I2C communication in PSLab Android

PSLab device is a compact electronic device with a variety of features. One of them is the ability to integrate sensors and get readings from them. One might think that why they should use PSLab device to get sensor readings and they can use some other hardware like Arduino. In those devices, user has to create firmware and need to know how to interface them with correct sampling rates and settings. But with PSLab, they all come in the whole package. User just have to plug the device to his phone and the sensor to device and he’s ready.

The idea of this blog post is to show how this sophisticated process is actually happening. Before that, let me give you a basic introduction on how I2C communication protocol works. I2C protocol is superior to UART and SPI protocols as they are device limited or requires many wires. But with I2C, you can literally connect thousands of sensors with just 4 wires. These wires are labeled as follows;

  • VCC – Power line
  • GND – Ground line
  • SDA – Data line
  • SCL – Signal clock

It is required that the SDA and SCL lines need to be connected to VCC line using two pull up resistors. But that’s just hardware. Let’s move on to learn how I2C communicate.

Here there is this communicating concept called master and slave. To start communication, master issues a global signal like a broadcast to all the devices connected to SCL and SDA lines. This signal contains the address of the slave, master needs to address and get data from. If the slave received this call to him, he will pull down the SDA line to signal the master that he heard him and ready to communicate with him. Here communication means reading or writing data. Then the communication happens and the link between master and slave breaks giving opportunity to other masters and slaves.

One might think this is a slow process. But these signals are transmitted at high frequencies. In PSLab it is at 100 kHz and that is one millisecond.

PSLab library has a special class to handle I2C communication. That is

public class I2C {/**/}


Once this class is initiated, one has to call the start function to start communication. This method requires the address we wish to communicate with and the mode of operation stating if it is a read or write operation

public int start(int address, int rw) throws IOException {
   packetHandler.sendByte((address << 1) | rw & 0xff);
   return (packetHandler.getAcknowledgement() >> 4);


Once the address is sent out, protocol requires us to stop and wait for acknowledgement.

public void wait() throws IOException {


If there are no congestion in the lines such as reading from multiple devices, the acknowledgement will be instantaneous. Once that is complete, we can start communication either byte-wise or bulk-wise

public int send(int data) throws IOException {
   return (packetHandler.getAcknowledgement() >> 4);


As an example, reading sensor values at a given interval can be done using the following method call.

public ArrayList<Byte> read(int length) throws IOException {
   ArrayList<Byte> data = new ArrayList<>();
   for (int i = 0; i < length - 1; i++) {
   return data;


Once we get the data bundle, either we can save them or display in a graph whatever the way it’s convenient.


  1. https://en.wikipedia.org/wiki/I%C2%B2C
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Sensor Data Logging in the PSLab Android App

The PSLab Android App allows users to log data from sensors connected to the PSLab hardware device. The Connected sensors should support I2C, SPI communication protocols to communicate with the PSLab device successfully. The only prerequisite is the additional support for the particular sensor plugin in Android App. The user can log data from various sensors and measure parameters like temperature, humidity, acceleration, magnetic field, etc. These parameters are useful in predicting and monitoring the environment and in performing many experiments.

The support for the sensor plugins was added during the porting python communication library code to Java. In this post,  we will discuss how we logged real time sensor data from the PSLab Hardware Device. We used Realm database to store the sensor data locally. We have taken the MPU6050 sensor as an example to understand the complete process of logging sensor data.

Creating Realm Object for MPU6050 Sensor Data

The MPU6050 sensor gives the acceleration and gyroscope readings along the three axes X, Y and Z. So the data object storing the readings of the mpu sensor have variables to store the acceleration and gyroscope readings along all three axes.

public class DataMPU6050 extends RealmObject {

   private double ax, ay, az;
   private double gx, gy, gz;
   private double temperature;

   public DataMPU6050() {  }

   public DataMPU6050(double ax, double ay, double az, double gx, double gy, double gz, double temperature) {
       this.ax = ax;
       this.ay = ay;
       this.az = az;
       this.gx = gx;
       this.gy = gy;
       this.gz = gz;
       this.temperature = temperature;

  // getter and setter for all variables

Creating Runnable to Start/Stop Data Logging

To sample the sensor data at 500ms interval, we created a runnable object and passed it to another thread which would prevent lagging of the UI thread. We can start/stop logging by changing the value of the boolean loggingThreadRunning on button click. TaskMPU6050 is an AsyncTask which reads each sample of sensor data from the PSLab device, it gets executed inside a while loop which is controlled by boolean loggingThreadRunning. Thread.sleep(500) pauses the thread for 500ms, this is also one of the reason to transfer the logging to another thread instead of logging the sensor data in UI thread. If such 500ms delays are incorporated in UI thread, app experience won’t be smooth for the users.

