iQunet > FAQ


Q1: How many wireless sensors can the iQunet sensor network manage?

Virtually unlimited. There is no limit on the number of sensors in one iQunet sensor network. You can also combine different sensor types in one network. The central node is the base station. All data gathered by the sensors is stored on the iQunet server attached to the base station.

Q2: What is the range of a wireless iQunet sensor?

The range of a sensor is a few hundreds of meters in free field. In industrial plants the range is less due to interference and reflections. If the sensor is mounted according to our instructions you can reach up to 50m in a rather open plant. In a very dense plant with metal constructions all over, the range will be up to 30m. If a sensor or the base station is put in a metal cabinet, the range will drop to less than 10m. You can always check the RSSI symbol in the dashboard to find out if the sensor is able to connect to the base station. Due to limitations in the free frequency bands, we are not allowed by governmental rules to increase broadcasting power – although we could.




Q3: Can I extend the range of the sensor network?

Yes, you can! Use an iQunet repeater to extend the range of the sensor network. You can add an unlimited number of repeaters in the range of the base station.  Each repeater can serve also an unlimited number of sensors.  Nevertheless, each sensor might not see more than one repeater between sensor and base station. More repeater hops in the network will drastically increase the uptime of the radio transmitters in the sensors. By avoiding this, we can guarantee a long battery life.

Q4: What is the battery life time of the 2 batteries in the sensors?

This depends on the adjustable settings made on the sensor via the sensor dashboard. But as a comparison: the batteries of the vibration sensor, measuring 8192 vibration points every day, will last up to 5 years. With one important remark: the batteries should be installed clean! The sensor electronics are extremely low power. E.g. touching the CR2032 coin cell batteries will leave some grease on the batteries and this will allow leakage current to run over the battery poles, resulting in a reduced sensor life time up to 50%!

Q5: Is it possible to attach a magnetic base to the wireless sensor without interfering the wireless signal quality?

Yes, you can. Sensors like the standard vibration sensor are not sensitive to magnets. This allows you to mount the sensor on a magnetic base and start online measuring in no time. Other sensors like the proximity sensors measure the magnetic field, and it is obvious that mounting such a sensor on a magnetic base makes little sense.

Q6: I am making a test with the Vibration Sensor, and I am observing that I measure 1gRMS when the sensor is measuring nothing (I only put it on the table). Why is this happening?

The vibration sensor contains an acceleration MEMS chip. Even when on the table, the sensor measures gravity. Depending on how it lays on the table you will find +1g or -1g on the axis that is in line with gravity. You can set the high pass filter in the sensor dashboard to filter out the gravity measurement in the graphs.

Q7: How can I avoid taking measurements with the vibration sensor when the rotating equipment is not rotating?

You can set a threshold level for the vibration sensor which avoids creating not usable data. When the measured RMS on a few samples is higher than the threshold, the full measurement is processed and stored in the OPC database. Otherwise this sample measurement is dropped.

Q8: Can I monitor already installed analog sensors with the iQunet sensor network?

We are working on a system which digitizes analog sensor values and stores them in the OPC database with a time stamp. This way you will be able to combine existing monitoring sensors and wireless iQunet sensors and store the values in one database for further processing.  We keep you updated via our website.

Q9: Do I have to install software and buy licenses to setup and monitor the sensor network?

No, you don’t need to install any software but your browser to address the iQunet sensor dashboard.  Neither is there any license fee to be paid. By purchasing the product, you have paid for both the hardware and installed software. We advise a Chrome browser, but any browser webRTC ready will do fine (check http://iswebrtcreadyyet.com/legacy.html to see if your browser supports this open source development).  Try to browse the dashboard on a WebRTC ready browser on any device like your smartphone, tablet, etc.  It will work fine too.

Q10: Where is my data stored? Do I have to pay a cloud fee?

The sensor measurements are stored on the iQunet Unix server you buy with the sensors and network components. This server runs several processes and contains a database. (We compute “in the edge – not in the cloud”) The OPC UA server allows you to access the data free of charge from any OPC UA client. There is no lock-in, nor are there any fees to be paid. It is the vision of iQunet that data collected by the customer belongs to the customer without fees. Of course, you will need stable network access to address the server and to visualize the data or to extract data using the OPC UA server communication.

