Measuring Particulate Pollution With The ESP32

Air pollution isn’t just about the unsightly haze in major cities. It can also pose a major health risk, particularly to those with vulnerable respiratory systems. A major part of hazardous pollution is particulate matter, tiny solid particles suspended in the air. Particulate pollution levels are of great interest to health authorities worldwide, and [niriho] decided to build a monitoring rig of their own.

Particulate matter is measured by an SDS011 particulate matter sensor. This device contains a laser, and detects light scattered by airborne particles in order to determine the level of particulate pollution in PM2.5 and PM10 ranges. The build makes use of an ESP32 as the brains of the operation, chosen for its onboard networking hardware. This makes remotely monitoring the system easy. Data is then uploaded to a Cacti instance, which handles logging and graphing of the data.

For those concerned about air quality, or those who are distrustful of official government numbers, this build is a great way to get a clear read on pollution in the local area. You might even consider becoming a part of a wider monitoring network!

Building An Army Of ESP32 Air Quality Sensors

The ESP8266 and its heavyweight sibling the ESP32 are fantastic boards to develop with as they allow you to quickly and easily get a project online. Just tack a few sensors and some LEDs on them, and you’re well on the way to producing your own “Internet of Things”. The real challenge is utilizing the incredible capabilities these boards offer us to do something meaningful.

Judging by what he’s got so far, we think [Samuel Klit] is well on his way. He’s using the ESP32 and some off-the-shelf modular components to create an Internet-connected air quality monitoring station. But he’s not just building one or two of them, he’s building enough so they can be distributed and collect data over a wide area. Who knows, perhaps you’ll be building one next.

[Samuel] is using the CCS811 sensor which can pick up potentially harmful Volatile Organic Compounds (VOCs) and determine carbon dioxide concentrations, as well as a BMP280 sensor to read ambient temperature and atmospheric pressure. There’s also an SD card reader for local data storage, a 1602 LCD display that provides a basic user interface, and the electronics required to support the 18650 Li-Ion batteries which power the unit for up to 12 hours on a charge. Everything’s held in a professional looking enclosure that we’ll be sure to add to our next AliExpress order.

Collecting data is one thing, but what do you do with it once you’ve got it? To that end, each node runs a web interface that not only allows you to view current hardware status and download the locally stored data, but also provides an easy to understand visual representation of the environmental conditions. To get around the limited storage space for web assets on the chip, [Samuel] is calling out to Chart.js to inject some slick graphics into the web interface on-demand. The web interface is a particularly nice touch, and an excellent use of the power and capabilities offered by the ESP32.

We’ve previously seen air quality sensors added to Taxi cabs in Peru, the homes surrounding Barcelona’s Plaza del Sol, and of course [Radu Motisan] has done incredible work towards the goal of creating city-wide environmental monitoring networks. With increasingly capable technologies, it looks like citizens are studying the world around them in greater numbers than ever before.

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An Air Quality Monitor That Leverages The Cloud

Air quality has become an increasing concern in many urban areas, due to congestion and our ever-increasing energy use. While there are many organisations that task themselves with monitoring such data, it’s also something anyone should be able to take on  at home. [Chrisys] is doing just that, with some impressive logging to boot.

The build starts with a Raspberry Pi Zero W, which offers the requisite computing power and Internet connectivity in a compact low-power package. For determining air quality, the Bosch BME680 sensor is used. This offers temperature, pressure, and humidity readings, along with the ability to sense the presence of volatile organic compounds, or VOCs. These can be harmful to human health, so it’s useful to have an idea of the levels in your home.

The hardware is incredibly refined. It’s simple enough for the newbie, but just begs for the more experienced hacker to expand on.

On the software side, data is accessible through the Balena cloud service. Sensor readings are stored in an InfluxDB instance, with Grafana providing the visually attractive graphs and monitoring. It’s all very slick and Web 2.0, and can be accessed from anywhere through a web browser.

The project is a great example of combining a basic DIY Raspberry Pi setup with the right software tools to create a polished and effective end product. Of course, if you’re looking for something more portable, this project might be more your style. 

The Electric Imp Sniffs Out California Wildfires

The wildfires in California are now officially the largest the state has ever seen. Over 50,000 people have been displaced from their homes, hundreds are missing, and the cost in property damage will surely be measured in the billions of dollars when all is said and done. With a disaster of this scale just the immediate effects are difficult to conceptualize, to say nothing of the collateral damage.