Runnable loggingRunnable = new Runnable() {
   public void run() {
       try {
           MPU6050 sensorMPU6050 = new MPU6050(i2c);
           while (loggingThreadRunning) {
               TaskMPU6050 taskMPU6050 = new TaskMPU6050(sensorMPU6050);
              // use lock object to synchronize threads
       } catch (IOException   InterruptedException e) {

Sampling of Sensor Data

We created an AsyncTask to read each sample of the sensor data from the PSLab device in the background thread. The getRaw() method read raw values from the sensor and returned an ArrayList containing the acceleration and gyro values. After the values were read successfully, they were updated in the data card in the foreground which was visible to the user. This data card acts as a real-time screen for the user. All the samples read are appended to ArrayList mpu6050DataList, when the user clicks on button Save Data, the collected samples are saved to the local realm database.

private ArrayList<DataMPU6050> mpu6050DataList = new ArrayList<>();

private class TaskMPU6050 extends AsyncTask<Void, Void, Void> {

   private MPU6050 sensorMPU6050;
   private ArrayList<Double> dataMPU6050 = new ArrayList<>();

   TaskMPU6050(MPU6050 mpu6050) {
       this.sensorMPU6050 = mpu6050;

   protected Void doInBackground(Void... params) {
       try {
           dataMPU6050 = sensorMPU6050.getRaw();
       } catch (IOException e) {
       return null;

   protected void onPostExecute(Void aVoid) {
       // update data card TextViews with data read.
       DataMPU6050 tempObject = new DataMPU6050(dataMPU6050.get(0), dataMPU6050.get(1), dataMPU6050.get(2),
               dataMPU6050.get(4), dataMPU6050.get(5), dataMPU6050.get(6), dataMPU6050.get(3));
       synchronized (lock) {
Source: PSLab Android App

There is an option for Start/Stop Logging, clicking on which will change the value of boolean loggingThreadRunning which stops starts/stops the logging thread.

When the Save Data button is clicked, all the samples of sensor data collected from the  PSLab device till that point are saved to the local realm database.

for (DataMPU6050 tempObject : mpu6050DataList) {

Data can also be written asynchronously to the local realm database. For other methods to write to a real database refer write section of Realm docs.


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How to Read PIC Data-Sheet and Add a New Functionality to PSLab Firmware

Reading data-sheets is not a fun task. Going through tens of hundreds of pages with numerical, mathematical and scientific data is not fun reading. This blog post attempts to simplify reading the available data-sheets related to PIC24 micro-controller used in the PSLab device to help reader with implementing a new feature in PSLab firmware.

There are many features available in the PSLab device, such as; UART, SPI, I2C, ADC and Basic I/O reading. The “basic” implementation techniques do not vary much from one feature to other. That being stated this blog will carry out the basic implementation techniques one should follow and basic knowledge on PIC micro-controller programming to save himself from the trouble going through the 500+ pages in PIC data-sheets.

PIC Basics:

Before go into implementation there are few facts one should know about PIC programming.

– In the micro-controller values are saved in a memory block known as Registers. The values saved in these registers are volatile as they are all set to 0 regardless the value they were assigned when the power is off.

– Micro-controller configurations are made by setting values to these registers. Even turning on and off a whole feature like UART in PSLab device can be done using setting 0 to UARTEN register bit.

– When it comes to I/O ports, there are two different types of registers called TRIS and LAT/PORT. By setting 1 to TRIS ports will make the relevant pin an input pin. Setting it to 0 will make it an output pin. Easy way to remember this is think 1 as I in input and 0 as O in output. In UART implementation of PSLab, pin RP40 is set as an input pin to receive the data stream and pin RP39 is set as an output pin to send the data stream out. These settings are made using TRIS port settings. PORT registers save the value received by the relevant input pin attached to it.

The above figure extracted from mikroe learning materials, illustrates different stages an I/O pin can handle. As an extra point, ANSEL register makes the pin support digital signals or analog signals as per user requirements.

– In PIC, some registers such as PORT, TRIS and registers with similar functionalities are combined together. To access the value of each individual register can be done using dot notation. Assume the program requires to access the 8th register in TRISB register set. Note that the registers are indexed from zero. This implies that the 8th register will have the index 8 in the register sub-set. The following syntax is used to access the register;



The above points cover the basic knowledge one should have when developing firmware to PSLab device.

How to implement a feature like UART in PSLab firmware?

The first thing to know when implementing a new feature is that the developer needs to be familiar with the relevant hardware protocols. As an example, to implement UART; relevant protocol is RS232. If the feature is I2C; one should know about the I2C protocol.

Once the feature is familiar, next step is to refer the PIC data-sheet and resources on how to implement it in firmware. As for demonstrative purposes, this blog will continue with UART implementation.

