Yet another linux on Chromebook post…

I have written about crouton that provides chroot installs of popular linux distributions like ubuntu, debian and kali. I followed that up by installing the official linux on Chromebook offering.

Now I just have to tell you about my new favourite solution – chromebrew

The reason I like chromebrew is that it simply extends chromeos to run like any other linux distribution – “…Chromebooks with Chrome OS run a Linux kernel. The only missing pieces to use them as full-featured Linux distro were gcc and make with their dependencies. Well, these pieces aren’t missing anymore…”

The biggest advantage with chromebrew is that it takes so little space, which is a limited quantity on most Chromebooks. It also has a good package manager, crew.

With crew, it is easy to add the apps you need, try ‘crew install nano’. Package installer scripts are written in ruby and support aarch64, arm7l, i686 & x86_64 processor architectures.Check out crew packages

Have fun!

Quick & dirty antenna comparison for LoRaWAN

One problem working  with LPWAN is having confidence that the antenna you just bought is effective.  From my experience, it is not reasonable to expect similar-looking antennae to be equally efficient, or even tuned for the same frequency band.

I decided to make a quick comparison of 6 antennae I had acquired over time from various suppliers. The method shown below is intended to simply identify the resonant frequency(ies) of each. The idea of the test rig is that the RF bridge enables matched connection of a white noise source, receiver (RTL-SDR) and the antenna under test. The RTL-SDR scans a suitable frequency band and the signal strength is plotted against frequency. The picture shows the 6 samples numbered 1 to 6 from left to right.

I based this test on the following article: –

The RF bridge and noise source can be bought cheaply from ebay –  as of posting, UK item numbers 232943112992 and 202335272932. The 50ohm terminator came from my parts bin, a relic from the days of ethernet over coax (10base2)…

The idea of the test is first to scan the the rig with no antenna connected. The 50ohm terminator ensures a matched circuit. I chose to scan from 50MHz to 1.5GHz in 1MHz steps and stored the signal strength  for each step as the baseline column in a Google spreadsheet – please don’t try this in Excel as manipulating so many values in a single spreadsheet will grind to a halt on a Windows PC.

Now each antenna is attached in turn and the scan repeated, giving columns Antenna1 to Antenna6. Next, each frequency step’s baseline value is subtracted from each Antenna’s corresponding signal strength. This results in  a lot of data that effectively indicates the resonant frequency(ies) of each antenna – as shown by the overlaid plots.

So, as an indication, it can be seen that Antenna1 (brown trace) is well-tuned for the European LoRaWAN band, whereas Antenna6 (pink trace) is pretty useless.

Note that this test cannot be used alone to determine best antenna, which would require real field trials, monitoring actual RSSI and SNR at a distance from an installed node/antenna. Resonant frequency, for example can be detuned by the node’s enclosure, mounting and/or large metal objects, such as batteries. An effective ground plane will dramatically improve both receive and transmission characteristics.

However, this test does give a quick comparison in the lab and can lead you to reduce the number of antennae used in field trials.

Running Docker on a docker-based OS

I have been following  RancherOS for quite some time, but somehow never got past just running the example as a VM. However, I have now installed on bare-metal and I have to say that it is a revelation.

To understand the basics, please take time to read the page and watch the video

The ISO is less than 100MB and there are versions for both Intel and ARM-based platforms and I set mine up on nothing fancy (a HP Compaq 8200 ultra-slim desktop with Core i3 and 8GB RAM). It took around 30 minutes to have running the current CE version of docker, together with a ubuntu console (more of which, later).

So, the idea is to boot off the ISO, install to hard drive and then access remotely via ssh – so I can hide the ancient HP box under my desk.

First, create a config file containing the public part of an ssh-key, something similar to this, taking care to indent the 2nd line


  - ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQC6KLZr...PT9I2rVkySlT7UmiFl rancher@rancher.local

Note: If you don’t yet have an ssh key-pair, take a look at this document: generate an ssh key-pair

Now, make your cloud-config.yml available via an HTTP server on your local network. A quick way to do this is in python:

python -m SimpleHTTPServer

This runs a simple HTTP server on port 8000, by default.

