Sending sensor board data from Raspberry Pi to Intelligent Systems Service (ISS)

I have been mucking around with the Xtrinsic-sense board which is an add-on to my Raspberry Pi. In my previous post, I had executed the Python scripts that came with the sensor library that I cloned out of this github. There is a good article that explains about how to enable Xtrinsic-sense board in Raspbian.

However my aim is to get the Intelligent Systems Service (ISS) sample C application to invoke the sensor board shared library to retrieve the altimeter and temperature values, assign that to a string property within the data model, then send it to ISS. The sensor board library comes in the form of a shared library called

Hence I started on a journey to try to invoke the functions within the out of mirroring the Python code, but in the sample C application. Now I must admit that Python coding skills is non-existent, and my C coding skills were really rusty. The last time I wrote a C/C++ application was in 2000/2001! What’s surprising is that I haven’t completed forgotten C, it’s like riding a bike, suddenly remnants of makefile, linking with dynamic/static libraries, include files, and function pointers in C slowly came back to memory.

But I’m still hopeless in Python, I gave up because I didn’t understand what the following code does except that it does some byte shifting, but for what reason, it beats me.

def getTemp(self):
    t = self.readTemp()
    t_m = (t >> 8) & 0xff;
    t_l = t & 0xff;

    if (t_l > 99):
        t_l = t_l / 1000.0
        t_l = t_l / 100.0
    return (t_m + t_l)

I knew there has to be an easier way to invoke the sensor board library in C, but where’s the sample code? After much searching, I found a reverse-engineered with C source code! How amazing, thanks to this bloke named Lars Christensen. It was just hot off the oven, to be specific just last Saturday 13 Sept. To get started, all I had to do was to clone his source from github. In my raspberrywifai SSH session, I issued the following command (provided you have already installed git too).

git clone

There was a slight problem. The mpl3115a2.h header file was empty. No worries, just go to the github repository at, click on mpl3115a2.h, copy the content, and paste it in the file in your working directory on RaspPi.

You also need to download and extract the bcm2835 library. Then just follow the steps on how to make it. This creates a static library called libbcm2835.a. Next, make the reverse-engineered sensor board library so that you create a new, and libmemssensor.a. I was only interested in the static libraries of libbcm2835.a and libmemssensor.a so that I can compile test.c. There wasn’t a proper make statement for test so I just issued my own gcc command.

gcc -Wall -I /home/pi/rpi-mems-sensor  -L. -lmemssensor -lbcm2835 -static test.c -o test libmemssensor.a libbcm2835.a

Do not just run ./test because initializing bcm2835 requires elevated permission. If you do that you will get the following error:

pi@raspberryfai ~/rpi-mems-sensor $ ./test
bcm2835_init: Unable to open /dev/mem: Permission denied

So do this instead:

sudo ./test

And voila! I get the altimeter and temperature reading.

raw alt = 11968
alt: 46.750000, temp: 23.812500
raw alt = 11968
alt: 46.750000, temp: 23.812500
raw alt = 11968
alt: 46.750000, temp: 23.812500
raw alt = 11968

The Python code which I just couldn’t comprehend is the equivalent of the following C code:


double getTemp() {
    int t = MPL3115A2_Read_Temp();
    int t_m = (t >> 8) & 0xFF;
    int t_l = t & 0xFF;
    if (t_m > 0x7f) t_m = t_m - 256;
    return t_m + t_l / 256.0;

It still beats me what it does, but that’s alright, I just wanted this code to work within the ISS sample C application. Next I embedded this code within the DATAPROVIDER_RESULT DATA_PROVIDER_INIT function. I didn’t want to create a new data model so I reused the sample data model, and chose to assign the altimeter and temperature reading to the stringProperty, as shown in the following code:

// setting StringProperty which contains the alt and temperature
char tempinfo[1024];
snprintf(tempinfo, sizeof(tempinfo), "alt: %f, temp: %f\n", getAlt($
stringProperty = tempinfo;

Compile (also includes modifying the makefile to ensure the sensor board header files and static libraries are correctly linked), and then run the ISSAgent app, and wait for it……..