Download the latest data-sheet from MicroChip official website and browse to the table of content. It consists of a set of features supported by the micro-controller implemented in the PSLab device. Find the entry related to the feature being implemented. In this case it will be Universal Asynchronous Receiver Transmitter (UART).

Each feature will contain a description following this format explaining what are the options it support and its constraints.

One must be aware of the fact that not every pin in the micro-controller can be used for any feature as he desires. The “PINOUT I/O DESCRIPTIONS” section in the data-sheet explains which pins are capable of the feature being implemented. According to these details, the pins should be initiated as Input/Output pins as well as Digital/Analog pins.

The next step is to refer to the control registers related to the feature. They are all mentioned in the data-sheet under the specific feature. There are some notations available in this section which resembles something like the following;

PDSEL<1:0>: Parity and Data Selection bits
11 = 9-bit data, no parity
10 = 8-bit data, odd parity
01 = 8-bit data, even parity
00 = 8-bit data, no parity


This represents a register with two bits. By setting either 11 or 10 or 01 or 00; different implementations can be achieved.

In PSLab firmware this is implemented as;

U1MODEbits.PDSEL = 0;


which implements UART feature with 8-bits stream having no parity bits for error correction.

In UART feature implemented in PSLab device, receiving bit stream is fetched by reading the register values in U1STAbits.URXDA and data is transmitted using U1TXREG. All these registers are mentioned in the control registers section in the feature.


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Creating Sensor Libraries in PSLab

The I2C bus of the PSLab enables access to a whole range of sensors capable of measuring parameters ranging from light intensity, humidity, and temperature, to acceleration, passive infrared, and magnetism.

Support for each sensor in the communication library is implemented as a small Python library that depends in the I2C communication module for PSLab.

However, most sensors have capabilities that are not just limited to data readouts, but also enable various configuration options.

This blog post explains how a common format followed across the sensor libraries enables the graphical utilities such as data loggers and control panels to dynamically create widgets pertaining to the various configuration options.

The following variables and methods must be present in each sensor file in order to enable the graphical utilities to correctly function:

Name: A generic name for the sensor to be shown in menus and such. e.g. ‘Altimeter BMP180’

GetRaw(): A function that returns a list of values read from the sensor. The values may have been directly read from the sensor, or derived based on some parameters/equations.

For example, the BMP180 altitude sensor is actually a pressure and temperature sensor. The altitude value is derived from these two using an equation. Therefore, the getRaw function for the BMP180 returns a list of three values, viz, [temperature, pressure, altitude]

NUMPLOTS: A constant that stores the number of available dataPoints in the list returned by the getRaw function. This enables the graphical utilities to create required number of traces . In case of the BMP180, it is 3

PLOTNAMES: A list of text strings to be displayed in the plot legend . For the BMP180, the following list is defined : [‘Temperature’, ‘Pressure’, ‘Altitude’]

params: A dictionary that stores the function names for configuring various features of the sensor, and options that can be passed to the function. For example, for the BMP180 altimeter, and oversampling parameter is available, and can take values 0,1,2 and 3 . Therefore, params = {‘setOversampling’: [0, 1, 2, 3]}

The Sensor data Logger application uses this dictionary to auto-generate menus with the ‘key’ as the name , and corresponding ‘values’ as a submenu . When the user opens a menu and clicks on a ‘value’ , the ‘value’ is passed to a function whose name is the corresponding key , and which must be defined in the sensor’s class.

When the above are defined, menus and plots are automatically generated, and saves considerable time and effort for graphical utility development since no sensor specific code needs to be added on that front.

The following Params dictionary defined in the class of MPU6050 creates a menu as shown in the second image:

self.params = { 'powerUp':['Go'],

As shown in the image , when the user clicks on ‘8’ , MPU6050.setAccelRange(8) is executed.

Improving the flexibility of the auto-generated menus

The above approach is a little limited, since only a fixed set of values can be used for configuration options, and there may be cases where a flexible input is required.

This is the case with the Kalman filter option, where the user may want to provide the intensity of the filter as a decimal value. Therefore we shall implement a more flexible route for the params dictionary, and allow the value to certains keys to be objects other than lists.

Functions with user defined variable inputs are defined as Spinbox/QDoubleSpinBox.

KalmanFilter is defined in the following entry in Params:

‘KalmanFilter’:{‘dataType’:’double’,’min’:0,’max’:1000,’prefix’:’value: ‘}

Screenshot of the improved UI with MPU6050.

In this instance, the user can input a custom value, and the KalmanFilter function is called with the same.

