Monday, May 21, 2012

Mobile Sensing


    Today, I am going to discuss about the "mobile sensing" topic. Here I start with basic in-built sensor into the advance mobile phone (i.e., Android,  iOS). More I'll be adding about the same in future.
   Modern smartphones have a variety of in-built sensors to detect, for example, movement, orientation, rotation, proximity, and magnetic fields. As mobile phones have matured as a computing platform and acquired richer functionality, these advancements often have been paired with the introduction of new sensors. It is surprising how many physiological senses are represented on a smart phone or tablet. The camera, the most widely used sensor on a phone, allows a device to “see” the outside world, while the microphone lets the device “hear.” And many devices now have multiple cameras and microphones for possible spatial resolution. Other means to let a device “see” include light and proximity sensors. The ability to “hear” is further facilitated by any of the four wireless sensors (cell tower, Wi-Fi, Bluetooth, and GPS). Considering these communication devices as sensors naturally leads to methods of determining context, and providing an overall “sense” of the world around the device. The advanced and latest smartphone phone includes eight different sensors: accelerometer, GPS, ambient light, dual microphones, proximity sensor, dual cameras, compass, and gyroscope.

  • The proximity and light sensors allow the phone to perform simple forms of context recognition associated with the user interface.
  • The compass and gyroscope represent an extension of location, providing the phone with increased awareness of its position in relation to the physical world (e.g., its direction and orientation) enhancing location-based applications.
  • Accelerometer data is capable of characterizing the physical movements of the user carrying the phone.
  • The camera and microphone are powerful sensors. These are probably the most ubiquitous sensors on the planet. By continuously collecting audio from the phone’s microphone, for example, it is possible to classify a diverse set of distinctive sounds associated with a particular context or activity in a person’s life, such as using an automatic teller machine (ATM), being in a particular coffee shop, having a conversation, listening to music, making
    coffee, and driving.
  • The combination of accelerometer data and a stream of location estimates from the GPS can recognize the mode of transportation of a user, such as using a bike or car or taking a bus or the subway.


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