soon as possible.
At this point, we ask ourselves....
The concept of AIoT is still new and we know that what is essential is to distinguish between what is currently possible and what is still far from being done. It will require continuous development as new forms of connectivity emerge and as AI advances gradually arrive.
In addition, a point to be further improved is the protection of privacy in potentially insecure devices such as toys, smart watches, kitchen robots, robot vacuum cleaners, televisions, vehicles... as it is on the threshold of integration into people's lives and there are brands that still do not comply with privacy policies.
That said, through the European Data Strategy published in February 2020, the European Union wants to be a leader and have a data-driven society. This will be possible thanks to the European Data Protection Act proposed in February 2022, which aims to provide more data for use and establish rules on who can access what data and for what purposes.
Finally, this technology also gives rise to new professions, such as IoT developer and other jobs that have been evolving thanks to the irruption of this technology, such as electronics stores or embedded software engineers.
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