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Street Sense

Portable electronic device to measure air and noise pollution

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Street Sense is a project to build a portable, battery-powered sensor unit to measure:

Air Quality: Ozone, NO2, Particulates
Noise Pollution
Environment: Temperature, Humidity

There are two NGO sponsors. They require a sensor that can help them answer some important questions:
1. What air and noise pollution effects are experienced by people at the street level?
2. Can we quantify the changes in street level pollution resulting from a capital infrastructure project?

The project name "Street Sense" seems appropriate - sensing the environment at the street level in the urban landscape

Street Sense Features:

  • Measurement sensing:
    • ozone, in ppb
    • NO2, in ppb
    • PM2.5 particulates
    • audio recording for post analysis
    • temperature and humidity
  • Measurement recording
    • on-board micro SD Card media
    • continuous recording of audio stream to WAV file
    • air quality measurements logged to files
    • SD Card removable to enable file download
    • recorded data is time-stamped
  • Power
    • battery or USB powered
    • minimum 8 hours operation time on battery
    • USB rechargeable without battery removal
  • Enclosure
    • weatherproof
    • simple attachment to a street level structure such as a lighting pole
    • allows air flow thru 
  • Connectivity
    • WiFi for pushing sensor data to an internet cloud database
  • User Interface
    • on-board display to view readings and verify operation
    • simple operation requiring minimal training
  • 100% Open
    • Open Hardware - schematics, BOMs, etc
    • Open Software - all firmware and software hosted on public github account

Stretch ambitions:

  • on-board audio sample processing to calculate real time dB
  • open API to allow customization using MicroPython


Project Parts Budget:  USD $225

   

Functional Block Diagram showing major components


"Need Help" Section:

This section describes areas where I am having difficulties and could use some help from Hackaday experts.  Please consider commenting if you have ideas on any of these problems.  thanks!

April 2019:

1.  Oscillations from Spec Sensor ozone and NO2 sensors.  I think it is caused by noise in the 3.3V rail power supplied to both the sensors and ADC.  The initial breadboard proto no doubt contributes to this problem.  Described in this project log.   Any ideas appreciated!  e.g.   LC filtering to create cleaner analog power rail?   Is it worth trying to make a soldered proto?   Or, is a custom PCB the only way to improve this?

2.  SDCard write delays.   The 10GB card that I am using (SanDisk Ultra 16GB) claims to be a class 10 device.  But, some 512Byte sector writes take a really long time...e.g.  >50ms.  And, there can be multiple back-to-back writes > 50ms.  These long SDCard write block the waiting coroutines in the cooperative multitasking asyncio design.  My main need is fast writes.  Fast reads don't matter for this application.  Are there better choices for SD Cards that support fast writes?

Street Sense Schematic-V08.pdf

Version 8 of Street Sense air and noise pollution sensor unit - added separate analog supply - reading ADC using ADC ~DRDY signal and uPy interrupt

Adobe Portable Document Format - 74.90 kB - 05/14/2019 at 16:16

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Adobe Portable Document Format - 69.76 kB - 03/25/2019 at 16:52

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Street Sense Schematic-V05.pdf

Version 5 of Street Sense air and noise pollution unit - new ADS1219 ADC

Adobe Portable Document Format - 67.74 kB - 03/18/2019 at 16:37

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Street Sense Schematic-V04.pdf

Version 4 of Street Sense air and noise pollution unit 3 changes to reduce noise created by boost converter - added high side MOSFET switch - added Schottky diode to USB/Battery select cct - added capacitor to input of boost converter

Adobe Portable Document Format - 64.26 kB - 03/14/2019 at 23:08

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Street Sense Schematic-V03.pdf

Version 3 of Street Sense air and noise pollution unit

Adobe Portable Document Format - 60.52 kB - 02/13/2019 at 22:21

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  • From Breadboard to Enclosure - Part 3

    Mike Teachman06/26/2019 at 19:07 0 comments

    Continuing with stripboard construction methods, the ozone and NO2 sensor module was built.  This module also contains a LDO voltage regulator, the 24-bit ADC, and a temperature sensor.  The readings from the two sensors will need to be compensated wrt temperature - that is the reason to locate the temperature on this module.   An overview of the modules is described in an earlier project log From Breadboard to Enclosure - Part 1.

    This stripboard module can be considered a stepwise improvement.  Compared to the boardboard prototype it should give improved performance for the Spec Sensor modules, but will still be lacking compared to a properly laid out PCB.

    The module includes the major components U6, U8, U9, U10, U11 found in the schematic.

    The next log will outline the construction of the final module, containing the ESP32 and RTC.

  • From Breadboard to Enclosure - Part 2

    Mike Teachman06/19/2019 at 14:13 0 comments

    Building the power conditioning module for the particulate sensor is the subject of this log.   The components in this module include all of the MOSFETS, transistors, diode, and the DC-DC boost converter.   An overview of the modules was described in From Breadboard to Enclosure - Part 1

    The components are shown below.  The full schematic is here:  schematic.