Info: Microsoft Intelligent Systems Agent Console
Info: Using device endpoint:
Info: Registering device: Name=raspberrywifai, FriendlyName=raspberrywifai, ModelName=Contoso.Device, Description=raspberrywifai
Info: x-ms-activity-id: 557374f8-2342-4bfb-bb7b-ce19199fa77e
Info: Getting endpoints for device raspberrywifai
Info: x-ms-activity-id: 229227bf-483b-4914-a613-e447bb7caca5
Info: Got ingress queue, name=getfityall/raspberrywifai
Info: Got commands queue, topic path=DeviceBank1, subscription name=raspberrywifai
Info: Got per device token=[secret]
raw alt = 11152
Info: Uploading message 2e5f2634-bee2-4e88-b1c3-3ed991f25f41 for device raspberrywifai (payload={"@iot.devicename":"raspberrywifai", "value":[ {"@odata.context":"Contoso\/$metadata#Device\/$entity", "":"Device('raspberrywifai')", "@Microsoft.IntelligentSystems.Vocabulary.V1.Timestamp":"2014-09-17T00:34:41Z", "structProperty":{"simpleField":17, "structField":{"int32Field":10, "int64Field":34, "doubleField":40.000000000000000, "stringField":"Wed Sep 17 10:34:40 2014\u000A", "guidField":"0F1E2D3C-4B5A-6978-8796-A5B4C3D2E1F0", "binaryField":"AAAA", "dateTimeOffsetField":"2014-09-17T10:34:40Z", "booleanField":true}}, "stringProperty":"alt: 43.562500, temp: 22.812500\u000A", "dateTimeOffsetProperty":"2014-09-17T10:34:40Z"} ]}) ...Info: Success

Or more specifically:

"stringProperty":"alt: 43.562500, temp: 22.812500\u000A"

Woo hoo! I got it. Now moving on to the next steps. This opens up other possibilities such as sending temperature as an event on a pre-determined interval, and also set up alarm when temperature falls below or goes above a certain value. The fun begins! 🙂

RaspberryWiFai getting mobile

Raspberryfai has transformed into RaspberryWiFai, and it is can’t wait to go out there under the spring sun! I’d procrastinated for awhile in opening up the clear case and plugging in the Xtrinsic-Sense board that I purchased together. Initially I wanted to buy a downgrade GPIO cable from 40 pins to 26 pins so that the cable could nicely slip out of the clear case. I could order from Adafruit but this means that it would be an international shipment and it would cost me more than the inexpensive cables. I checked out a local electronics mart, but they didn’t sell it. Searched more online stores that would deliver fast around here, and none sell this cable.

Now that RaspberryWiFai is more mobile due to a working WiFi USB adapter, why not power it up using my 19,200 mAh power bank, open up the clear case top, plug in the Xtrinsic -Sense board, and will it out for a drive tomorrow. Here’s how RaspberryWiFai looks like with the dropped top.


However the funny thing was that I didn’t know which was GPIO PIN 1. The Xtrinsic-Sense board has 26 pin to work with the older RaspPi A and B, but RaspPi B+ has 40 pins. It wasn’t labelled on the RaspPi. I looked through GPIO layout diagrams for the RaspPi B+ but couldn’t find anything until I came across a comment from Matt the author of this blog, who said “if you look on the reverse of the PCB Pin 1 has a square pad and the others have round pads.”. Got it!

Without further ado, I executed the Python script for getting the temperature/pressure. The sun was up, and still is so it would be pretty good to show how temperature changes when I moved RaspberryWiFai  from inside my unit to the balcony which is baking hot from the spring sun. Here’s the output showing the temperature rising (I’d condensed the output for brevity sake here):

pi@raspberryfai ~/rpi_sensor_board $ sudo python
MPL3115: Alt. -59.888 Temp: 23.176
MPL3115: Alt. -60.04 Temp: 23.192
MPL3115: Alt. -60.776 Temp: 23.176
MPL3115: Alt. -59.888 Temp: 23.16
MPL3115: Alt. -57.872 Temp: 23.192
MPL3115: Alt. -58.824 Temp: 23.208
MPL3115: Alt. -58.0 Temp: 23.192
MPL3115: Alt. -54.2 Temp: 23.16
MPL3115: Alt. -54.68 Temp: 23.144
MPL3115: Alt. -57.856 Temp: 24.16
MPL3115: Alt. -58.808 Temp: 24.64
MPL3115: Alt. -58.824 Temp: 24.8
MPL3115: Alt. -57.84 Temp: 24.96
MPL3115: Alt. -58.84 Temp: 24.128
MPL3115: Alt. -57.84 Temp: 24.16
MPL3115: Alt. -58.792 Temp: 24.176
MPL3115: Alt. -57.808 Temp: 25.0
MPL3115: Alt. -57.84 Temp: 25.32
MPL3115: Alt. -57.2 Temp: 25.48
MPL3115: Alt. -57.2 Temp: 25.64
MPL3115: Alt. -58.888 Temp: 25.8
MPL3115: Alt. -58.04 Temp: 25.96
MPL3115: Alt. -58.856 Temp: 25.112
MPL3115: Alt. -57.84 Temp: 25.128
MPL3115: Alt. -57.84 Temp: 25.144
MPL3115: Alt. -57.2 Temp: 25.16
MPL3115: Alt. -54.856 Temp: 25.208
MPL3115: Alt. -54.84 Temp: 25.192
MPL3115: Alt. -54.52 Temp: 25.224
MPL3115: Alt. -54.68 Temp: 25.24
MPL3115: Alt. -55.0 Temp: 25.0
MPL3115: Alt. -55.856 Temp: 26.16
MPL3115: Alt. -55.856 Temp: 26.32
MPL3115: Alt. -56.76 Temp: 26.48
MPL3115: Alt. -55.36 Temp: 26.64
MPL3115: Alt. -55.04 Temp: 26.8
MPL3115: Alt. -55.2 Temp: 26.96
MPL3115: Alt. -55.856 Temp: 26.112
MPL3115: Alt. -55.2 Temp: 26.128
MPL3115: Alt. -55.36 Temp: 26.144
MPL3115: Alt. -56.808 Temp: 26.16
MPL3115: Alt. -59.872 Temp: 26.112
MPL3115: Alt. -60.76 Temp: 26.8
MPL3115: Alt. -60.76 Temp: 26.64

