Make the most of the common architectures used for deriving meaningful data from sensors. This
book provides you with the tools to understand how sensor data is converted into actionable
knowledge and provides tips for in-depth work in this field. Making Sense of Sensors starts
with an overview of the general pipeline to extract meaningful data from sensors. It then dives
deeper into some commonly used sensors and algorithms designed for knowledge extraction.
Practical examples and pointers to more information are used to outline the key aspects of
Multimodal recognition. The book concludes with a discussion on relationship extraction
knowledge representation and management. In today's world we are surrounded by sensors
collecting various types of data about us and our environments. These sensors are the primary
input devices for wearable computers IoT and other mobile devices. The information is
presented in way that allows readers to associate theexamples with their daily lives for better
understanding of the concepts. What You'll Learn Look at the general architecture for sensor
based data Understand how data from common domains such as inertial visual and audio is
processed Master multi-modal recognition using multiple heterogeneous sensors Transition from
recognition to knowledge through relationship understanding between entities Leverage different
methods and tools for knowledge representation and management Who This Book Is For New college
graduates and professionals interested in acquiring knowledge and the skills to develop
innovative solutions around today's sensor-rich devices.