    A soldered protoboard will be used for construction.  For protoboard, I either use Adafruit Perma-Proto (left in photo below) or a generic stripboard (right in photo), cut to a custom size.

    The Adafruit product is high quality - the through holes are accurately drilled and plated.  The stripboad is somewhat lower quality - no though hole plating and inconsistent drilling which can lead to track lifting if there is any rework.  The photo below shows some of the off-center drill holes on the stripboard.

    Sloppy drilling in stripboard

    However, compared to a Perma-Proto board a stripboard module can be designed with a denser component layout, leading to a smaller module.  In the end, the need for a small module size led to the selection of stripboard.  

    Related stripboard idea:   There is high quality stripboard that is available, but it comes a significant price premium.  I think it might be possible to design a stripboard in KiCad and then have it built by a custom PCB manufacturer.  I am seeing low-cost PCB manufacturers offering 3 PCBs (10cm x 10cm) for USD $10 + shipping.   These PCBs would have plated through holes and solder resist between the holes, and hopefully accurate hole placement.  I might explore this avenue and document the results in a Hackaday project.

    The completed power conditioning module is shown below.  I am using polarized JST connectors for connection to the particulate sensor and cpu module.    

    The upcoming Part 3 will detail the construction of the stripboard that contains the Spec Sensor modules.

  • From Breadboard to Enclosure - part 1

    Mike Teachman06/02/2019 at 21:56 0 comments

      It's time to transform the Street Sense breadboard implementation into something more permanent.   Over the next month my ambition is to get all of the electronics and sensors into a weatherproof enclosure so I can start some field trials

      The selection of the enclosure wasn't difficult.  I'm going to house the electronics in the same enclosure used in the SensorUp Smart City Starter Kit.  I am a participant in the SensorUp Smart City pilot project and have a one of their beta sensor units mounted on my back porch, measuring PM2.5 particulates, since August 2018.  My measurement site is called "Fernwood" in the air quality map of Victoria.   This enclosure seems to work well.  My only issue was a spider that nested inside the enclosure.  The SensorUp enclosure is a commercially available unit, made by AcuRite.  

      The sensors and electronics will be located inside the enclosure cavity.  The dimensions of the cavity are:

      Bottom opening:  5cm x 9cm
      Depth:  12cm

      Packaging Goals:

      1. Protect electronics and sensors from wind and rain.  
      2. Allow airflow across sensors
      3. Removal of electronics as a single unit, to facilitate desktop development.  

      I would like to build some sort of carrier frame, to mount the electronics, that would fit inside the AcuRite enclosure cavity.  Here is a paper prototype sketch of the carrier frame for the electronics and sensors.

      3 circuit boards are planned, implemented with veroboard:

      1. Ozone + NO2 sensors, ADC, power conditioning for sensors
      2. Power conditioning for PM2.5 sensor 
      3. Processing board.  ESP32 + RTC 

      The Lipo battery needs to go somewhere as well.  Not sure where it will be located at this time.

      The frame will likely be constructed with acrylic, laser cut at Victoria Makerspace, where I am a member.  The 3 circuit boards will be attached to the frame with standoffs and bolts.  Then the whole assembly will slide into the cavity of the AcuRite enclosure.  Some sort of latched attachment mechanism needs to be conceived to securely hold the frame to the AcuRite enclosure - another TBD design topic.

  • Improving Ozone and NO2 Sensor Performance

    Mike Teachman05/14/2019 at 17:07 0 comments

      This project update outlines some incremental improvements to the ozone and NO2 sensor performance.

      A separate analog power supply was created on the breadboard to provide 3.3V to the ADC and Spec Sensor modules.  The idea is to isolate these sensitive analog components from the noisy 3.3V digital power supply.   The battery provides power to the input of an ultra-low dropout linear regulator which then feeds the ADC and Spec Sensor modules.   Luckily, the combined current consumption of the Spec Sensor modules and ADC are low enough that the Lolin D32 Pro battery charging circuit is not affected.  The analog power supply circuit can be found in the version 8 schematic.

      The method of reading the sample values from the ADC is another significant change.  Previously, the ADC was polled using I2C in single-shot mode to detect every new sample.  The polling with I2C was factor in creating unwanted noise into the Vgas outputs of the Spec Sensors.  This noise was appearing while the ADC was performing the conversion - not good.  Now, the ADC runs in a continuous conversion mode and the ~DRDY signal is used to run an ISR in the MicroPython code.  The ISR reads the sample value.  This is arrangement is better for two reasons:

      1. I2C polling during ADC conversion is eliminated = less noise is seen by the sensitive op-amp circuits in the Spec Sensor modules
      2. The MicroPython code is more efficient - no more polling is need to detect the end of ADC conversion

      The MicroPython code for this change is documented with this github commit.

      Here is what the breadboard prototype looks like now.  You'll spot the new voltage regulator which sits just below the two orange tantalum capacitors.

      Here are some ozone measurements that were published to Adafruit IO using the MQTT protocol, every 2 minutes.  The units are parts-per-billion (ppb).  The goal is to have a resolution of 10ppb. You can see that the readings still bounce around.  It is significantly better with the changes.  But, there is still work to be done to improve measurement stability.  

