What this book covers

Chapter 1, Sensor Fundamentals, provides you a thorough understanding of the fundamentals and framework of Android sensors. It walks you through the different types of sensors and the sensor coordinate system in detail.

Chapter 2, Playing with Sensors, guides you through various classes, callbacks, and APIs of the Android Sensor framework. It walks you through a sample application, which provides a list of available sensors and their values and individual capabilities, such as the range of values, power consumption, minimum time interval, and so on.

Chapter 3, The Environmental Sensors – The Weather Utility App, explains the usage of various environment sensors. We develop a weather utility app to compute altitude, absolute humidity, and dew point using temperature, pressure, and relative humidity sensors.

Chapter 4, The Light and Proximity Sensors, teaches you how to use proximity and light sensors. It explains the difference between wakeup and non-wakeup  sensors and explains the concept of the hardware FIFO sensor queue. As a learning exercise, we develop a small application that turns on/off a flashlight using a proximity sensor, and it also adjusts screen brightness using a light sensor.

Chapter 5, The Motion, Position, and Fingerprint Sensors, explains the working principle of motion sensors (accelerometer, gyroscope, linear acceleration, gravity, and significant motion), position sensors (magnetometer and orientation), and the fingerprint sensor. We learn the implementation of these sensors with the help of three examples. The first example explains how to use the accelerometer sensor to detect phone shake. The second example teaches how to use the orientation, magnetometer, and accelerometer sensors to build a compass, and in the third example, we learn how to use the fingerprint sensor to authenticate a user.

Chapter 6, The Step Counter and Detector Sensors – The Pedometer App, explains how to use the step detector and step counter sensors. Through a real-world pedometer application, we learn how to analyze and process the accelerometer and step detector sensor data to develop an algorithm for detecting the type of step (walking, jogging, sprinting). We also look at how to drive the pedometer data matrix (total steps, distance, duration, average speed, average step frequency, calories burned, and type of step) from the sensor data.

Chapter 7, The Google Fit Platform and APIs – The Fitness Tracker App, introduces you to the new Google Fit platform. It walks you through the different APIs provided by the Google Fit platform and explains how to request automated collection and storage of sensor data in a battery-efficient manner without the app being alive in the background all the time. As a learning exercise, we develop a fitness tracker application that collects and processes the fitness sensor data, including the sensor data obtained from remotely connected Android Wear devices.

Bonus Chapter, Sensor Fusion and Sensor – Based APIs (the Driving Events Detection App), guides you through the working principle of sensor-based Android APIs (activity recognition, geo-fence, and fused location) and teaches you various aspects of sensor fusion. Through a real-world application, you will learn how to use multiple sensors along with input from sensor-based APIs to detect risky driving behavior. Through the same application, you will also learn how to develop the infrastructure (service, threads, and database) required to process high volumes of sensor data in the background for a longer duration of time. This chapter is available online at the link https://www.packtpub.com/sites/default/files/downloads/SensorFusionandSensorBasedAPIs_TheDrivingEventDetectionApp_OnlineChapter.pdf