Virtual Design of an Audio Lifelogging System: Tools for IoT Systems (Synthesis Lectures on Algorithms and Software in Engineering)

The availability of inexpensive, custom, highly integrated circuits is enabling some very powerful systems that bring together sensors, smart phones, wearables, cloud computing, and other technologies. To design these types of complex systems we are advocating a top-down simulation methodology to identify problems early. This approach enables software development to start prior to expensive chip and hardware development. We call the overall approach virtual design. This book explains why simulation has become important for chip design and provides an introduction to some of the simulation methods used. The audio lifelogging research project demonstrates the virtual design process in practice.

The goals of this book are to:

• explain how silicon design has become more closely involved with system design;
• show how virtual design enables top down design;
• explain the utility of simulation at different abstraction levels;
• show how open source simulation software was used in audio lifelogging.

The target audience for this book are faculty, engineers, and students who are interested in developing digital devices for Internet of Things (IoT) types of products.

Brian Mears has a PhD from City University, London. He worked in the computer industry in the UK, at CERN in Geneva, at Bell Labs designing integrated circuits for audio compression, and at Intel Corporation for 29 years where he was a silicon architect and manager for embedded 32-bit microcontrollers, multi-core digital signal processors, and smartphone SoCs. His experience with complex SoC chip design led him to employ the modeling and simulation techniques found within.Mohit Shah received his PhD from Arizona State University in 2015. He cofounded Genesis Artificial Intelligence, which specializes in advanced system and application design. His research interests lie in speech processing and analysis methods, covering both DSP and machine-learning related aspects. His prior work in industry included internships at Intel and Palo Alto Research Center (Xerox PARC).