The iOLab wireless lab system allows one to gather experimental data in real time.
One can measure temperature, voltage, current, distance, velocity, acceleration, force, etc. using a variety of built-in or attached sensors.
A USB "dongle" must be plugged into your computer, and you must be accessing this web page through the Chrome (or Chromium, Opera, edge for Windows 10) browser for this to work. Firefox and Safari will not work.
If you do not have an iOLab device, you can load and analyze any data set, by reading an arbitrary text file with two columns of numbers separated by spaces. An optional header line begins with a '!', and specifies data column names.
Data acquisition via WebSerial needs a Chrome/Chromium browser.
Select the sensor(s) that you are interested in from the list on the left (there is no list until you connect to an iOLab), then decide on how long you want to collect the data for, and press Start. If you set the time to -1, the data acquisition will continue indefinitely, and you will need to press Stop to stop it. The data table will be filled at the end of the data acquisition, one tab per sensor, and you can save and graph it down below. The rates at which the sensors report the data vary depending on which sensor(s) are selected and the times when each sensor is measured may differ slightly between sensors.
Collecting new data will overwrite all previously collected data, so be sure to save it to a file first (the Download button below the data table), a file for each sensor separately or one merged dataset for all sensors together, resampled to a common timeline.
Disconnectng from the iOLab device turns it off to save battery power, and you will need to press its On button before you can Connect again. After fifteen minutes of idling, iOLab will be powered off automatically. Change batteries promptly when warnings of low battery voltage are shown: some sensors report invalid data when this voltage is too low.
The calibration data are saved within your browser, so the next time you connect to the same iOLab device, previously used values should be restored, but they may no longer be valid. For best results, re-calibrate sensors before each set of measurements. To reset to the uncalibrated default scales first, replace the values below with zeroes.
Local g= m/s2,
local BEarth= μT
Force (acquire some data before pressing each): with no force applied to
;
then measure the weight of a
-g mass to
Accelerometer, Magnetometer and Gyroscope:
×
1 / 6
Place the IOLab remote x-axis up on a horizontal surface, then press Next and do not change orientation for 2 seconds.
2 / 6
Place the IOLab remote x-axis down on a horizontal surface, then press Next and do not change orientation for 2 seconds.
3 / 6
Place the IOLab remote y-axis up on a horizontal surface, then press Next and do not change orientation for 2 seconds.
4 / 6
Place the IOLab remote y-axis down on a horizontal surface, then press Next and do not change orientation for 2 seconds.
5 / 6
Place the IOLab remote z-axis up on a horizontal surface, then press Next and do not change orientation for 2 seconds.
6 / 6
Place the IOLab remote z-axis down on a horizontal surface, then press Next and do not change orientation for 2 seconds.
Report after decimal
•
Live Display every 1 / data
•
Download graph as:
Override:X labelY labelTitle
FFT:windowing function
BrockPhysics PIC:connected
Range Finder:
Vsound=m/s,
Xoffset= m
Place the range finder at a "true" distance from a target (use the distances in the first column, or specify your own);
then click 'measure' to get the raw time-of-flight (in μs). Once the table has at least three data points, press 'fit' to calibrate.
Select the function to fit to the data from the drop-down menu, or type your own expression. Typical math expressions are recognized, including abs(), sqrt(), exp(), ln(), sin(), cos(), tan(), atan(), etc. For xn use power(x,n) or x**n. Be sure to match the number of specified starting values to the expression used, and blank out the unused variables.
The fits are performed using a generalized non-linear least squares minimization, which requires that a set of reasonable approximate values for all fit parameters be specified. If your fit fails, review the graph and adjust the starting values for the parameters in use. Sometimes increasing the max number of iterations may be helpful.