Q11: What happens if the internet or intranet fails?

As long as the servers (and repeaters) are connected to the mains, data collection and monitoring remains ongoing, even without internet/intranet connection. The iQunet sensor network stays up and running because we compute “in the edge”, not in the cloud. Data is stored nearby the sensor network. Only visualization (via browser) is done over the network.

Q12: Do you have a temperature sensor?

All battery-operated sensors have a temperature sensor chip on board. This electronic sensor is situated on the PCB inside the sensor unit and measures the mass temperature from the wireless sensor. There will be some delay between the surface temperature of the sensor unit and the collected inside temperature.

Q13: What means the message in my browser: ``Error: Could not connect to peer server xxxxxxx``?

This message will appear if your browser is not able to connect with the iQunet server via internet. Most likely, the network connection from the server is broken. In rare cases the company firewall setting will have to allow our relay server to connect to the iQunet Unix server within the company network. Please contact us for further instructions.

Q14: What is the IP address of the iQunet Unix server in my network?

The current IP address from the server in the network can easily been shown: click on the 3 bars below the iQunet logo in the browser. The left pane opens. Click “Ethernet-Wifi” and the information appears.

Q15: I would like to give a fixed IP address to the iQunet server. Is this possible?

Yes, indeed. Connect to the iQunet server. Open the left pane in the iQunet dashboard by clicking the 3 bars below the iQunet logo. Click “Ethernet-Wifi” and change the setting from layer 3 in the network profile.

Q16: Why are the iQunet vibration sensors not calibrated?

The iQunet vibration sensors are not calibrated because the calibration would only be valid for a specific frequency and temperature. Since these parameters cannot be kept stable in a real industrial environment and a calibration procedure per sensor is expensive, iQunet has chosen for a more practical solution.

Instead of (re)calibrating each sensor each year, iQunet keeps track of several trends, on top of the time signal, of the vibration signal (for example RMS). Based on these trends deviations can be detected automatically, where one-time measurements must work with prefixed threshold values. Since the sensor doesn’t need to be removed for calibration, it can remain mounted on an identical spot. This will lead to consistent trend tracking measurements. Since the iQunet sensors work completely wireless, there is also no risk of variable contact surface, modified measuring points, interference on the cabling or even an incorrectly performed measurement. Problems in the machine on the short term can thus be detected faster, even without calibration.

Since the sensor doesn’t need calibration, the maintenance costs per sensor are much lower and the sensor design is simpler which results in a lower current consumption and a longer battery life time.

Finally, the peak frequencies in the Fourier spectrum are dependent on the rotation speed. Even if the rotation speed is theoretically constant, there will be an unknown shift in the spectrum caused by the variable motor load, variations in the frequency control of the motor, etc. These shifts are however constant across the whole spectrum. Because of this, orders of the fundamental frequencies (1X, 2X, 3X, etc.) can be used in the spectrum. The same principle applies for a noncalibrated iQunet sensor.

Q17: How can I connect to the iQunet Unix server?

Connect the iQunet server to the 230V mains and if available to the network.


As shown in the figure below, there are several options to connect to the server.

  1. Via WiFi hotspot. The IP address of the server is always An active network connection is optional.
  2. Via local access (LAN) where server and client server are on the same subnet.
  3. Via WiFi (WLAN). An active wireless network connection is required.
  4. Via WebRTC (rtc.iqunet.be). This only works for the dashboard GUI. An active network connection is required
  5. (optionally) Via Hamachi commercial VPN. Please contact us for more details if interested.


On all listening interfaces, the ports are fixed: 8000 for the dashboard and GraphQL, 4840 for OPC UA, 9001 for the supervisor (pw: admin/admin) and port 22 for SSH.



1 Hotspot


If there is no network connection available, you can use the hotspot functionality of the iQunet server. Of course, this functionality can also be used when there is an active network connection available.


