Development of embedded hardware systems with edge AI

The growing volume of data worldwide is bringing new challenges in data processing. Traditionally, the information generated at the data source is sent to the cloud for processing. However, this approach has several disadvantages: from potential security breaches when handling sensitive data to high energy consumption in data centers and time delays in data transmission and processing, which can be particularly problematic in critical applications.

To meet these challenges, data processing is increasingly shifting from the cloud to the edge. This decentralized approach enables faster and more secure data processing.

Fraunhofer IZM develops embedded hardware systems tailored specifically for the use of artificial intelligence that optimize the efficiency and performance of data processing at the source.

• Increased data security and privacy: Since data is processed locally, the risk of data leaks and unauthorized access is reduced.
• Lower latency and increased efficiency: Processing directly at the point of origin results in faster response times and optimizes workflow.
• Reduced energy consumption: Edge AI minimizes energy requirements by sending less data to the cloud, which is both economical and environmentally friendly.
• Cost savings: Significant savings can be achieved by reducing bandwidth requirements and the need for cloud resources.
• Scalability for a wide range of applications: From real-time inventory management to automated systems, edge AI can be flexibly adapted and scaled to meet different requirements.