So, now switch to your target machine and boot from the Rancher OS ISO, available here:

While booting, start reading this:

You will see that Rancher have provided a very useful tool, called ros

So to install Rancher OS, is as easy as

sudo ros install -c http://[your-server-IP]:8000/cloud-config.yml -d /dev/sda

A word of caution – this didn’t work for me the first couple of times I tried it; the problem was the layout of the .yml file. Rancher must have seen this before, because they provide a yml file validator.
So, pull the .yml file to your local shell with:

wget http://[your-server-IP]:8000/cloud-config.yml

and run

sudo ros config validate -i cloud-config.yml

OK, so run the install command as above, answer yes when asked and Rancher OS will be installed to your hard drive.

Congratulations! You now have the bare minimum of OS on which to run your docker containers.

But wait – Rancher OS can be made even more useful by swapping out the default busybox console:

First, find out what consoles are available on your hardware:

$ sudo ros console list
disabled alpine
disabled centos
disabled debian
current  default
disabled fedora
disabled ubuntu

Then install your favourite – it’s just a docker container:

sudo ros console switch ubuntu

This action will drop your ssh connection, so log in again and go have some docker-based fun…

Storing your TTN node data in a noSQL database

This blog post is all about building a Node.js server to subscribe to the TTN MQTT(S) broker and store the data in a Mongo noSQL database. I am assuming that you have built a Node.js app before. There is also a suggestion of an application that will show your data.

The Things Network (TTN) is an open-source, secure and scalable solution that has around 5,000 gateways and 50,000 members around the world. It started in August 2015 and just keeps on growing.

TTN manages every aspect of creating and managing a LoRaWAN network except storing your data (note that TTN does offer a storage solution, but provides storage for 7 days only). There are several integrations available, including EVRYTHNG, AWS IoT, Cayenne and Tago. This example is useful if you want to keep your data in-house.

Just FYI, my example code, shown below, is running on a VPS with an instance of ubuntu xenial server, hosted by for around €3/month.

First, install the following components

Mosquitto – lightweight broker/client for MQTT
Node.js – javascript run-time environment – I used V8.x LTS
MongoDB – noSQL database, ideal for json-formatted data

Then create a Node.js application, which typically consists of

package.json – describes app, dependencies, licence, etc.
config.js – store for all configuration data – URL, username, etc
(Note: contains your db password & MQTT access key in plain text!)
server.js – the Node.js app
mqtt-ca.pem – enables use of TLS encrypted MQTT traffic (available from your TTN console)

package.json typical contents:

    "name": "ttn-mqtt-database",
    "description": "Listens to MQTT messages and stores in MongoDB",
    "version": "1.0.0",
    "dependencies": {
	"mongodb": "^3.0.3",
	"mqtt": "2.15.1",
	"ttn": "^2.3.1"
    "repository": {
    	"type": "git",
      "url": "[your github repository].git"

config.js contains the configuration information to subscribe to your specific MQTT channel and the connection credentials and path for your mongo database

var config = {};

config.debug = process.env.DEBUG || true;

config.mqtt  = {};
config.mqtt.namespace = process.env.MQTT_NAMESPACE || '+/devices/+/up';
config.mqtt.protocol  = process.env.MQTT_PROTOCOL  || 'mqtts://';
config.mqtt.hostname  = process.env.MQTT_HOSTNAME  || '';
config.mqtt.port      = process.env.MQTT_PORT      || 8883;
config.mqtt.user      = process.env.MQTT_USER      || '[name of your TTN application]';
config.mqtt.password  = process.env.MQTT_PASSWORD  || 'ttn-account-v2.[your TTN key]';
config.mqtt.cafile    = process.env.MQTT_CAFILE    || 'mqtt-ca.pem';

config.mongodb = {};
config.mongodb.user       = process.env.MONGODB_USER       || '[user]';
config.mongodb.password   = process.env.MONGODB_PASSWORD   || ‘[your ultra-secret password]';
config.mongodb.hostname   = process.env.MONGODB_HOSTNAME   || '[your server DNS]';
config.mongodb.port       = process.env.MONGODB_PORT       || 27017;
config.mongodb.database   = process.env.MONGODB_DATABASE   || 'mqtt';
config.mongodb.collection = process.env.MONGODB_COLLECTION || 'nodedata';

module.exports = config;