Place the server within the WiFi range of your PC and look for the hotspot name (e.g. SERN- xxxxxxxxxxxx) in the network center of your computer. Your PC should be WiFi enabled. Select the hotspot and click Connect. The hotspot’s password is the Sensor Proxy ID (e.g. server-xxxxxxxx). This ID is written on your UNIX server. Once connected to the hotspot, you can connect to the server by browsing to We recommend using the Chrome browser.


2 Local Access


Look for the current IP address of the server in the local network. The current IP address can be found as explained in Q14. Copy this IP address and replace the “xxx.xxx.xxx.xxx” in  http://xxx.xxx.xxx.xxx:8000/dashboard/app with this address.


Please make sure that your computer and the server are on the same network by for example checking the network settings of your computer or by pinging the server’s address. It is also necessary that both clients can directly connect to each other. Some network configurations do not allow such connections even when both computer and server are on the same subnet.


3 WiFi


To establish the WiFi connection you need to change the “Ethernet-WiFi” settings in the iQunet sensor dashboard. From software version 1.2.6 on this can be done via a wired connection and via hotspot. For earlier versions a wired connection to the internet is needed.


Connect to the sensor dashboard. Click on the 3 bars below the iQunet logo and open the “Ethernet-WiFi” control panel. Select your WiFi network under the section “WIFI CLIENT”. Enable the encryption in “Layer 2 – Security”. Fill out your network key. Click the “Save” button and then the “Connect” button.


4 WebRTC


If there is a network connection available, you can connect to the server via rtc.iqunet.be. WebRTC only works for the dashboard GUI.

The first time you connect via rtc.iqunet.be, you will be prompted to identify yourself with a Google account. This identification is to make sure you are not a web robot.



To logon to the iQunet sensor dashboard, you will be prompted for a Cloud API Key and a Sensor Proxy ID (API Key and Sensor Proxy ID are provided by iQunet). The Sensor Proxy ID is written on your UNIX server (e.g. server-xxxxxxxx).


Q18: How can I start data acquisition?

Once you are connected to the iQunet Unix server, you can adjust the settings of the sensors to your needs in the sensor dashboard and start data acquisition.

For the vibration sensor for example you can change the sample rate, measurement axis, number of samples, etc. Start the data acquisition by either triggering manually (REC button in the ‘MEMS Vibration Setup’ section) or by enabling automatic measurements where you set the time interval in between two measurements (‘Auto Measurements’ section).



The recorded vibration data can be viewed in the iQunet sensor dashboard by opening the vibration lab pane. Click on the ‘vLab’ button in the ‘Vibration Download’ section to open this pane.



Q19: How can I extract data from the OPC UA server?

All recorded data can be extracted via the built-in OPC UA server. The OPC UA server always listens on port 4840 regardless if the connection is made via cable, hotspot or WiFi. If you use the hotspot connection, this will be If you use another connection type, you need to use the IP address of the iQunet Unix server (xxx.xxx.xx.xx:4840). The current IP address of the server in the network can easily been found by clicking the 3 bars below the iQunet logo in the sensor dashboard. Select “Ethernet-WiFi” in the left pane and the IP address will appear.


To extract data via OPC, you can use UAExpert for example.

Open UA Expert and click on Server –> Add.



Double click on “Double click to Add Server” and fill out the IP address behind opc.tcp://. Click OK.



Select the added server in the server list. All sensors connected to this server will appear in the Address Space.



Click on the macId of the sensor to see all possible attributes of the sensor.



Add a document to inspect for example the board temperature data (Document –> Add). Select ‘History Trend View’ as the document type and click ‘Add’.



Drag the boardTemperature attribute of the sensor to the configuration window.



Temperature read-out is possible via either a single update that extracts all data values in between two points of time at once or via a cyclic update that extracts all data over the set timespan every set time interval (update interval).


The accelerationPack attribute contains the raw vibration data. The accelerationPack format is as follows:

1/ numSamples: n = #samples

2/ accelArray: rawSample[0:n-1]

3/ sampleRate: e.g. 400 = 400Hz

4/ formatRange: e.g. 4 = +/-4g (hardware setting of the accelerometer IC)

5/ offset: unused, 0 (hardware offset of the accelerometer IC)

6/ encoded_axis: X = 0, Y = 1, Z = 2

7/ prescaler: unused (only used when no compression in debug mode)

8/ compression:  unused (0 = no compression in debug mode, 1 = compression)


You will see that the first 7 samples of the accelArray (at the start of each measurement) show a transient response due to the start-up behavior of the compression algorithm. Since a Hanning window is used for the calculation of the DFT and RMS, this behavior will be automatically suppressed and has thus no further impact.


