An interdisciplinary research project is developing new technological approaches for better and more effective integration of artificial intelligence at the edges of IT networks. These developments could fuel future applications in industrial electronics, medical technology, and environmental monitoring. The project, called “InSeKT,” joins the Technical University of Applied Sciences Wildau, the Leibniz Institute for High Performance Microelectronics (IHP), and the Fraunhofer-Institute for Photonic Microsystems IPMS to develop new hardware, software, and sensor solutions. The project aims to enable complex calculations directly where the data is generated, for example at the sensor itself. At present, data processing with AI is often carried out via central cloud computing solutions. The data is calculated on central servers, which necessitates large amounts of data to be transmitted over long distances. As a result, data leaks can occur which creates opportunities for unauthorized third parties to attack. Decentralized data processing not only improves data protection, but also enables real-time capability of the systems, as data transmissions over long distances are avoided. The Integrated Silicon Systems branch of Fraunhofer IPMS is working on the functional expansion and integration of existing MEMS sensors for edge AI applications. Signal processing is integrated directly into the sensor and data can be collected directly where it is generated. The aim is to increase the adaptability of sensors to different application scenarios without having to replace the underlying hardware. An initial central area of development at Fraunhofer IPMS is gas analysis using ion mobility spectrometers (IMS). An IMS makes it possible to detect ionizable analyte substances directly in the air, even at very low concentrations. Existing approaches lack sufficient miniaturization. A first IMS demonstrator, which is based on a FAIMS (field asymmetric-waveform ion mobility spectrometry) approach, has flexible electrode spacing, making it possible to overcome this hurdle. Furthermore, the goal of a data-supported evaluation of photodetectors for the near-infrared wavelength range is being pursued. These are used, for example, in material analysis and recycling and even enable analysis through packaging. The focus lies on improving an Al-TiN-Si-Schottky detector component with cylindric pyramidal structures for a higher sensitivity and improved scalability by using cheaper materials. A third area deals with the adapted use of capacitive micromechanical ultrasonic transducers (CMUTs) for improved imaging. CMUTs are highly sensitive ultrasound receivers due to their size and capacitive operating principle. Signal evaluation close to the sensor would enable faster imaging. “Later on, it will be possible to carry out very precise analyses of hand movements using an ultrasound signal based on that of bats, as well as measuring blood sugar using ultrasound,” said Sebastian Meyer, head of the Integrated Silicon Systems department at Fraunhofer IPMS. The TH Wildau and the Leibniz IHP will then use the generated sensor data to train edge AI systems for fast and precise data processing. The results of the project will enable further steps towards more intelligent and compact sensor systems.