notes on algorithm.txt

(ambient background refers to all the "noise" around the phone. When I refer to noise below, it means "junk" noise that doesn't correspond to any alert)
1) Initializing
	The program must initialize an AudioRecord object to read in microphone data. To do this, determine the phone's audio settings: check which audio format (8bit, 16 bit), channel configuration (mono/stereo), and sample rates (in Hz) are supported, and use these settings to record ambient background.
2) Recording
	The phone will use a timer to record a sample of the ambient background on regular intervals (in this case, 50 ms). After obtaining each sample it will analyze it.
3) Analyzing: FFT
	Description: FFT is the faster version of the Fourier transform. It is commonly used to analyze the magnitude vs. frequency audio spectrum of a sound sample. Basically it will determine which combination of sinusoidal waves, when added together or superimposed, will produce the desired sample wave.
	Algorithm: The audio data is read in as an array of bytes. Each byte of audio data is converted to an imgainary number with real part b and imaginary part 0. The array is padded with 0's at the end since we're using a version of FFT that must take in an array whose size is a power of 2.
4) Analyzing: Thresholds
	We assume that a particular alert type is made up of one or more frequencies. We check the resulting FFT spectrum if these frequencies reach a certain magnitude. If they do, we prepare to alert the user of this alert. If there is no alert in the ambient background, a new sample is recorded.
(Note: in future work only, state that we currently only test for one target frequency, but in the future we can theoretically distinguish alert types that emit multiple frequencies)
5) Alerting
	Switch to Alert activity (previously was in MainActivity while recording). Screen flashes in AlertActivity and the name of alert type is displayed, and the phone will undergo a distinct pattern of rumbles depending on the alert type. The user can press the soft button or the phone's back button to acknowledge the alert and resume recording.

A) Detect device's audio settings
Bit rate, channel configuration, sample rates
Record a sample periodically
Analyze audio sample (described next slide)
If audio sample matches certain frequency/amplitude criteria, send appropriate alert type
User acknowledges alert; app resumes recording

B) FFT (Fast Fourier Transform)
Faster version of the Fourier analysis
Audio input is read in as bytes and mapped to imaginary numbers
Analyzes the amplitude vs. frequency distribution of the sound sample
Determine if sound sample's FFT contains particular frequencies that reach a certain amplitude
E.g. a frequency between appx. 1000-1200 Hz with a high enough amplitude corresponds to a tornado warning
App can pick out particular frequencies even with lots of background "junk" noise, so algorithm can even theoretically distinguish alarms that emit multiple frequencies