The conversion of the accelArray to g units is as follows:


Conversion of rawSample[0:n-1] to [g]:


gSample = rawSample[0:n-1]/512.0*formatRange [g]

gTimes = [0:n-1]/sampleRate [sec]

Q20: How can I export data to Google Sheets/Excel?

From software version 1.2.8 on you can use either the Google Sheets export functionality or the Data Explorer export functionality to export data to Google Sheets or Microsoft Excel.

Important remark: for earlier versions, only the Google Sheets export functionality is available.


Using Google Sheets export functionality


Connect to the server via rtc.iqunet.be as explained in Q17. Once connected to the iQunet Unix server, you can for example view the recorded vibration data in the vibration lab pane. Click on the ‘vLab’ button in the ‘Vibration Download’ section to open this pane.



To export data to Google Sheets click on the “Sheets” button.



By clicking “Sheets”, a Google spreadsheet is created in the account you used to identify yourself at login.



Go to Google Sheets, and you will see the file you created from this sensor by clicking the “Sheets” button. The data is updated every time you click the “Sheets” button in the same graph. Exporting new data parameters of the same sensor will create new tabs in the same file.



Open the file you created, and you can explore the data points or use plug-ins to analyze the data. Share the file with others by clicking the right upper blue button. Shared files will also be updated with new data once created.

It is also possible to save the data in Microsoft Excel format. Select “File” and choose “Download as”. Select the .xlsx format.



Using Data Explorer export functionality (as from version 1.2.8)


Connect to the iQunet server via rtc.iqunet.be or http://xxx.xxx.xxx.xxx:8000/dashboard/app (see Q17 for all connection options). Open the “Data Explorer” control panel in the iQunet sensor dashboard by clicking on the 3 stripes underneath the iQunet logo. Select a device and according attribute on the left.



The data for this attribute will be loaded in the text box on the right in a csv format. Click on “Save As…” to download the data to disk as a .csv file. For large amounts of data, the data loading might take a few minutes. The downloaded csv file can be imported in Microsoft Excel via the “Data” tab or opened in Google Sheets.


Q21: How can I extract data from the GraphQL server?

The GraphQL APIs can be accessed via http://xxx.xxx.xxx.xxx:8000/graphql. If you are connected via the hotspot use to access the APIs. If you are connected to the internet, you can use the IP address of the server instead of the hotspots. The current IP address from the server in the network can be found as explained in Q14. Copy this IP address and replace the “xxx.xxx.xxx.xxx” in  http://xxx.xxx.xxx.xxx:8000/graphql with this address.


Important remark: when connecting to the GraphQL development interface via hotspot, the server still needs a working internet connection, in order to download some browser libraries from CDN. In future versions the latter requirement will be dropped.


All documentation regarding the API’s can be found in the Documentation Explorer at the right hand side at http://xxx.xxx.xxx.xxx:8000/graphql.

Click on ‘Docs’ in the upper right corner to open this Documentation Explorer. A list of all available queries and mutations is shown there.




For example, to retrieve the vibration data, you first need to retrieve the exact timestamps using vibrationTimestampHistory and then use these timestamps to get the vibrationArray you want.



deviceManager {

device(macId: “78:47:8e:af”) {


… on GrapheneVibrationCombo {







On top of the exact date, you need to specify which fields you want to retrieve out of the vibrationarray.



deviceManager {

deviceList {





device(macId: “78:47:8e:af “) {


… on GrapheneVibrationCombo {



vibrationArray(isoDate: “2018-03-08T09:12:48.681441+00:00”) {












The result of this vibrationArray request is a raw AccelerationPack structure. This object packs the following data:

AccelerationPack =

  • numSamples: number of samples in the vibration array
  • rawSamples: raw, unscaled vibration array
  • sampleRate: [Hz]
  • formatRange: sensitivity during capture (e.g 4 == ±4g)
  • axis: ‘X’, ‘Y’ or ‘Z’



Please keep in mind that the rawSamples part contains the raw vibration data and you still need to convert it to g units.