The code for your Node.js server should look something similar to this:


var mongodb  = require('mongodb');
var mqtt     = require('mqtt');

var fs       = require('fs');
var config   = require('./config');

var client = mqtt.connect(config.mqtt.hostname, {
            ca: [fs.readFileSync(config.mqtt.cafile)],
          username: config.mqtt.user,
          password: config.mqtt.password,
              port: config.mqtt.port

client.on('connect', function () {

var mongoUri = 'mongodb://' + config.mongodb.user + ':' + config.mongodb.password + '@' + config.mongodb.hostname + ':' + config.mongodb.port + '/' + config.mongodb.database;

mongodb.MongoClient.connect(mongoUri, function(err, client) {
    if(err != null) {
        throw error;
    else {
        var mydb = client.db('mqtt');
        var collection = mydb.collection(config.mongodb.collection);
        collection.createIndex({ "topic" : 1 });
        client.on('message', function (topic, message) {
        var messageObject = {
            topic: topic,
            message: message.toString()
        collection.insert(messageObject, function(err, result) {
            if(err != null) {
                console.log("ERROR: " + err);

To see the data stored in your mongo database, either use the mongo client:

cli access via mongoDB client
user@demo:~/ttn-demo# mongo
> use mqtt
> db.message.find();

Or use a GUI app, like NoSQLBooster for MongoDB

A useful noSQL query would be similar to this, which shows the last 20 messages from a specific device called pycomr001:

db.nodedata.where({'device': 'pycomr001'}).sort({ "natural": -1}).limit(20);

So, in summary:
TTN provides an excellent platform to move your node data to the cloud
TTN enables access via a secure MQTT broker
MongoDB is a noSQL db, good for JSON data
Node.js is a simple way to build a headless server app
NoSQLBooster for MongoDB is a good GUI to access your db
systemctl is a sensible method to manage your app

Now, it’s down to you to do something useful with your data!

Technical overview of LoRa, LoRaWAN and The Things Network

The Radio Spectrum

Radio-connected devices work within a certain frequency range. The radio spectrum is allocated by government and licensed for specific functions.

For example, broadcast radio currently has a reserved VHF band from 88 to 108 MHz.

Cellular phones have several reserved frequency bands around 900 MHz and 1800 MHz.

The licensees pay for use within these bands. However, there are some specific bands that are made available for low power use, license-free.

2.4GHz is a global band that allows low power unlicensed operation; this is where WiFi and Bluetooth co-exist.

Some license-free bands are allocated differently by each country and LoRa is designed to work in the appropriate band for each country or region. For example, Europe is covered by 863-870MHz, North America, Canada & South America by 902-928MHz. TTN provide details of global frequency plans –

LoRa radio technology

LoRa is a technology that works well within a crowded radio spectrum.

It uses a technique called chirp spread spectrum that creates a signal which is distinguishable by the receiver from the atmospheric noise and signals created by other devices that use simpler modulation techniques, such as On Off Keying (OOK) and Frequency Shift Keying (FSK).

LoRa also takes advantage of a feature called Spreading Factor (SF) where the spreading factors are the duration of the chirp. LoRa operates with SF7-12. SF7 is the shortest time on air, SF12 the longest. Each step up in spreading factor doubles the time on air to transmit the same amount of data.

With the same bandwidth, longer time on air obviously results in less data transmitted per unit of time.

So, with very little output power, the LoRa signal can be detected at great distance or through infrastructure that attenuates the signal. Typically, this could be 1-3km in an urban environment. The current record distance is just over 700km from a node under a helium balloon at a height of 40km, at an output power of only 25mw. For comparison your car key fob works at 2mw for a couple of metres and your phone at up to 1W to the nearest cellphone mast, at most 30km distant.

The trade-off for LoRa is that low power and long distance is traded for limited data rate. Maximum data rate at SF7 is 6kbits/s, reducing to 300bits/s at SF12. One key figure RF engineers discuss is “link budget”, bigger is better and Spreading Factor affects the number where SF12 gives the best chance to receive data. For more information –

There are payload size limitations for LoRa – in EU it’s 230 bytes per transmission at SF7, 59 bytes at SF12. Consider LoRa only for telemetry data, such as location, heading, height, temperature, pressure and humidity values or simple on-off actions.

The LoRaWAN protocol

LoRaWAN is a communication protocol that runs on LoRa hardware.

LoRaWAN operates in a star of stars network with ability for multiple gateways to receive and forward data from any nearby node to The Things Network.