While not suggesting their situation is comparable to those who’ve lost their homes or families, Electric Imp CEO [Hugo Fiennes] has recently made a post on their blog calling attention to the air quality issues they’re seeing at their offices in Los Altos. To quantify the problem so that employees with respiratory issues would know the conditions before they came into work, they quickly hacked together a method for displaying particulate counts in their Slack server.

The key to the system is one of the laser particle sensors that we’re starting to see more of thanks to a fairly recent price drop on the technology. A small fan pulls air to be tested into the device, where a very sensitive optical sensor detects the light reflected by particles as they pass through the laser beam. The device reports not only how many particles are passing through it, but how large they are. The version of the sensor [Hugo] links to in his blog post includes an adapter board to make it easier to connect to your favorite microcontroller, but we’ve previously seen DIY builds which accomplish the same goal.

[Hugo] then goes on to provide firmware for the Electric Imp board that reads the current particulate counts from the sensor and creates a simple web page that can be viewed from anywhere in the world to see real-time conditions at the office. From there, this data can be plugged into a Slack webhook which will provide an instantaneous air quality reading anytime a user types “air” into the channel.

We’ve covered a number of air quality sensors over the years, and it doesn’t look like they’re going to become any less prevalent as time goes on. If anything, we’re seeing a trend towards networks of distributed pollution sensors so that citizens can collect their own data on their air they’re breathing.

[Thanks to DillonMCU for the tip.]

Monitoring Air Quality, One Sleepy Meeting At A Time

To those of us in the corporate world, the conference room is where hope goes to die. Crammed into a space too small for the number of invitees, the room soon glows with radiated body heat and the aromas of humans as the time from their last shower gradually increases. To say it’s not a recipe for productivity is an understatement at best.

Having suffered through too many of these soporific situations, [Charles Ouweland] took matters into his own hands and built this portable air quality meter for meetings. With an OLED display on top and sensors inside, it displays not only the temperature, humidity, and barometric pressure, but also the CO₂ concentration and the levels of volatile organic compounds (VOC), noxious substances sometimes off-gassed from building materials, furniture upholstery, and coworkers alike.

The monitor quantifies his meeting misery, which we’re sure wins him points with his colleagues. For our part, though, what we find interesting is his design process. He started where many of us would, with an Arduino Uno. The sensor modules, a CCS811 for VOC and CO₂ as well as a BME280 for temperature, humidity, and pressure, both needed 3.3 volts, so he added a regulator to knock the Arduino’s 5-volt supply into range and some MOSFETs for level matching. Things were getting bulky, though, so he set about reducing the component count. The Uno went by stripping out its already programmed MCU. That killed the need for the regulator and MOSFETs, since everything would be happy with 3.3 volts. A few more rounds of optimization led to the final product, compact enough to run on a pair of AA batteries.

This is a great lesson in going from prototype to product. And it’s so compact, it could even ride on top of a Roomba to map the conference room’s floor-level air quality.

Hackers Vs. Mold: Building A Humidistat Fan

Having a mold problem in your home is terrible, especially if you have an allergy to it. It can be toxic, aggravate asthma, and damage your possessions. But let’s be honest, before you even get to those listed issues, having mold where you live feels disgusting.

You can clean it with the regular use of unpleasant chemicals like bleach, although only with limited effectiveness. So I was not particularly happy to discover mold growing on the kitchen wall, and decided to do science at it. Happily, I managed to fix my mold problems with a little bit of hacker ingenuity.

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Distributed Air Quality Monitoring Via Taxi Fleet

When [James] moved to Lima, Peru, he brought his jogging habit with him. His morning jaunts to the coast involve crossing a few busy streets that are often occupied by old, smoke-belching diesel trucks. [James] noticed that his throat would tickle a bit when he got back home. A recent study linking air pollution to dementia risk made him wonder how cities could monitor air quality on a street-by-street basis, rather than relying on a few scattered stations. Lima has a lot of taxis, so why wire them up with sensors and monitor the air quality in real-time?

This taxi data logger’s chief purpose is collect airborne particulate counts and illustrate the pollution level with a Google Maps overlay. [James] used a light-scattering particle sensor and a Raspi 3 to send the data to the cloud via Android Things. Since the Pi only has one native UART, [James] used it for the particle sensor and connected the data-heavy GPS module through an FTDI serial adapter. There’s also a GPS to locate the cab and a temperature/humidity/pressure sensor to get a fuller environmental picture.

Take a ride past the break to go on the walk through, and stick around for the testing video if you want to drive around Lima for a bit. Interested in monitoring your own personal air quality? Here’s a DIY version that uses a dust sensor.

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