Smartphone Energy Consumption

Get the key measurement, modeling, and analytical tools for developing energy-aware and efficient systems and applications with this practical guide.

Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size

This book constitutes the refereed proceedings of the International Conferences on Security Technology, SecTech 2012, on Control and Automation, CA 2012, and CES-CUBE 2012, the International Conference on Circuits, Control, Communication, Electricity, Electronics, Energy, System, Signal and Simulation; all held in conjunction with GST 2012 on Jeju Island, Korea, in November/December 2012. The papers presented were carefully reviewed and selected from numerous submissions and focus on the various aspects of security technology, and control and automation, and circuits, control, communication, electricity, electronics, energy, system, signal and simulation.

This book constitutes the thoroughly refereed post-conference proceedings of the Fourth International Conference on Mobile Computing, Applications, and Services (MobiCASE 2012) held in Seattle, Washington, USA, in October 2012. The 18 revised full papers presented together with 9 revised poster papers were carefully reviewed and selected from 51 submissions. The conference papers are organized in five topical sections, covering mobile application development, multi-dimensional interactions, system support and architecture, mobile applications, and mobile services.

The dramatic progress of smartphone technologies has ushered in a new era of mobile sensing, where traditional wearable on-body sensors are being rapidly superseded by various embedded sensors in our smartphones. For example, a typical smartphone today, has at the very least a GPS, WiFi, Bluetooth, triaxial accelerometer, and gyroscope. Alongside, new accessories are emerging such as proximity, magnetometer, barometer, temperature, and pressure sensors. Even the default microphone can act as an acoustic sensor to track noise exposure for example. These sensors act as a ""lens"" to understand the user's context along different dimensions. Data can be passively collected from these sensors without interrupting the user. As a result, this new era of mobile sensing has fueled significant interest in understanding what can be extracted from such sensor data both instantaneously as well as considering volumes of time series from these sensors. For example, GPS logs can be used to determine automatically the significant places associated to a user's life (e.g., home, office, shopping areas). The logs may also reveal travel patterns, and how a user moves from one place to another (e.g., driving or using public transport). These may be used to proactively inform the user about delays, relevant promotions from shops, in his ""regular"" route. Similarly, accelerometer logs can be used to measure a user's average walking speed, compute step counts, gait identification, and estimate calories burnt per day. The key objective is to provide better services to end users. The objective of this book is to inform the reader of the methodologies and techniques for extracting meaningful information (called ""semantics"") from sensors on our smartphones. These techniques form the cornerstone of several application areas utilizing smartphone sensor data. We discuss technical challenges and algorithmic solutions for modeling and mining knowledge from smartphone-resident sensor data streams. This book devotes two chapters to dive deep into a set of highly available, commoditized sensors---the positioning sensor (GPS) and motion sensor (accelerometer). Furthermore, this book has a chapter devoted to energy-efficient computation of semantics, as battery life is a major concern on user experience.

DS RT 2019 serves as a forum for simulationists from academia, industry and research labs, for presenting recent research results in Distributed Simulation and Real Time Applications DS RT 2019 targets the growing overlap between large distributed simulations and real time applications, such as such as mirror world simulations and collaborative virtual environments The conference features prominent invited speakers as well as papers by top researchers in the field DS RT 2019 will include contributed technical papers, invited papers, and panel discussions

This book describes the implementation of green IT in various human and industrial domains. Consisting of four sections: “Development and Optimization of Green IT”, “Modelling and Experiments with Green IT Systems”, “Industry and Transport Green IT Systems”, “Social, Educational and Business Aspects of Green IT”, it presents results in two areas – the green components, networks, cloud and IoT systems and infrastructures; and the industry, business, social and education domains. It discusses hot topics such as programmable embedded and mobile systems, sustainable software and data centers, Internet servicing and cyber social computing, assurance cases and lightweight cryptography in context of green IT. Intended for university students, lecturers and researchers who are interested in power saving and sustainable computing, the book also appeals to engineers and managers of companies that develop and implement energy efficient IT applications.

This book constitutes the proceedings of the 7th International Conference on Mobile Computing, Applications, and Services (MobiCASE 2015) held in Berlin, Germany, in November 2015. The 16 full and 4 poster papers were carefully reviewed and selected from 43 submissions, and are presented together with 4 papers from the First Workshop on Situation Recognition by Mining Temporal Information (SIREMETI 2015). The conference papers cover the following topics: intelligent caching, activity recognition and crowdsourcing, mobile frameworks, middleware, interactive applications and mobility.