Each multi-channel LoRaWAN gateway can scan 8 channels simultaneously and decode up to 8 data packets at the same time. Several packets using different data rates may be demodulated simultaneously even on the same channel.

LoRaWAN provides several modes of operation – modes A, B & C, where B is allocated a time slot and C devices are permanently powered on and receiving.

Most nodes run as mode A devices where they occasionally wake up to transmit a small amount of data and listen for a short time after transmission for any received data. Working like this, it is possible to construct a node that can transmit an update every 30 minutes and run off 2 ‘C’-size alkaline batteries for more than 5 years.

Each mode A node is free to transmit at any time, with the limitation in Europe that each node should not exceed a 1% duty cycle.

There are predictive formulae available to show that the combination of multi-channel gateways, small data packets, operational modes and Spreading Factors results in the capability to handle thousands of nodes per gateway. See “Understanding the Limits of LoRaWAN (Adelantado, Vilajosana et al, IEEE magazine January 2017)” –

The Things Network originally provided complete LoRaWAN coverage for the city of Amsterdam with just 10 gateways –

The Things Network

The Things Network is an open-source, free-to-use solution that provides all functions necessary to:

  • Register a gateway
  • Register a node
  • Handle encryption and decryption of payload data.
  • Route the data between node and the internet using MQTT-broker technology.
  • Queue data for transmission to each node.
  • Monitor and action the process through API

The Things Network does all this and more on a scalable, resilient platform with regional bridge access globally.

The Things Network is provided as open-source solution by The Things Industries. Gateways are being made available worldwide by The Things Network community – see and try it for yourself! it costs less than £200 to setup your own.

The Things Industries also deliver private LoRaWAN solutions with guaranteed SLA, so be assured that you can develop a solution and build it out to a stable product.

For more information, please get in touch – take a look at

Linux on Chromebook just became extremely simple…

My previous post “My new go-to linux dev machine is a Chromebook…” seems now to be obsolete. Google have released a “linux mode” in Chrome version 69 for Chrome OS. This is the project “crostini” that was first made available on the Pixelbook.

There are a couple of gotchas, such as it is only beta so far and is only supported on certain Chromebooks – see here for more information: linux mode capable chromebooks – note it says that Chromebooks like the HP 14 G3 running 32-bit ARM and others using Baytrail x86 CPU devices will never support linux mode.

Luckily, my ASUS Chromebook Flip C101PA is on the list. So, no need to reset and set developer mode, just simply select Settings -> Linux(Beta) and go for lunch – this is definitely more than a coffee install.

You will see a new app on your Chromebook – “Terminal”. The username and password are those of your Google account – so, launching Terminal, I see a prompt of “nicbkw@penguin:~$”. Click  (touch & hold) on the Terminal icon in the appfinder and you have the options to uninstall and shutdown Linux(Beta). Clicking on the launched Terminal icon, you will see the option to open new windows, meaning it is possible to run multiple terminal session windows as well as browser and your other chromebook apps.

The distribution is debian stretch and installing apps is as simple as “sudo apt-get install gimp”. The GUI runs natively in the Chrome OS environment and this linux app appears alongside other ordinary Chrome OS/Android apps – see the header image.

The linux virtual machine, together with any data you store while using it persists between sessions, so you can quit apps, logout, etc without worrying about resetting anything. All data is stored in the same encrypted storage as other Chrome OS data.

My new go-to linux dev machine is a Chromebook…

The other day I arrived at work to discover I had left my laptop at home. I hot-desk some days each week in Liverpool in fabulous SensorCity (@SensorCityUK) and was lost without a keyboard and ability to geek. Fortunately, just 5 minutes walk away is the local branch of a well-known UK “previously-loved” chain, so I went for a meander. I returned with an ASUS C101PA ChromeBook for less than half-price. It has a 10.1″ 1200×800 touchscreen with 6-core ARM CPU, 4GB RAM, 16GB eMMC, USB-C charging and a 9-hour battery – what should a geek do???

The answer is to enable Chrome Developer mode and install xenial ubuntu, of course – note that you should backup before enabling as this will factory reset your chromebook and delete all your data. Warning over.

