In recent years, we have seen the definitive breakthrough of artificial intelligence, especially thanks to the popularity of ChatGPT. IoT devices are also increasingly using AI. ‘Artificial Intelligence of Things’ (AIoT) not only analyses the data collected by IoT devices, but also translates it into actions to make processes run more efficiently. For example, AIoT can optimise route planning in logistics based on real-time traffic information, or detect early warning signs for medical intervention in healthcare.
AI will be applied in IoT in several ways:
● Generative AI: Generative AI is used to design complex infrastructure solutions and create simulations that mimic real-world scenarios, such as digital twins. These virtual copies of physical systems help test and optimize different scenarios without having to make actual physical changes.
● Predictive maintenance : AI models predict the maintenance needs of industrial machines by continuously monitoring performance data. Companies use this technology to prevent breakdowns, save costs and increase efficiency. In the transportation industry, for example, these models can predict when trucks need maintenance and thus prevent unexpected downtime.
● Edge computing for real-time analytics: ‘AI on the edge’ enables AI models to run directly on the IoT devices themselves. Data is analyzed locally, enabling real-time insights and direct actions. An example of this is the local processing of camera images. This makes it possible, for example, to adapt the operation of traffic lights to the current traffic flows.
● AI-driven security : AI plays a crucial role in protecting IoT devices from cyber threats. Applications include advanced threat modeling, systems that quickly respond to attacks by recognizing anomalies in network behavior, and techniques to detect and neutralize threats early.