Virtual Design Of An Audio Lifelogging System

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.

While it may be attractive to view sensors as simple transducers which convert physical quantities into electrical signals, the truth of the matter is more complex. The engineer should have a proper understanding of the physics involved in the conversion process, including interactions with other measurable quantities. A deep understanding of these interactions can be leveraged to apply sensor fusion techniques to minimize noise and/or extract additional information from sensor signals. Advances in microcontroller and MEMS manufacturing, along with improved internet connectivity, have enabled cost-effective wearable and Internet of Things sensor applications. At the same time, machine learning techniques have gone mainstream, so that those same applications can now be more intelligent than ever before. This book explores these topics in the context of a small set of sensor types. We provide some basic understanding of sensor operation for accelerometers, magnetometers, gyroscopes, and pressure sensors. We show how information from these can be fused to provide estimates of orientation. Then we explore the topics of machine learning and sensor data analytics.

The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources. In addition, the use of heterogeneous sensing nodes provides a diversity of information that also enhances estimation performance. This work reviews cognitive systems and presents a cognitive fusion framework for sequential state estimation using adaptive configuration of heterogeneous sensing nodes and heterogeneous data fusion. This work also provides an application of cognitive fusion to the sequential estimation problem of target tracking using foveal and radar sensors.

Blurring is almost an omnipresent effect on natural images. The main causes of blurring in images include: (a) the existence of objects at different depths within the scene which is known as defocus blur; (b) blurring due to motion either of objects in the scene or the imaging device; and (c) blurring due to atmospheric turbulence. Automatic estimation of spatially varying sharpness/blurriness has several applications including depth estimation, image quality assessment, information retrieval, image restoration, among others. There are some cases in which blur is intentionally introduced or enhanced; for example, in artistic photography and cinematography in which blur is intentionally introduced to emphasize a certain image region. Bokeh is a technique that introduces defocus blur with aesthetic purposes. Additionally, in trending applications like augmented and virtual reality usually, blur is introduced in order to provide/enhance depth perception. Digital images and videos are produced every day in astonishing amounts and the demand for higher quality is constantly rising which creates a need for advanced image quality assessment. Additionally, image quality assessment is important for the performance of image processing algorithms. It has been determined that image noise and artifacts can affect the performance of algorithms such as face detection and recognition, image saliency detection, and video target tracking. Therefore, image quality assessment (IQA) has been a topic of intense research in the fields of image processing and computer vision. Since humans are the end consumers of multimedia signals, subjective quality metrics provide the most reliable results; however, their cost in addition to time requirements makes them unfeasible for practical applications. Thus, objective quality metrics are usually preferred.

The sensor cloud is a new model of computing paradigm for Wireless Sensor Networks (WSNs), which facilitates resource sharing and provides a platform to integrate different sensor networks where multiple users can build their own sensing applications at the same time. It enables a multi-user on-demand sensory system, where computing, sensing, and wireless network resources are shared among applications. Therefore, it has inherent challenges for providing security and privacy across the sensor cloud infrastructure. With the integration of WSNs with different ownerships, and users running a variety of applications including their own code, there is a need for a risk assessment mechanism to estimate the likelihood and impact of attacks on the life of the network. The data being generated by the wireless sensors in a sensor cloud need to be protected against adversaries, which may be outsiders as well as insiders. Similarly, the code disseminated to the sensors within the sensor cloud needs to be protected against inside and outside adversaries. Moreover, since the wireless sensors cannot support complex and energy-intensive measures, the lightweight schemes for integrity, security, and privacy of the data have to be redesigned. The book starts with the motivation and architecture discussion of a sensor cloud. Due to the integration of multiple WSNs running user-owned applications and code, the possibility of attacks is more likely. Thus, next, we discuss a risk assessment mechanism to estimate the likelihood and impact of attacks on these WSNs in a sensor cloud using a framework that allows the security administrator to better understand the threats present and take necessary actions. Then, we discuss integrity and privacy preserving data aggregation in a sensor cloud as it becomes harder to protect data in this environment. Integrity of data can be compromised as it becomes easier for an attacker to inject false data in a sensor cloud, and due to hop by hop nature, privacy of data could be leaked as well. Next, the book discusses a fine-grained access control scheme which works on the secure aggregated data in a sensor cloud. This scheme uses Attribute Based Encryption (ABE) to achieve the objective. Furthermore, to securely and efficiently disseminate application code in sensor cloud, we present a secure code dissemination algorithm which first reduces the amount of code to be transmitted from the base station to the sensor nodes. It then uses Symmetric Proxy Re-encryption along with Bloom filters and Hash-based Message Authentication Code (HMACs) to protect the code against eavesdropping and false code injection attacks.