It is possible to run a full linux desktop (something lightweight, like xfce, bearing in mind the free space on the eMMC), but I like working with a command line and you will see that you end up with linux running in one or more Chrome Tabs, while retaining full access to the Chrome/Android side of things – browser, email, 6Music on BBC Radio iPlayer, etc.

So, The best instructions are those available from the master – take a look at

Here are the basics:

1. Enable developer mode –
2. Download the current version of crouton from here – crouton
3. Open a shell (Ctrl+Alt+T, type shell and hit enter)
4. Run sudo sh ~/Downloads/crouton -t core – wait patiently and answer the prompts to add user, etc.
5. Done! Run sudo enter-chroot

The result is an arm64 install of ubuntu xenial that has access to serial over USB, USB and SD card storage

So far, I have:

1. mbed-cli to build and flash code to STMicro Nucleo boards – this installed build-essential, git, python, etc.
2. go version go1.10.3

I am very impressed. So, don’t dismiss chromebooks as over-sized androids, poor iPad substitutes, especially if you can pick up a bargain…

STMicro DISCO-L072CZ-LRWAN1 quickstart with mbed-os

There is a great article on the ARM mbed website about their support of LoRaWAN.

Their code has improved a lot this year. Previously, it was a little tricky to work with – there is now a clean install available on github that can be built locally from the command line on Mac, Windows or linux. using the GNU ARM embedded toolchain and mbed-os.

I describe below a simple recipe to use this code with the STMicro DISCO-L072CZ-LRWAN1 evaluation board (pictured). The code can be simply adapted to run with the sx1272 mbed shield on STMicro Nucleo boards and there is also support for the RAKWireless RAK811 node.

I am assuming that you have already registered your device in your application in your TTN console:[your application name]/devices

1. Setup the GNU ARM embedded toolchain and install mbed-cli:

On a Windows 10 PC – just use the installer that you can download from here:
mbed-cli installer

The Windows installer for Mbed CLI includes the following components:

  • Python – Mbed CLI is a Python script, so you need Python to use it. The installer installs version 2.7.13 of Python. It is not compatible with Python 3
  • Mbed CLI version 1.2.2 – Mbed CLI
  • Git and Mercurial – Mbed CLI supports both Git and Mercurial repositories. Both Git and Mercurial are being installed. git and hg are added to system’s PATH
  • GNU Arm Embedded Toolchain – GNU Embedded Toolchain for Arm
  • Mbed Windows serial port driver – serial port driver

Note that the Windows installer sets all paths and even configures some MBED variables
Check the path to the gcc compiler:
mbed config -L

On a Mac – use homebrew – remember to brew update && brew upgrade before installing
If you need to install homebrew first, then
/usr/bin/ruby -e "$(curl -fsSL"
Otherwise, just:

brew tap ArmMbed/homebrew-formulae
brew install arm-none-eabi-gcc
brew install python@2
brew install mercurial
brew install git
git clone
cd mbed-cli
python install

Check the version of mbed-cli and that it is installed OK – version should be =>1.8.2
mbed-cli --version
Check the install location of arm-none-eabi-gcc with
which arm-none-eabi-gcc
Set path for mbed
mbed config -G GCC_ARM_PATH "/usr/local/bin"

On a linux machine, here is a typical install (I used ubuntu xenial)

sudo apt-get install software-properties-common
sudo add-apt-repository ppa:team-gcc-arm-embedded/ppa
sudo apt-get update
sudo apt-get install gcc-arm-embedded
sudo apt-get install build-essential libssl-dev libffi-dev libxml2-dev libxslt1-dev
sudo apt-get install mercurial git python-dev python-pip
pip install mbed-cli
mbed-cli --version
which arm-none-eabi-gcc
mbed config -G GCC_ARM_PATH "/usr/bin"

2. Pull the example code from the mbed github and create the local mbed-os environment in the folder, using mbed-cli (note that ‘mbed-cli’ also works using just ‘mbed’)

mbed import mbed-os-example-lorawan
cd mbed-os-example-lorawan/

3. Configure for your node
edit mbed_app.json to configure lora.device-eui, lora.application-eui, lora.application-key

4. compile and send to evaluation board (assumes there is only one ST-Link/Nucleo/DISCO board connected)
mbed compile -m DISCO_L072CZ_LRWAN1 -t GCC_ARM --flash

5. use mbed as your terminal emulator:
mbed sterm --baudrate 115200

Note that on linux, it may be necessary to change user permissions for the serial port, similar to:
sudo chmod 666 /dev/ttyACM0

6. press the black reset button on the DISCO board
You should see this:

 Mbed LoRaWANStack initialized
 CONFIRMED message retries : 3
 Adaptive data  rate (ADR) - Enabled
 Connection - In Progress ...

