Artificial intelligence (AI) is a rapidly growing field that involves the development of intelligent machines that can perform tasks that normally require human intelligence, such as learning, problem solving and decision making. In industry, AI is used to automate processes, increase efficiency and make better decisions.

One of the key benefits of AI in industry is automation. AI-driven robots and software can take over tasks that are repetitive, time-consuming or dangerous for humans, such as assembling products, inspecting equipment or monitoring hazardous environments. By automating these tasks, companies can save time and money while improving safety and accuracy.

AI can also be used to improve efficiency in various ways. For example, AI-powered algorithms can analyze large amounts of data to identify patterns and insights that would be difficult or impossible for humans to detect. This can help companies to optimize their processes, reduce waste and improve the quality of their products or services.

Another area in which AI plays a role in industry is decision-making. AI-supported systems can analyze data and make recommendations to humans on the best course of action.

Digital transformation and user interaction with various applications generate valuable usage data. Together with the operating data from sensors and machines (IIoT), this data forms the basis for identifying optimization potential and making predictions. However, the increasing complexity and volume of data is overwhelming traditional, rule-based systems. Self-learning models based on machine learning (ML), deep learning (DL) and artificial intelligence (AI), on the other hand, are able to fully exploit the data potential even with increasing complexity. Machine learning models learn the correlations between different sensor values and process data and recognize anomalies, for example, that a programmer would not have been able to teach the machine due to their large number and diversity. Thanks to the possibility of real-time monitoring, unknown problems can also be identified in good time and expensive failures avoided. The rapid further development of specialized hardware for solving AI tasks opens up the possibility of economical use in many areas of production today.

In the automotive industry and many other sectors, quality requirements are increasing rapidly. The components supplied must be absolutely flawless because they must meet the highest reliability standards. The verifiably documented 100% quality of the components and complete traceability is therefore an indispensable mandatory requirement. Small defects in components could cause a stop in subsequent production and assembly or, in an even worse scenario, trigger a recall in the automotive industry, for example. This can quickly lead to heated disputes about responsibilities, costs and other consequences.

Conventional approaches with rule-based image processing quickly reach their limits if the image data to be analyzed varies too frequently and the differences are difficult or impossible to map using algorithms. Robust automation cannot be realized in such cases due to an inflexible set of rules. Even if it is a task that is supposedly easy for humans to solve. Artificial intelligence (AI) opens up new fields of application for camera technology and image processing. It makes it possible to solve tasks where classic, rule-based image processing reaches its limits. Hardware, software, infrastructure, knowledge and support are optimally coordinated. Unidor provides you with all the components you need to start implementing your own AI applications straight away. This makes it particularly easy to get started with deep learning-based image processing.