IoT Cloud Platforms☁

🔘Several previous posts have mentioned the 🔗Ubidots and 🔗Thingspeak IoT cloud ☁ platforms, conveniently accessed from a web-browser, that have been used with some of our sensor based projects to capture, visualise and analyse 💹 the sensor measurements. Two others, 'Arduino IoT Cloud' and 'Thingsboard', have been found and tried out in conjunction with the PMS5003 Particle Concentration Sensor; ( see 8 April & 16 June ). Setting up was quick and straightforward, following the typical process for such platforms of creating an IoT 'thing', assigning 'variables', associating a 'device', programming & connecting the device, & designing a 'dashboard'; our device is a "D1 Mini Esp32" micro-controller board.

The 🔗Arduino IoT Cloud is an entirely cloud based platform, including an editor for writing and compiling the project firmware, which can then be downloaded from the cloud ( depending on the subscription plan ) to the device, from anywhere in the world 🌐. Nothing is required to be installed locally on a pc 💻or connected to it other than a browser and internet connection. The dashboard shown in the image below is constrained by a maximum of  5 cloud variables under the no-time-limit free 🆓 plan. In general, the widgets to populate the dashboard tend to be the standard, classic ones.

Example of Arduino IoT Cloud dashboard - desktop version

An App "Arduino IoT Remote" on a mobile device 📱provides a mobile friendly version of the dashboard.

An account was opened for the 30 day free trial period of the 🔗Thingsboard cloud 'Maker' version. There is a large selection of attractive widgets for the dashboard, sorted by various categories. For example, under the "Air 🜁 Quality"  category there are numerous widget designs specifically for the measurement data relevant to air-quality. Some were chosen for the dashboard shown in the image below

Example of a Thingsboard dashboard

🌀IoT = Internet of Things.      

PM2.5 data from AQM now on the cloud

🔘Particulate Matter ㏘, PM2.5, data can now be uploaded 🖧 to the Ubidots cloud  ☁ from the Air Quality Monitor ( AQM ); see 15.03.2023. The Ubidots Ů platform provides visualisation / analysis of data from IoT sensors, also generating events, alerts, actions etc if required. We are already using this platform in conjunction with the Greenhouse Gas Monitoring system ( see 28.07.2022 ) and a soil moisture meter. On this occasion, with the AQM,  Node-Red is being used for alerts⏰.Two new widgets to display the PM2.5 concentration value have been added to an existing SpacerLabs Ubidots dashboard. The colours used for the air-quality levels ( good, OK, poor ) on the gauge widget match those used on the coloured LED indicator on the front of the AQM. 

Part of the dashboard showing the new widgets for PM2.5

Using the Node-Red 🟥 application, function 'nodes' are linked by connecting inputs to outputs and on-line services to create a 'flow' to perform task(s) using a browser based workspace. We have used it previously with the UVRM ( see 23.03.2023 ) and a soil moisture meter. The AQM flow ( image below ) starts by subscribing to the AQM PM2.5 data on Ubidots cloud using MQTT ( blue node ) and ends by triggering an email 📧 to be sent when the PM2.5 level exceeds 85 ug/m3; classified as level 'high' and air 🜁 quality 'poor'.

Node-Red 'flow' to trigger an email warning of poor air quality

It can be seen under the 'Debug' tab that an email 📧is indeed sent when PM2.5 >85; otherwise only the value ( if changed ) is reported. The email topic reads "SpacerLabs AQM - PM2.5 Alert " and the message reads "The SpacerLabs AQM has measured a PM2.5 level >85 (High) Air-Quality category - Poor. (Timestamp)". Even though the AQM may not be visible, an immediate audible notification is given by a smart phone when the email is received. 🔲

PM2.5 = Particulate Matter size 2.5 micron

MQTT = Message Queued Telemetry Transport

IoT = Internet of Things

🏭Greenhouse Gas Monitor - Real Time Data

       🔘The SpacerLabs "Greenhouse Gas Monitoring System" 🟩 was described on 28.07.2022 & 05.01.2023 🗓. Periodically since then it has been used to measure the outdoor concentrations of two potent green-house gases, Methane and Carbon Dioxide, in close proximity to "Spacerowa Laboratories" at 3m above ground level.  Methane ( CH4 ) and Carbon Dioxide ( CO2 ) concentration data in parts per million are now downloaded here every 15 minutes from the SpacerLabs Greenhouse Gas Monitor channel on ThingSpeak cloud ☁ for IoT sensor projects.

It has been noticed that increased concentration of methane coincides with wet weather conditions and vice-versa. According to NASA data, atmospheric concentration of CO2 was 416ppm in 2021, and CH4 was 1.8922ppm in 2020.

Lower left MQ-4 sensor, lower right MQ-135 sensor

The image above shows the outdoor part of the system with the two gas sensors, MQ-4 ( methane ) and MQ-135 ( carbon dioxide ), mounted in a weather-proof junction box,  ( cover removed ).

The blue trim-pot on each sensor breakout board can be used to set a concentration threshold level to trigger an alarm ⏰ and illuminate 💡 a LED ( just visible in the image ). Although active, the alarm condition is currently not being extended back to the micro-controller situated indoors for processing. 🔲

 

LoRa WAN

A "LoRa" ( Long Range )  wireless data link had already been used in a previous project to collect soil moisture data; but was not joined to a LoRa WAN network, in which nodes ( end-devices e.g. sensors ) are connected to gateways which then connect to the network server where the data from the end-device can be displayed and accessed by other applications for long-term storage and visualisation.

The public "TheThingsNetwork (TTN)" global IoT LoRaWAN network with the "Things Stack Community edition" server were used to test the possibility of connecting a node comprising a TTGO LoRa32v2 development board, before designing future projects with sensors. Only a short text message was to be sent; "TTGOLoRa32v2 node test".

The message was successfully received by a gateway 6kms away and forwarded to the server.

The upper image shows the experimental node in a temporary location by a window. The lower image is a partial screen capture of the live data on the server console.

 

TTGO LoRa32v2 node successfully joined TTN

Live data from the TTGO LoRa32 node on the Things Stack server

 

For more information on TheThingsNetwork visit https://thethingsnetwork.org

IoT = Internet of Things