Additional Reading:

[1]: Using sensors with PSLab Android

[2]: Analyzing sensor data with PSLab android
[3]: YouTube video to understand analysis of data from MPU6050 with Arduino – https://www.youtube.com/watch?v=taZHl4Mr-Pk

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Temporally accurate data acquisition via digital communication pathways in PSLab

This blog post deals with the importance of using a real-time processor for acquiring time dependent data sets. The PSLab already features an oscilloscope, an instrument capable of high speed voltage measurements with accurate timestamps, and it can be used for monitoring various physical parameters such as acceleration and angular velocity as long as there exists a device that can generate a voltage output corresponding to the parameter being measured.  Such devices are called sensors, and a whole variety of these are available commercially.

However, not all sensors provide an analog output that can be input to a regular oscilloscope. Many of the modern sensors use digitally encoded data which has the advantage of data integrity being preserved over long transmission pathways. A commonly used pathway is the I2C data bus, and this blog post will elaborate the challenges faced during continuous data acquisition from a PC, and will explore how a workaround can be managed by moving the complete digital acquisition process to the PSLab hardware in order create a digital equivalent of the analog oscilloscope.

Precise timestamps are essential for extracting waveform parameters such as frequency and phase shifts, which can then be used for calculating physics constants such as the value of acceleration due to gravity, precession, and other resonant phenomena. As mentioned before, oscilloscopes are capable of reliably measuring such data as long as the input signal is an analog voltage, and if a digital signal needs to be recorded, a separate implementation similar to the oscilloscope must be designed for digital communication pathways.

A question for the reader :

Consider a voltmeter capable of making measurements at a maximum rate of one per microsecond.

We would like to set it up to take a thousand readings (n=1000) with a fixed time delay(e.g. 2uS) between each successive sample in order to make it digitize an unknown input waveform. In other words, make ourselves a crude oscilloscope.

Which equipment would you choose to connect this voltmeter to in order to acquire a dataset?

  1. A 3GHz i3 processor powering your favourite operating system, and executing a simple C program that takes n readings in a for loop with a delay_us(2) function call placed inside the loop.
  2. A 10MHz microcontroller , also running a minimal C program that acquires readings in fixed intervals.

To the uninitiated, faster is better, ergo, the GHz range processor trumps the measly microcontroller.

But, we’ve missed a crucial detail here. A regular desktop operating system multitasks between several hundred tasks at a time. Therefore, your little C program might be paused midway in order to respond to a mouse click, or a window resize on any odd chores that the cpu scheduler might feel is more important. The time after which it returns to your program and resumes acquisition is unpredictable, and is most likely of the order of a few milliseconds.

The microcontroller on the other hand, is doing one thing, and one thing only. A delay_us(2) means a 2uS delay with an error margin corresponding to the accuracy of the reference clock used. Simple crystal oscillators usually offer accuracies as good as 30ppm/C, and very low jitter.

Armed with this DIY oscilloscope, we can now proceed to digitize a KHz range since wave or a sound signal from a microphone with good temporal accuracy.

Sample results from the PSLab’s analog oscilloscope

sine wave shown on the oscilloscope
PSLab Oscilloscope showing a 1KHz sinusoidal wave plotted with Matplotlib

If the same were taken via a script that shares CPU time with other processes, the waveform would compress at random intervals due to CPU time unavailability. Starting a new CPU intensive process usually has the effect of the entire waveform appearing compressed because actual time intervals between each sample are greater than the expected time intervals

Implementing the oscilloscope for data buses such as I2C

With regards to the PSLab which already has a reasonably accurate oscilloscope built-in, what happens if one wants to acquire time critical information from sensors connected to the data bus , and not the analog inputs ?

In order acquire such data , the PSLab firmware houses the read routine from I2C in an interrupt function that is invoked at precise intervals by a preconfigured timer’s timeout event. Each sample is stored to an array via a self incrementing pointer.

The I2C address to be accessed, and the bytes to be written before one can start reading data are all pre-configured before the acquisition process starts.

This process then runs at top priority until a preset number of samples have been acquired.Once the host software knows that acquisition should have completed, it fetches the data buffer containing the acquired information.

An example of data being read from a 6-Degree of freedom inertial measurement unit mounted on the pivot of an oscillating physical pendulum.

The plots that overlap accurately with a simulated damped sinusoidal waveform are not possible in the absence of a real-time acquisition system

A 6-DOF sensor connected to the pivot of a physical pendulum.

The sensor in question is the MPU6050 from invensense, used primarily in drones, and other self-stabilising robots.

Its default I2C address is 0x68 ( 104 ) , and 14 registers starting from 0x3B contain data for acceleration along orthogonal axes, temperature, and angular velocity along orthogonal axes. Each of these values is an integer, and is therefore represented by two successive registers. E.g. , 0x3B and 0x3C together make up a 16-bit value for acceleration along the X-axis.


The Final App

Raw Data from a 6-Degree of freedom Inertial Measurement Unit
A least square fit is applied to all 6 datasets (3-axis acceleration, 3-axis angular velocity) from the MPU6050. Extracted parameters show amplitude, frequency, phase and damping coefficient.


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