Someone is illegally making charcoal at night (like 1-2 AM), likely as far as 3-4 km away. I am trying to build an Arduino package fitted with sensors to trace the awful "smell" (which wakes me up nightly from sleep) to the strongest source.
Ideally, I would have a drone fly the package, fitted with a GPS module, and its flight path altered as it traces the strongest source of the "smell". I don't trust myself flying a drone at night, so I'd rather have the drone programmed to search/seek and return home automatically. The drone is probably $3000 at the very least, and it's not within my budget at all.
However, I can probably start work on the Arduino sensors, perhaps mount this on a pole as I drive around at night (in my 20-year-old car), and take sensor measurements and wind direction readings to narrow the search. I also have worked with an Arduino-CO2 sensor 6 years ago.
Considerations: The smoke is completely invisible at night (from IR, thermal cameras), the source is as far as 3-4 km away (based on feedback from other affected individuals), possibly sheltered under trees and a make-shift shelter from rains, and even as far as 200m from the nearest accessible road. Only the smoke's "smell" can be detected.
I'd like to obtain tips on which (outdoor) sensors would be best for this task. I imagine MQ or PM sensors, but I have not worked with any of them before, and real-life experience on these sensors would be greatly appreciated. TIA.
This is a lot of effort to find a single source .
Why not go out for a drive one night and trace it .
If you do go for complex systems such as drones , what will you do with the results ?
The source (highest concentration of detected gasses from multiple sensors) would definitely be far from the nearest road, at least 200 meters (as they have to hide from the nearest houses). Many trees, hills, rocks and plunging/climbing 10-100ft below/above the road is part of the challenge of driving to the source. Once the likely location is found, I'll provide the location to the environmental authorities who do act on the complaint - but they too cannot find the source. You're right it's a lot of effort, but the fumes from the charcoal making activity has already caused my asthma to come back. I might go for a custom programmable drone build - which might bring the drone's cost below $800. It definitely needs to carry a package of at least 500g (arduino+sensors+battery), fly at least 30 mins using calculated GPS coordinates from the arduino, and cover an area of maybe 9-10 sq.km, then return/land safely back home automatically at night with all the data.
It is illegal (here) and (here) we have national and local/community laws against it. That IR cam will be useless - when the assumed target is under dense trees (think mango trees 30-100 ft tall, with canopy diameters over 100 ft), possibly under a makeshift shelter, and very likely below ground covered with soil. You don't really measure a smell, you measure the concentration of gasses that coincidentally emit smells.
So far, this is the list of sensors I am considering, but again I have not worked with any of these, so I am uncertain how suitable they are for the task. I have only worked with a CO2 sensor some years back.
MQ-2 Gas Sensor: Detects gases such as propane, methane, and smoke; useful for identifying combustible gases and smoke.
MQ-135 Air Quality Sensor: Measures a variety of air pollutants, including benzene, alcohol, and ammonia, to assess air quality.
MQ-7 CO Sensor: Specifically designed to detect carbon monoxide (CO) concentrations in the air.
PMS5003 PM2.5/PM10 Sensor: Measures particulate matter (PM2.5 and PM10) in the air, helping to assess air pollution levels.
BME280 Sensor: Measures temperature, humidity, and atmospheric pressure; useful for environmental monitoring.
Wind Speed and Direction Sensor: Measures the speed and direction of the wind, which can help determine the source of air pollution.
MH-Z19 CO2 and Formaldehyde Sensor: Measures carbon dioxide (CO2) and formaldehyde levels in the air.
I too have little confidence in the drone/sensor-based approach. In principle it could work, but the practical implementation is kind of complex. You need to determine the 'signature' of a charcoal-producing operation in terms of the measured parameters. Then exclude all false negatives (e.g. wood-burning stoves etc.) When collecting data, you'll need to include data on very local wind speed and direction so you can guesstimate where the origins of your measurements would be. Ideally you would be able to measure a 'plume' coming from the production location, but getting this sort of data would likely be beyond the technical capabilities of a small DIY drone system. Collecting such data would require hovering pretty close to the production location for an extended period of time, which will surely alert the charcoal people since a drone is pretty noisy.
A more feasible approach I think is to track them based on the logistics movements involved in transporting the wood to the production location, and perhaps also the charcoal from it towards the market. This likely leaves traces in the surroundings. You'd have to hike around a bit and look for well-used tracks in places where there's apparently nothing of interest.
Alternatively, the social approach can work well; basically ask around until you find rumors about this alleged charcoal production and then see if you can identify people close to the operaton so you can report them to the authorities. I'm feeling queasy typing this as you're well within ethically very dubious territory by now.
I'm sorry about your asthma; it's a bitch; I remember it from childhood. No fun at all.
It would be a fun exercise to mount a PMS5003, MQ-2, and MQ-7 on a drone, and then when you smell the emissions fly the drone in a pattern such as shown in the following snip, with each pass separated by about 500 m, and the zig-zags going upwind for four or five km.
After downloading the data, do a 3d plot of the measurements, georeferenced on a Google Earth image.
With a few nights of this, I bet you'd see patterns that help you know where to look.
That social approach is Plan B, instead of building anything, I offer my limited budget as reward money. Good point on the false negatives, the drone could end-up at someone's BBQ party. But I have always planned on releasing the drone at around 1-4am.
Thanks, that pretty much visualizes what I have been thinking.... what I don't really know is if those arduino sensors would work well enough in that open sky environment. I imagine the drone would be flying at least 150ft off the ground to avoid trees etc.
That's my primary concern - would any of these sensors work well enough in the open sky. Sure, they'd probably work indoors great, but how well do they work outside?
Whether any of the sensors will do the job depends on the concentration of the gasses or particulates at the drone elevation. I doubt anyone knows that, so you will probably just have to bite the bullet and try it yourself.
FWIW, the PMS5003 is in a widely used commercial product called Purple Air. United States government air quality maps include their data, as well as official sensor data.
You could try mounting the sensors at your home and then see if they register any changes when the charcoal smell starts.
But the concentrations will be higher closer to the source, so the drone idea could work even though a home test may be disappointing.
Edit to add:
Suggest you not attempt to program the drone to try to zero in on the source. I suspect that may be hard.
On the other hand, if you plot the data as I suggested, I bet your brain will much more easily synthesize the data and pull the signals from the noise (if they're there...)
That's a good point, thanks. Though I live outside the city, the air is definitely cleaner after it rains. I'll have to do a baseline reading of each sensor right after a good rain, and mark that as "clean air" reading.