Indeed RaspberryWiFai was basking in the sun, from a low of 23.176 degrees C, it went up to 26.96 degrees C under the hot sun. Smoking hot! Time to wire it up to my ISS, and do some cool things like raise an alarm when it is too hot.

How to get Raspberry Pi to work with TP-Link TL-WN721N USB Wi-Fi adapter

Wow! It’s taken me over a week to find just the right combo of advice from a number of really helpful blogs to help me setup raspberryfai with mt TP-Link TL-WN721N USB WiFi adapter. I tried so many different steps that I couldn’t remember what I’d done. I thought that the wicd-curses utility would work like a charm but it hung my RasPi a few times.

Now that it’s setup, I shall call it raspberrywifai. 🙂

The blog which was most helpful was this post written almost 2 years ago. Just follow the steps especially on how to get the firmware for the TP-Link USB adapter. The only exception was that the following command didn’t work in my case,

pre-up wpa_supplicant -Dwext -i wlan0 -c /etc/wpa_supplicant.conf -B

Instead I just have to change it to the simpler form of (my wpa_supplicant.conf file is kept in its own folder):

wpa_conf /etc/wpa_supplicant/wpa_supplicant.conf

In order to get the psk value, you can’t just type in your WPA2 passphrase, you need to run the following command:

sudo wpa_passphrase ssid passphrase

To be sure that it is indeed connected and seen as a USB device on my RasPi, I run lsusb, a command I learned from  this post.

Now that raspberryfai has become raspberrywifai, I can bring it out for a spin this weekend.

Intelligent Systems (at your) Service

I was really excited that my application for the Microsoft Azure Intelligent Systems Service (ISS) Limited Public Preview (LPP) had been approved (my apologies for all the 3-letter acronyms which I will be repeating all over my posts from now on). What the ISS LPP entitles me are the following:

  • Access to the ISS service which is enabled for use with my Azure account. The ISS service icon is now available in the list of services (on the left in my Azure Management Portal) and it looks like this:


  • Download the ISS SDK along with a couple other utilities such as DeviceMonitoring and the Contoso Home Automation -part 1 sample/demo (to be checked out soon)
  • Participate in a private forum.  According to the welcome email, “You are more likely to get a response in a reasonable timeframe, since you are not reliant on an individual being online and able to answer your question”, which sounds great.

I went ahead to create an ISS service for GetFitY’all. However I could not share too much details and the screen clipings because according to confidential information clause in the EULA,  the software and service, including the user interface, features and documentation, are confidential and proprietary to Microsoft and its suppliers.

The real fun happens inside my raspberryfai. The RPi runs Raspbian, a customized version of Debian used to run on the RPi. I used scp to copy the ISSAgent_C_Samples folder into my raspberryfai. Then I compile the sample ISS agent and run it. The agent sends messages to my ISS account. My next step is to embed the ISS managed library into my GetFitYall device gateway, which was implemented as a WebJob described in one of my previous posts, and do the same in sending the activity data points to my ISS account. Previously I implemented a simple message pump functionality in the WebJob to send activity data points (pulled from Fitbit and Strava APIs) asynchronously to an Azure Event Hub via AMQP. Then I have Azure Worker Role instance(s) to ingest the event hub messages by persisting into respective Azure Storage Tables.

