TY - GEN A1 - Segabinazzi Ferreira, Raphael A1 - George, Nevin A1 - Chen, Junchao A1 - Hübner, Michael A1 - Krstic, Milos A1 - Nolte, Jörg A1 - Vierhaus, Heinrich Theodor T1 - Configurable Fault Tolerant Circuits and System Level Integration for Self-Awareness T2 - Proceedings of the Work in Progress Session held in connection with SEAA 2019, the 45th EUROMICRO Conference on Software Engineering and Advanced Applications and DSD 2019, the 22nd EUROMICRO Conference on Digital System Design N2 - Scaling minimum features of ICs down to the 10nm- area and below has allowed high integration rates in electronics. Scaling at supply voltages of 1V and below also implies a rising level of stress which drives aging effects that reduce switching speed and the expected life time. Additionally, vulnerability from particle radiation is increased. Hence, fault detection and on- line correction become a must for many applications. However, not only fault tolerance but self-awareness becomes also an advantage. Provided that by being aware of its own healthy state allow optimized configurations regarding system operation modes and configurable hardware mechanism. This paper shows a preliminary work in a configurable circuit and explores its configuration possibilities when integrated into a complete system. Y1 - 2019 SN - 978-3-902457-54-7 U6 - https://doi.org/10.26127/BTUOpen-5050 PB - SEA-Publications CY - Kallithea, Chalkidiki (Greece) ER - TY - GEN A1 - Segabinazzi Ferreira, Raphael A1 - Nolte, Jörg A1 - Vargas, Fabian A1 - George, Nevin A1 - Hübner, Michael T1 - Run-time Hardware Reconfiguration of Functional Units to Support Mixed-Critical Applications T2 - IEEE Latin American Test Symposium (LATS), Maceió, Brazil Y1 - 2020 U6 - https://doi.org/10.1109/LATS49555.2020.9093692 ER - TY - GEN A1 - Shahin, Keyvan A1 - Rotta, Randolf A1 - Archila, Oscar A1 - Mykytyn, Pavlo A1 - Nattke, Matthias A1 - Reichenbach, Marc A1 - Nolte, Jörg A1 - Natarov, Roman T1 - A Modular Communication Architecture for Adaptive UAV Swarms T2 - 2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS) N2 - Small Unmanned Aerial Vehicles (UAVs) have vast application potential from industrial logistics and disaster monitoring to smart farming, for example, to create maps with Normalized Difference Vegetation Index (NDVI) cameras and AI-based image classification or the precision spot application of fertilizers. Operating multiple UAVs in parallel, including those with different specializations, enables efficient coverage of large areas. While existing research focused mainly on predefined flight formations for swarms or autonomous missions for single UAVs, the focus of this work is on multiple UAVs with individually adaptable missions. We derive communication system requirements from swarm coordination algorithms and present a respective design. The resulting modular architecture enables future research on autonomous adaptive UAV swarms and their use as flying sensor platforms. Y1 - 2023 SN - 979-8-3503-4647-3 SN - 979-8-3503-4648-0 U6 - https://doi.org/10.1109/COINS57856.2023.10189245 PB - IEEE CY - Berlin ER - TY - GEN A1 - Herglotz, Christian A1 - Jabłoński, Ireneusz A1 - Karnapke, Reinhardt A1 - Shahin, Keyvan A1 - Reichenbach, Marc T1 - Designing intelligent sensor networks : a comprehensive survey of sensing, edge AI, and 5G+/6G connectivity T2 - IEEE access N2 - With the advent of advanced transmission technologies, powerful neural-network architectures, and the availability of cheap sensing solutions, new paradigms for monitoring, controlling, and optimizing any automated system are appearing. While traditionally, sensors simply provided visual or acoustic feedback to human operators of such systems, nowadays, autonomous systems more and more rely on the automatic sensing and processing of such data to react and adapt their control mechanisms. In such complex control systems, sensor networks play a vital role. In this paper, we assess the state of the art in the three main components used within sensor networks: smart sensing elements, transmission technologies, and processing technologies. Concerning the latter, more and more artificial intelligence-based methods are developed and applied turning smart sensor networks into intelligent or even cognitive sensor networks. For the development of such sensing systems, a high variety of performance metrics could be important to the designer. This paper discusses the vast design space for intelligent sensor networks and provides guidance and directions on how to construct future intelligent sensor networks efficiently. KW - 5G, Sensor networks, Edge computing, Energy efficiency, KPIs, Design space, AI Y1 - 2025 U6 - https://doi.org/10.1109/ACCESS.2025.3615205 SN - 2169-3536 VL - 13 SP - 172306 EP - 172325 PB - IEEE CY - Piscataway, NJ ER -