I'm developing a tool which receives motion sensor data and sends it to a machine learning algorithm, which ultimately will deduce different types of movement.
I read the Motion sensor guide and it seems like there is some redundancy in the data you can get from the sensors. For example: the accelrometer data contains gravity data and the linear acceleration data shows acceleration without acceleration due to gravity.
So my question is: do i really need all the sensors to get all forms of motion or can I give up some of them?
EDIT: (clarifying the question)
I want to collect the minimal data that will allow me to deduce the same things. What I'm looking for is user behavior: the angle which the user holds his phone, the way the user moves while using his phone, etc..
The answer I'm looking for should include the sets of sensors that have high correlation within them, such that only some of the sensors in this set are required to deduce the same type of motion\movement\rotation\acceleration\etc..
The term "Motion" in the question have no precise meaning. So I answer more generally.
"The way one holds his phone" is nothing but the orientation of the phone.There are three sensors which individually tells the orientation of the phone.
Among them only the accelerometer is physical sensor and other two are virtual sensors (they don't have special piece of hardware, they use accelerometer data and report the orientation in different formats).
"The way one moves his phone" - Here I consider four motions.
Output of the gyroscope sensors is not accurate in long term and the output of accelerometer is not accurate in short term, so combine them to get steady output. For details see this question.
Now it is clear that the gyroscope and accelerometer is required in minimum. However using wide range of sensors minimizes our work.
You can't decide what you get - each sensor's data is already defined, and you get all or nothing. If you see closely, there isn't a place in public API which would let you ask for specific things.
To back this up here's quote from Google's document explaining sensor types:
An accelerometer sensor reports the acceleration of the device along the 3 sensor axes. The measured acceleration includes both the physical acceleration (change of velocity) and the gravity. The measurement is reported in the x, y and z fields of sensors_event_t.acceleration.
If you see into android source, the structs here are strictly defined, and struct for acceleration contains specific fields. So even if you would get
0 in fields you don't like, you won't gain anything.
But what you're referring to are two things - base sensors, which are roughly equivalent to physical sensors on the device, and composite sensors, which combine readings from various physical sensors to get more useful data.
So while you can't decide what you get for a particular sensor (like "only gravity" or "only acceleration in Y axis"), composite sensors do give you data that you can compute by yourself using only base sensors. So linear acceleration is composition of data from accelerometer and gyroscope (or magnetic sensor), after some calculations. Similarly step detector "sensor" uses only accelerometer, but interpretes the data automatically to just give you an event that "yes, someone has made a step" with single value
If you're feeding raw motion data to some algorithms, I would guess base sensors are what you're looking for. That said, I believe you can still safely register for all sensors (both base and composite ones) that combined give you all data that you need (and maybe more), without meaningful battery impact.
For more detailed information on each of the sensors refer to Sensor types on Android website, and if you're curious, you can read up short summary on sensors stack as well.
No, you don't need every sensor. Some of the sensors exist as a convenience to the user. Your example of the linear acceleration sensor is one- it tells you the results of the accelerometer with gravity taken out. You could do this yourself from the raw accelerometer data, but that takes a bit of math (you need to subtract the vector gravity over all 3 axes) and a bit of knowhow (did you remember to calibrate the sensor? It may not read 9.8 at rest. For that matter, 9.8 may not be your gravity if you're not at sea level). That's a lot of work that would need to be repeated by each app, so they created a software "sensor" that sits on top of the accelerometer and provides the computed data. It would be unusual for an app to use raw and linear accelerometers in the same app, generally its one or the other. The step counter is another example of this, it guesses at what a step is based on the accelerometer data. You also wouldn't want calibrated and uncalibrated gyroscope data.
As for what you do need- no clue, you don't say enough about what you're trying to do. One warning though- you said you're trying to detect motion. YOu can't do that. You can detect accelerations and rotation. You cannot detect motion at a constant speed. If you're developing any type of app using these it pays to use the correct terminology and think in terms of physics and how the physical accelerometer and gyroscope work, otherwise you're going to cause yourself bugs.