To waste or not to waste

Since a young age, I had been taught by my mother not to waste, especially precious resources like water, power, food and yes money too (she still thinks that I’m a spendthrift) . I reckon that my mother understood well about the importance of minimizing waste before carbon footprint appeared in our vocabulary. Up to today, I cringe whenever I see people wasting. As a case in point I once saw a guy leaving the water hose running at his front porch, he was presumably watering his plants, except that there were no plants there and he was doing something else. Although water was free and remains so in my birth state of Selangor, there is absolutely no excuse to leave the tap running for no reason.

While the case above was very much about with social behavior and civic mindedness (or the lack of it), I believe that technology and product innovations around our everyday things, be it appliances, devices, gadgets, wearable devices, or just about anything you own could provide positive implications in conserving resources. The Internet of Your Things could provide means to improve efficiency and minimize waste.

If things could communicate real-time information to each other or via an intelligent systems service, there is a real possibility that power and fuel consumption could fall. The Nest learning thermostat is one such product innovation that helps you save on your energy bill by learning your usage patterns. It could interact with other things too. In my previous post I mentioned a scenario that I would like to cater for which is to alert my family once I’d finished my ride in the trails and when I’m riding or driving home, including my ETA. If it’s winter, it may be good to get that heater warming the bathroom so that it’s all nice and warm when I take my shower or a hot tub bath. It is possible with the Nest and drum roll please… a Mercedes.


No pun intended but I doubt that I would buy a Mercedes just so that my car could tell Nest that I’m on my way home and make it warm and comfortable as soon as I get home. If I did, then this would just prove that my mother was right, that I’m a spendthrift and this negates the reason why I should minimize waste. Hence I’ll try to build my own thing, and application on top of an intelligent systems service to try to enable this scenario. Maybe there are some projects readily available out there, which is great!

Meanwhile I’ll put on my “pastry chef” hat and see what I could do with “raspberryfai” being at my service. I trust there are umpteen scenarios in this uncharted territory of smart things. Do comment and please let me know.

Note: This post was originally posted on my LinkedIn. I still haven’t decided how I will segregate the musings and the technical posts. Meanwhile I’ll just repost every thing I wrote.

raspberryfai at your service

My apologies for the corny title of this post, but since Fai rhymes with Pi, I couldn’t resist not naming my li’ juice fruit as RaspberryFai. See my SSH session below:



I lost a couple days of precious time in tinkering with my Raspberry Pi (RPi) because I got some internet connection issues but it’s been resolved since yesterday. First thing I did was to ensure I could make an SSH connection to my “headless” Pi that’s sitting next to and connected to my ADSL router. Next on the list is to download all the essential packages that I need to get started. The apt-get tool works like a charm once you have internet connection. No need to hunt for all the dependencies, just know what I want and apt-get install away.

I’d installed the following packages so far:

  • wicd-curses – easy way to get WiFi enabled on my raspberryfai. My TP-Link TL-WN721N WiFi USB dongle works well with RPi. It’s not exactly compact in size but then I don’t want to get more gadgets yet so this will suffice at the moment.
  • mono
  • C# interactive shell – both mono and this from
  • build-essential
  • node-js – by following this setup tutorial.
  • node-red: while i’m at it, I may as well check out node-red which is presumably the simplest form of an open source visual editor for wiring the internet of things produced by IBM

Before I end up downloading a bunch of non-essential packages, I better start wiring a quick IoT scenario using raspberryfai.


Unboxing my Raspberry Pi B+

Like a delighted child upon given some candies, that’s was me yesterday, just better. The day started when I went to the post office for an early collection of a parcel which contains a hand-picked tasting selection composed of three Grands Crus Nespresso, two of which I had not tasted before. I’m more of a morning person these days, so this is much appreciated for my early  morning tinkering with Project GetFitY’all.

2014-09-02 07.08.06

Then another pleasant surprise in the afternoon, my Raspberry Pi B+ was delivered. I ordered it from Element 14, a nice reference to silicone in the periodic table. I think this would be a good start to me being a “pastry chef”. I always liken mucking around with technology akin to being a cook. And technical demos are just like a cooking show, my favourite phrase is “and here’s one I prepared earlier…. “. So in this post, I will be using the analogy of being a pastry chef, aptly linked to my new juicy fruit, the Raspberry Pi. 🙂

Here’s the unboxing of my delicious pi, and the pastry ingredients I got were a Raspberry Pi B+ with and 8GB SD card with NOOB, a clearcase, a MEMS Sensors Evaluation board, and a charger.

2014-09-01 16.11.46


The Pi was small, credit-card sized.
2014-09-01 16.11.55

2014-09-01 18.10.51


2014-09-01 18.22.21


Then nicely protected in the clear case.

2014-09-01 18.21.41


More to come at a later post which I’ll boot up NOOB to install Rasbian, enabling XBMC perhaps, and then connecting with the sensor board to start mucking around my project extension.