Artificial Intelligence (AI) and the Internet of Things (IoT): Two technologies shaping ubiquitous digitalization. And when combined, they can unleash a revolutionary force and become a true game changer for IoT projects.
The terms AI or AI (Artificial Intelligence) describe specialized software that simulates intelligent behavior—for example, making independent decisions and solving problems in this way. The associated machine learning ensures that AI can continue to learn from newly collected data and information. In this way, it improves its approaches and decision criteria almost autonomously—every second.
Ovidiu Ursachi is our HK.SYSTEMS expert in this field: “I am a big fan of continuous learning—constantly trying to find new ways, come up with new solutions and ideas, and connect them. The flexible use of the latest IoT technologies such as AI and machine learning plays a crucial role here: Used correctly, they give us and our customers a significant competitive edge.”
Artificial intelligence makes connected things truly smart
Combining IoT and AI will make things truly exciting in the future, because it makes connected devices and objects even more useful. Experts refer to this development as the “Artificial Intelligence of Things,” or “AIoT” for short: It combines the sensor-, device-, and data-based infrastructure of the Internet of Things with the advantages of artificial intelligence. A promising synthesis that can make applications even more efficient and sustainable. The expected benefits are compelling:
- Predictive maintenance The foundation is a well-designed architecture and the intelligent use of machine learning algorithms: Both components specifically determine failure probabilities and generate reliable forecasts. Costly machine downtime is avoided while maintenance costs are reduced at the same time.
- Process chain optimization Collecting large volumes of manufacturing-related data is the key to “machine learning” here. The use of AI optimizes the manufacturing process, so that significantly less energy is required—offering major potential savings in resources and costs.
- Optical defect detection The intelligent analysis of image material using AI technology: A perfect solution for early defect detection.
- Fault prediction AI applications such as the “digital twin” make it possible to reliably predict surface damage in production environments. With this know-how, system settings can be adjusted in real time—so damage does not occur in the first place.
- Sustainable process chain planning Keyword: micro-manufacturing in medical technology and the automotive industry. The so-called “miniaturization” of production systems and production processes increases functionality.
- IoT data-based product development & retrofit planning Future generations and retrofits of products are systematically improved through insights gained from product usage and behavioral data. This is not only about data-driven identification of optimization potential, but also about targeted retrofit planning.
- Autonomous transport systems Efficient and automated transport systems lead to a wide range of improvements: process optimization, more flexible production, reduced waiting times, and increased productivity by enabling shorter time intervals.
- Sustainability analytics Machine learning and cloud technologies form an ideal combination for sustainable business and parallel competitive advantages: reduced CO2 emissions, lower costs, and reliable risk forecasts within the value chain.
Conclusion: Artificial intelligence—an indispensable component of successful IoT projects in the future
Connected things only become truly smart through the implementation of AI. They become smart devices that learn from their own activity and from one another. In this way, they continue to evolve and are increasingly able to make their own decisions. Through artificial intelligence, connected devices become steadily more autonomous and deliver more and more interpretable and usable data. This makes them increasingly valuable for companies of all sizes. Because companies draw targeted conclusions from these insights: They improve their products, optimize processes, and thus secure their long-term competitiveness in the global market.
In the future, AI and IoT will continue to converge: Smart devices will become more flexible—they will no longer function only within familiar structures, but will also be able to adapt to restructuring. Entire machine systems will transform into highly interconnected autonomous systems. Last but not least, the use of AI also makes interaction with machines increasingly natural: Intuitive human-machine communication and easy-to-use human-machine interfaces have long been part of many areas.
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