After a few seconds, this should appear:

 Connection - Successful
 Dummy Sensor Value = 2.1
 25 bytes scheduled for transmission
 Message Sent to Network Server

Any questions? Please get in touch…

Using node-red with ST NUCLEO L073RZ Sx1272

I have been working with the great LoRaWAN combo from STMicroelectronics – a low-cost dev board based on a ARM®32-bit Cortex®-M0+ CPU, coupled with the Sx1272 on an Arduino-compatible shield.

Using the online mbed compiler – , I modded the demo code – LoRaWAN-demo-72 – to add simple output to an OLED display – see attached photo.

My node-red install runs on a server hosted by that costs around €3/month. I designed a very simple activity monitor – the design of which may help others.

To the basic node-red install, I added node-red-contrib-ttn and node-red-dashboard.


The dashboard output looks like this:


Here is the node-red code:

[{"id":"cd89d617.a9d0e8","type":"function","z":"546def68.3e374","name":"Extract data","func":"count = {}\nrssi = {}\nsnr = {}\n\n//var b = new Buffer(msg.payload_raw);\n//count.payload = (b[1] << 8 | b[2]).toString();\n//var r = b[3] << 8 | b[4];\n//if ((r & 0x8000) > 0) {\n// r = r - 0x10000;\n//}\n//rssi.payload = r.toString();\n//snr.payload = (b[5]).toString();\n\ncount.payload = msg.counter;\n\nrssi.payload = msg.metadata.gateways[0].rssi;\nsnr.payload = msg.metadata.gateways[0].snr;\n\nreturn [count, rssi, snr];","outputs":"3","noerr":0,"x":230,"y":280,"wires":[["6de8dcb1.29b284"],["72787db7.d4bdf4","a262c4ea.068798"],["21f1441a.e028fc","e6796eca.3e2ec"]]},{"id":"6de8dcb1.29b284","type":"ui_text","z":"546def68.3e374","group":"3d90cd90.e1c9c2","order":7,"width":0,"height":0,"name":"txtCount","label":"Count","format":"{{msg.payload}}","layout":"row-spread","x":440,"y":220,"wires":[]},{"id":"72787db7.d4bdf4","type":"ui_text","z":"546def68.3e374","group":"3d90cd90.e1c9c2","order":5,"width":0,"height":0,"name":"txtRssi","label":"RSSI","format":"{{msg.payload}}","layout":"row-spread","x":430,"y":260,"wires":[]},{"id":"21f1441a.e028fc","type":"ui_text","z":"546def68.3e374","group":"3d90cd90.e1c9c2","order":6,"width":0,"height":0,"name":"txtSnr","label":"SNR","format":"{{msg.payload}}","layout":"row-spread","x":430,"y":340,"wires":[]},{"id":"69c26716.6f6598","type":"ui_text","z":"546def68.3e374","group":"3d90cd90.e1c9c2","order":1,"width":0,"height":0,"name":"txtDevice","label":"Device","format":"{{msg.dev_id}}","layout":"row-spread","x":440,"y":60,"wires":[]},{"id":"89e50c80.55a11","type":"ui_text","z":"546def68.3e374","group":"3d90cd90.e1c9c2","order":3,"width":0,"height":0,"name":"txtDataRate","label":"Data Rate","format":"{{msg.metadata.data_rate}}","layout":"row-spread","x":450,"y":140,"wires":[]},{"id":"d312c0a6.afb48","type":"ui_text","z":"546def68.3e374","group":"3d90cd90.e1c9c2","order":4,"width":0,"height":0,"name":"txtCodingRate","label":"Coding Rate","format":"{{msg.metadata.coding_rate}}","layout":"row-spread","x":460,"y":180,"wires":[]},{"id":"2065149f.497fbc","type":"ui_text","z":"546def68.3e374","group":"3d90cd90.e1c9c2","order":2,"width":0,"height":0,"name":"txtFrequency","label":"Freq.","format":"{{msg.metadata.frequency}}","layout":"row-spread","x":450,"y":100,"wires":[]},{"id":"a262c4ea.068798","type":"ui_chart","z":"546def68.3e374","name":"","group":"3d90cd90.e1c9c2","order":8,"width":0,"height":0,"label":"Signal Strength","chartType":"line","legend":"false","xformat":"HH:mm:ss","interpolate":"linear","nodata":"","dot":false,"ymin":"-150","ymax":"0","removeOlder":1,"removeOlderPoints":"","removeOlderUnit":"3600","cutout":0,"useOneColor":false,"colors":["#1f77b4","#aec7e8","#ff7f0e","#2ca02c","#98df8a","#d62728","#ff9896","#9467bd","#c5b0d5"],"useOldStyle":true,"x":460,"y":300,"wires":[[],[]]},{"id":"e6796eca.3e2ec","type":"ui_chart","z":"546def68.3e374","name":"SNR","group":"3d90cd90.e1c9c2","order":9,"width":0,"height":0,"label":"Signal:Noise Ratio","chartType":"line","legend":"false","xformat":"HH:mm:ss","interpolate":"linear","nodata":"","dot":false,"ymin":"0","ymax":"10","removeOlder":1,"removeOlderPoints":"500","removeOlderUnit":"3600","cutout":0,"useOneColor":false,"colors":["#1f77b4","#aec7e8","#ff7f0e","#2ca02c","#98df8a","#d62728","#ff9896","#9467bd","#c5b0d5"],"useOldStyle":true,"x":430,"y":380,"wires":[[],[]]},{"id":"7819848e.fd117c","type":"ttn uplink","z":"546def68.3e374","name":"unosx1272","app":"c7f29eb8.f2f1f","dev_id":"unosx1272","field":"","x":120,"y":60,"wires":[["cd89d617.a9d0e8","69c26716.6f6598","2065149f.497fbc","89e50c80.55a11","d312c0a6.afb48"]]},{"id":"3d90cd90.e1c9c2","type":"ui_group","z":"546def68.3e374","name":"unosx1272","tab":"a104b487.87dca8","order":2,"disp":true,"width":"6","collapse":false},{"id":"c7f29eb8.f2f1f","type":"ttn app","z":"","appId":"<app-id>","accessKey":"<app-key>","discovery":""},{"id":"a104b487.87dca8","type":"ui_tab","z":"546def68.3e374","name":"devices","icon":"dashboard"}]