Software development is hard, but creating good software is even harder, especially if your main job is something other than developing software. Engineer Your Software! opens the world of software engineering, weaving engineering techniques and measurement into software development activities. Focusing on architecture and design, Engineer Your Software! claims that no matter how you write software, design and engineering matter and can be applied at any point in the process. Engineer Your Software! provides advice, patterns, design criteria, measures, and techniques that will help you get it right the first time. Engineer Your Software! also provides solutions to many vexing issues that developers run into time and time again. Developed over 40 years of creating large software applications, these lessons are sprinkled with real-world examples from actual software projects. Along the way, the author describes common design principles and design patterns that can make life a lot easier for anyone tasked with writing anything from a simple script to the largest enterprise-scale systems.

Along with the introduction of technology in nearly every facet of human life comes the question of the ethical side of using technology to improve the human condition, whether that be physically or mentally. The capabilities of human enhancement technologies have created a dual-sided approach to discussing human enhancement: the critical approach of attempting to reach human perfection and the ethics within that idea and the endless capabilities of technology that have greatly impacted the medical field. It is essential to discuss both aspects within these emerging technologies, whether as separate entities or as cohesive units. Ranging from disease detection and treatment to implants and prosthetics to robotics and genetic engineering, human enhancement technologies are widespread and multi-purposed. By going beyond the capabilities of human hands, these technologies have propelled modern medicine and healthcare to new levels that have allowed humans to face new treatments or assistive technologies not seen before. The Research Anthology on Emerging Technologies and Ethical Implications in Human Enhancement covers the primary technologies and tools being used in medicine and healthcare along with discussions on the ethics of enhancing the human body. Topics covered include prosthetics and implants, robotics, human disorders/diseases and treatments and smart technologies, along with law and theory. This publication serves as a valuable reference work for doctors, medical professionals, researchers, students, professionals, and practitioners involved in fields that include ethics, medicine, computer science, robotics, genetics, assistive technologies, nanotechnology, biomedical engineering, and biotechnology.

Tracking the evolution of digital technology is no easy task; changes happen so fast that keeping pace presents quite a challenge. This is, nevertheless, the aim of the Digital Enlightenment Yearbook. This book is the third in the series which began in 2012 under the auspices of the Digital Enlightenment Forum. This year, the focus is on the relationship of individuals with their networks, and explores “Social networks and social machines, surveillance and empowerment”. In what is now the well-established tradition of the yearbook, different stakeholders in society and various disciplinary communities (technology, law, philosophy, sociology, economics, policymaking) bring their very different opinions and perspectives to bear on this topic. The book is divided into four parts: the individual as data manager; the individual, society and the market; big data and open data; and new approaches. These are bookended by a Prologue and an Epilogue, which provide illuminating perspectives on the discussions in between. The division of the book is not definitive; it suggests one narrative, but others are clearly possible. The 2014 Digital Enlightenment Yearbook gathers together the science, social science, law and politics of the digital environment in order to help us reformulate and address the timely and pressing questions which this new environment raises. We are all of us affected by digital technology, and the subjects covered here are consequently of importance to us all.