Working with EHealth Sensor from Libelium

I have been meaning to try out the cooking hacks EHealth Sensor kit for sometime now. My first attempts didn’t go well thanks to the changing supporting libraries and my impatience browsing all forums!

e-Health Sensor Platform V2.0 for Arduino and Raspberry Pi [Biometric /  Medical Applications]

Though it was interesting, I was facing a lot of compilation issues since the version I had for the sensor, arduino and the libraries shared by cooking hacks makers were incompatible.

Off late with the second wave of covid, I started using the sensor again. So I thought why not give it a try again to get the data onto internet. This time of course, I was able to get the errors fixed with the below actions

  1. Arduino version – I had to delete my Arduino 1.8 version and move back to 1.0.6 old version.
  2. Refer to the link and pick up the right version for EHealth and PinChangeInt Libraries based on your time of purchase.

with the above two steps properly done, I was able to compile and upload my code correctly for Arduino Leonardo board.

Now comes the bad part! ūüė¶

  1. ReadPulseOximeter() methods was not working! So the interrupt trigger was not working for some reason. I tried changing the pininterrupt library to the latest version. Somehow didn’t help.
  2. So I moved the code to Loop() and tried called the C++ method from here directly. While the device display showed the SP02 and BPM accurately, the data I got from the library on Arduino Serial monitor was highly inaccurate!!! I tried changing the libraries and the delay in the eHealth.cpp but with that didn’t change the accuracy of output. Al this while though the device showed proper readings on its native display. I believe it is somehow related to segToNumber method and the delay.
Serial monitor data

Source code is here (not much different from the existing source code) except for the direct call to Cpp library..

So what next?

-> Investigate the data accuracy issue by updating the Arduino library EHealth file, esp the segToNumber & the delay.

-> Interface the shield to Raspberry PI, use its libraries and see if the accuracy is better than Arduino libraries


Azure Stream Analytics to SQL Server – Isn’t that simple? or May be not..!

It is quite a known pattern to use Azure Stream Analytics (ASA) to create data pipelines to store ingress IoT data to an output location be it a SQL Server or EventHub or Azure Storage etc. This is all the more important when push ASA to the edge and use that as a data transformation and storage orchestration engine esp. with SQL Server on local on premises being used like a Historian. This seems to a straight-forward process but here comes a small catch and technical/product limitation of Azure. It took us a few precious hours to understand this aspect.

Short Answer (if you have scrolling like me):

“If you want to connect ASA with SQL server, ensure that you have a trusted CA certificate with proper certificate chain installed in the SQL server VM”.

For the patient ones who need the backstory ūüôā read along..

What were we doing?

We were trying to wire up an Azure IoT edge module with a SQL server on a VM! This seemed quite easy as per the documentation but I ended up with a curious certificate error.

As a troubleshooting step, I tried to create this on ASA on cloud and connect with the same SQL server on VM to rule out any Edge VM certificate issues. This should be quite quite simple if we follow this blog.

No big deal. So you thought.

But, I still got the famous certificate chain error.

So I started doing the below documented steps

Using Encryption Without Validation – SQL Server Native Client | Microsoft Docs

  1. Set Force Protocol Encryption Client Setting to Yes
  2.  For secure connectivity, ensure that the client and server both require encryption. Also ensure that the server has a verifiable certificate, and that the TrustServerCertificate setting on the client is set to FALSE.

Created self signed CA certificates and installed them as well. But then still the issue seems to be coming back and back.


Finally, we found out from Microsoft product team that we need proper CA certificates with certificate chain from well known authority to make ASA and SQL work together.

One requirement for SQL server on VM as output to work is that the SQL server needs to be configured with an SSL certificate issued by a trusted CA. There is no workaround with this. You can’t use a self signed certificate or use TrustServerCertificate=True and change SQL Server settings.

1- Regarding SSL Certificate – Make sure to use the DNS based FQDN for the CN. Here are the full requirements listed.

2- SSL Setup in the VM – Follow steps here. If using SQL 2016 , Also put the certificate‚Äôs thumbprint in the registry key mentioned in the ‚ÄúWildcard Certificates‚ÄĚ section. 

Now for me who is just doing a dev setup and doesn’t have the luxury of client CA certificates, there are quite limited options.

For IoT Edge, I used a custom .NET code with SQL DB client to communicate with SQL server VM using the TrustSeverCertificate = True flag in connection string for dev code until I get a CA cert.

But for Azure Stream Analytics PaaS service, we can’t enter connection string. So there is no way to enter TrustSeverCertificate=TRUE during development. Sure seems like a restriction.

