Dirk Pesch

TL;DR: This paper considers an emerging non-wearable fall detection approach based on WiFi Channel State Information (CSI), which uses the conventional Short-Time Fourier Transform to extract time-frequency features and a sequential forward selection algorithm to single out features that are resilient to environment changes while maintaining a higher fall detection rate.

TL;DR: TS-LoRa is proposed, an approach that tackles overheads of LoRaWAN by allowing devices to self-organise and determine their slot positions in a frame autonomously and only one dedicated slot in each frame is used to ensure global synchronisation and handle acknowledgements.

TL;DR: TATUS, a ubiquitous computing simulator designed to maximize usability and flexibility in the experimentation of adaptive ubiquitous computing systems, is described, which is interfaced with a testbed for wireless communication domain simulation.

TL;DR: A framework for indoor location with the nearest-neighbour and particle filter are developed to evaluate predicted and measured fingerprints and a map-filtering technique is elaborated to take advantage of environment description.

TL;DR: A series of key enabling technologies from a range of domains, such as new materials, algorithms, and system architectures are outlined, envisioning that machine learning will play an instrumental role for advanced vehicular communication and networking.