Recent Advances in Embedded Computing, Intelligence and Applications

The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems

Towards a Common Software/Hardware Methodology for Future Advanced Driver Assistance Systems

The European research project DESERVE (DEvelopment platform for Safe and Efficient dRiVE, 2012-2015) had the aim of designing and developing a platform tool to cope with the continuously increasing complexity and the simultaneous need to reduce cost for future embedded Advanced Driver Assistance Systems (ADAS). For this purpose, the DESERVE platform profits from cross-domain software reuse, standardization of automotive software component interfaces, and easy but safety-compliant integration of heterogeneous modules. This enables the development of a new generation of ADAS applications, which challengingly combine different functions, sensors, actuators, hardware platforms, and Human Machine Interfaces (HMI). This book presents the different results of the DESERVE project concerning the ADAS development platform, test case functions, and validation and evaluation of different approaches. The reader is invited to substantiate the content of this book with the deliverables published during the DESERVE project. Technical topics discussed in this book include:Modern ADAS development platforms;Design space exploration;Driving modelling;Video-based and Radar-based ADAS functions;HMI for ADAS;Vehicle-hardware-in-the-loop validation system

Parkinson's Disease Management through ICT

Parkinson's Disease (PD) is a neurodegenerative disorder that manifests with motor and non-motor symptoms. PD treatment is symptomatic and tries to alleviate the associated symptoms through an adjustment of the medication. As the disease is evolving and this evolution is patient specific, it could be very difficult to properly manage the disease.The current available technology (electronics, communication, computing, etc.), correctly combined with wearables, can be of great use for obtaining and processing useful information for both clinicians and patients allowing them to become actively involved in their condition.Parkinson's Disease Management through ICT: The REMPARK Approach presents the work done, main results and conclusions of the REMPARK project (2011 – 2015) funded by the European Union under contract FP7-ICT-2011-7-287677. REMPARK system was proposed and developed as a real Personal Health Device for the Remote and Autonomous Management of Parkinson’s Disease, composed of different levels of interaction with the patient, clinician and carers, and integrating a set of interconnected sub-systems: sensor, auditory cueing, Smartphone and server. The sensor subsystem, using embedded algorithmics, is able to detect the motor symptoms associated with PD in real time. This information, sent through the Smartphone to the REMPARK server, is used for an efficient management of the disease