One another way which is to use services like Let’s Encrypt and generate a chained certificate for your use temporarily. Something which I am yet to try. I think that should work.

If you have used that and worked, please let me know in the comments.

Back to Sensing, Streaming and Storing..

IoT Data Ingestion strategies (quickly pressed..)

Having worked on data ingestion part of IoT for 6 months with IoThub, what I have understood is that a few strategies should be applied while during data ingress to ensure smooth and meaningful data ingress.

  • Understanding the frequency of data ingress

If you look at the tiers given by Azure itself for data ingress Total Messages per day and each message packet size determine the one you choose among the 4 available. The more the messages, the more difficult it is to stuff everything into a database and then parse to make it meaningful. The ideal solution is to remove certain data which are off the chart or send it specific repositories. For example, if you want to remove data from event 1 processed and moved to datastore 1 and data from event 2 moved into datastore 2 at the outset itself.

  • Annotation metadata to data

Now that your IoT Device has collected billions of data and that you have stored it in some format, to build a relationship and history, would you search through the entire tables and build that hierarchy. I guess, you are better off adding metadata on the run

  • Stream Analytics is a must

If you want to raise an alarm when there is a temperature spike or fall, or if you want to start another process when the process 1 is continuously failing / not sending data, we would want a Stream analytics solution whomsoever provides in your ecosystem, be it Azure, Amazon, Google, IBM and the like. No one wants to build analytics and wait 10 mins for the instant alerts.


(Article in KDNuggets helped me verify that my understanding is in tune with what the industry and academia in general thinks about data ingress in general.)

Integrating Chafon RFID tags into your C#/.NET projects

Couple of months back I started working on a simple RFID application integrated to the Internet to do some interesting gamified use cases.

Well, if you ask what use cases did I have in mind, the easiest analogy that I have is Disney MagicWand.

The videos  of magic band usage encouraged me to make a silly version of the application where I can take some data from the swipe of a band and then put it on a mobile notification to do something interesting, something worthwhile, something though provoking.

So I ordered a Chafon RFID reader and a few TK4100 re-programmable RFID tags.


In the first version here, I setup Chafon Reader to work with a Windows 10 laptop, .NET code using a bit of managed code wrapping up over the Chafon dll.

After the setup mentioned here below or in GitHub page, we can download and run this application.

The application scans all the ports, finds out the port on which our reader is available, gets ready to read tag. Once tag is scanned it just displays details in the console.

Steps to follow:

Chafon reference code is available for free download here

TK4100 specs are available here

  1. Download Chafon RFID application for your corresponding LHF Device.
  2. Install the Prolific driver
  3. Follow the steps given by Chafon to update old driver in device manager (the pdf is inside the zip downloadable from Chafon site)
  4. Now use their given application to read and write into the tag
  5. you may want to make some changes to their code like I did – by adding a few decorators for the managed dll we are going to use
  6. Copy that dll into your executing code folder so that code can find it.

You may want to download and install Microsoft Visual C++ 2005 Redistributable Package (x86) to ensure that you are able to develop in a Win 10 x64 machine.


Uses dynamic port finding to ensure that you always get port where your device is connecting to. It could be COM3 or COM4 or COM8 based on what your laptop assigns it.


There are 2-3 sources which has contributed to this code. Please find the first one below where I understood what are the possibilities and how to get it done.

  • Blog 1 from Rob and related tools list
  • WMI code generator¬†from Microsoft
  • The initial code generated from the tool took me to this link¬†which gave me a detailed industrial code snippet which could be reused in my case with a few modifications.

These changes ensured that irrespective of how and where I plugin my Chafon reader it gets picked up correctly as long as my simple string search for “”


In the next parts, I am planning to upload this data to an Azure IoTHub and also configure a simple RAW push notification channel to ensure that you get this as a RAW message in your mobile phone.

Once these two steps are done, then the possibilities are numerous in terms of how you want to play with this.

Be it a simple gamified application or a complex use case.

  • for your kid inside your house – make her run into living room,¬†tap it on her chair,
  • increase your dogs happiness quotient by fastening¬†it on the collar – (ensure the devices and tags are¬†human and animal test and¬†friendly, do take care of things like choking hazard etc.)
  • Asset tracker like Tile App: Tie TK4100 to your keychain, build a custom key box with reader underneath your box [and a connected raspberry pi sending data our (here the program is on a laptop but)], use it to find out¬†which key is taken out when and what time do you return etc.Use this data to manage your activities better or even simply to find whether your key is in the keybox or not.