Raw Vibration Data -> Acceleration[g]

The raw vibration vector is converted to acceleration g-units with the following conversion formula, (n == numSamples):



Q22: How can I extract data using Python or Matlab?

You can extract iQunet data via OPC UA, Google Sheets/Excel or GraphQL. For all 3 options there is the possibility to perform the extraction in Matlab and/or Python.


For OPC UA communication in Python the OPCUA library can be used (https://python-opcua.readthedocs.io/en/latest/index.html). You can find some example scripts on our Github page (https://github.com/iqunet/sern). Matlab also offers an extension to read data directly out of OPC UA (https://nl.mathworks.com/products/opc.html and https://nl.mathworks.com/pricing-licensing.html?prodcode=OT).


The Excel files you created with the “Sheets” button in the iQunet dashboard (see Q20) can be read in Python using the Pandas library (https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html) or the xlrd library (http://xlrd.readthedocs.io/en/latest/api.html). In Matlab you can use the xlsread function (https://nl.mathworks.com/help/matlab/ref/xlsread.html).

The csv files you created with the “Data Explorer” (only available as from version 1.2.8) can be read in Python using the standard csv library (https://docs.python.org/3/library/csv.html). In Matlab you can use the csvread function (https://nl.mathworks.com/help/matlab/ref/csvread.html).


For GraphQL the gql library of Python can be used (https://github.com/graphql-python/gql). Make sure to install the latest version from Github (with pip you can use the following command: pip install -e git+git://github.com/graphql-python/gql.git#egg=gql). You can find 2 example Python scripts using gql on our Github page. For Matlab there is no extension or toolbox available for the moment.

Q23: Is it possible to connect to WiFi without the availability of a wired connection?

Yes, this is possible! From software version 1.2.6 on you can also use the hotspot instead of the wired connection to establish the wireless connection.

A WiFi hotspot is automatically created once the iQunet server is connected to the 230V mains. To use the hotspot, select the hotspot (SERN-xxxxxxxxxxx) in your network center and click Connect. The hotspot’s password is the Sensor Proxy ID (server-xxxxxxxx). This ID is written on your Unix server.

Go to Click on the 3 bars below the iQunet logo and open the Ethernet-WiFi control panel.

Select your WiFi network under the section “WIFI CLIENT”. Enable the encryption in “Layer 2 – Security”. Fill out your network key. Click the “Save” button and then the “Connect” button.

The hotspot will now be routed via your WiFi connection.

Q24: What is the difference between the temperature logger and the build-in temperature sensors?

All our industrial sensors have a temperature sensor on board. These build-in temperature sensors have a measurement range of -20°C to +70°C and an accuracy of +-0.5°C (max). Temperature is automatically logged every 15 minutes. These sensors should remain within the wireless range of the base station (be in contact with it) at all times.


Our temperature logger has a measurement range of -10°C to +85°C and an accuracy of +-0.4°C (max). This sensor can store the temperature data on board and thus keep logging even if it is outside of the range of the base station (e.g. to follow up the cold chain for food transport on a truck). When the sensor comes back in the range of the base station, the sensor will release the monitored data to the base station and store it on the iQunet server.

Q25: What happens if the wakeup interval is larger than the queue interval of the sensor?

The wakeup interval is an internal parameter of the iQunet sensors and indicates the maximum time interval at which the sensor must exit sleep mode and contact the base station to collect its scheduled tasks. If no task has been scheduled for this sensor or if the base station could not be contacted (for example because the base station is out of range), the sensor will return to sleep mode for the wakeup interval period. The purpose of the wakeup interval is to extend the battery life time.

The queue interval defines the time interval between two automatic measurements.

If the wakeup interval is larger than the queue interval, the measurements will only take place when the sensor goes out of sleep mode. When the sensor wakes up, it will contact the base station for pending measurements.