Raspberry Pi Zero W – $10 Citrix endpoint? maybe not…

I received an email from The PiHut on Tuesday, ordered a Raspberry Pi Zero W and case. It arrived two days later – the case, for £6, is impressive; 1 base and 3 lids – one plain, one for camera and one for GPIO access. Note that the case also came with the short ribbon cable required to connect the standard Raspberry Pi camera.

The board is yet another technical marvel from the Pi team and the biggest question for me was how did they find board area to include the WiFi/bluetooth 2.4GHz antenna? It is all explained in this post: – it definitely works.

When starting up headless or remote, the issue always with the official raspbian distribution is the Catch 22 issue of how to configure WiFi without access to a console. One way is to connect a serial console on the GPIO ports; I chose a faster way – use a Micro SD card from an already-configured Pi Zero 😉 – loaded with raspian jessie pixel lite.

As an aside – an alternate linux distribution I often use for Raspberry Pi and other ARM boards comes from DietPI – the beauty of this is that there is a text file in the root of the image that can be edited to include your WiFi SSID and password.

So, the board and WiFi work as expected from my previous experience with the Pi Zero. Next step was to run it as a desktop with the full version of rasbian jessie pixel. Not having a bluetooth keyboard to hand, I decided to use my Logitech K400+ keyboard/trackpad combo, connected via a very useful OTG 4-port USB2.0 hub.

The result? Pixel desktop on a Pi Zero is really not very useful, with this YouTube video hammering the CPU @ 100% with stutter. Of course, the single core 1GHz CPU is the limiting factor and a GUI like Pixel needs the 4-core design of the Raspberry Pi 3 Model B.

However, The Pi Zero W is perfect for my current project, running as a controller for sub-1GHz FSK radio sensors, communicating via LwM2M, parsing the data and then uploading via LoraWAN to an AWS IoT gateway over GSM – if that very brief description has whetted your appetite, then wait for my next post!