      These latest changes seem like the end-of-the-road for improvements to the breadboard prototype.  Breadboards have so many other limiting factors such as capacitance between metal connection strips and stray inductance.  Future improvements in sensor measurement performance will need to come from  other means, such as soldered connections and likely a custom PCB.

  • Publishing sensor data with MQTT

    Mike Teachman04/07/2019 at 18:47 0 comments

    The next iteration of the prototype involves taking advantage of the built-in WiFi feature of the ESP32 microcontroller to publish sensor to an internet database such as Adafruit IO or Thingspeak.  The MQTT protocol will be used.

    Publishing data to a cloud database with WiFi and MQTT protocol is something I've done in other projects.  But, there is an added technical challenge in this project - that is publishing data and simultaneously recording audio to SDCard without creating audio gaps.  If the MQTT task blocks for too long at any point, the DMA buffering used in by the audio recording task will "overrun" leading to gaps in the recorded WAV file.

    To overcome this risk I used a non-blocking asyncio version of MQTT written by Peter Hinch.   This version uses a non-blocking sockets implementation and will not block other asyncio co-routines from running (like the microphone recording task) when WiFi goes down or the MQTT broker is unreachable.   An additional pause/resume feature was added by Kevin Köck that allows WiFi to be turned off when the device is not actively publishing.   This turns off the WiFi radio which reduces the power consumed by the ESP32 - the end result is a longer battery life.  There is a discussion on the MicroPython forum describing how this enhancement was realized.  Sensor data will be published every 15 minutes in the final design.  

    A 2 hour test was run, publishing sensor data to Adafruit IO.  Below is a plot from Adafruit IO showing 2 hours of PM2.5 particulate data.  This shows a very clean air day on the west coast of Canada!  This publish period was reduced to 2 minutes for this test.  

    Some diagnostic information in the microphone task showed that there were two audio gaps in the 2-hour SD Card audio recording.   The was a unwelcome result.  More debugging code will be needed to determine the root cause of the audio interruption.  The audio sample rate in the test was 10kHz.     

  • Temperature and Humidity Sensor

    Mike Teachman03/25/2019 at 17:20 0 comments

    The next step in the project is rather unremarkable - adding a temperature and humidity sensor.  I chose the Si7021 sensor,  packaged in a convenient breakout board by Adafruit.  The sensor specification claims ±0.4 °C temperature accuracy.  Temperature measurements from the sensor will be recorded periodically to the SD card and will be used for temperature compensation of the ozone and NO2 sensor readings.

    I have used this breakout board in other MicroPython projects so I was expecting a simple integration with the Street Sense MicroPython code.  But, I once again stumbled on a breaking interface change in the Loboris ESP32 port.  The Si7021 driver that I use with the mainline of MicroPython does not work in the Loboris port - caused by a breaking change in the I2C interface API.

    Fortunately, I was able to source a different Si7021 MicroPython driver from Github for this sensor that works with the Loboris I2C implementation.

    The V07 schematic shows the addition of the sensor.

    The sensor is mounted in the breadboard to the left of the OLED display

  • New I2S Microphone

    Mike Teachman03/20/2019 at 15:52 1 comment

    It turns out that the Adafruit I2S MEMS Microphone breakout board does not work properly with ESP32 microcontrollers.  The Adafruit breakout board uses the SPH0645LM4H MEMS microphone.

    What's going on?    I have discovered a timing incompatibility between the ESP32 and the I2S microphone - the ESP32 samples data on the rising edge of the I2S clock, exactly the same time as the sample data is changing from the SPH0645LM4H microphone.   The unfortunate end result is that every 18-bit sample from the microphone is shifted one bit to the left - the MSB is lost and a '0' appears as the LSB.... not good.

    A couple of years ago this issue was discussed on an Adafruit forum...but no real answer came out of it.

    Let's take a deeper dive to see what is happening.

    The ESP32 Technical Reference Manual describes the expected timing between WS, BCK, and SD

    "WS and SD signals in the I2S module change on the falling edge of BCK, while the SD signal can be sampled on the rising edge of BCK"

    The key part is "sampled on the rising edge of BCK".  

    A timing diagram in the ESP32 Technical Reference Manual shows the expected timing for an I2S slave device.  Shown below:

    Philips Standard in ESP32 Technical Manual

    The SPH0645LM4H device implements the timing diagram shown below.  Notice that DATA (SD) transitions on the rising edge of CLK.  

    The SPH0645LM4H datasheet specificies a Max Tdc = 65.92ns, but surprisingly no Min value for Tdc.  

    This doesn't look like a good situation - data changing when it is being sampled is not a recommended design practice !  

    The captured sample data clearly shows a problem -- the data shows that the ESP32 uses the MSB of the Left channel as the LSB of the Right channel.  That line I just wrote is likely confusing!    Let's look at an example to get clarity.    

    The WAV file data shown below was captured using the ESP32 I2S interface.  The "0x01" value bytes that appear in two columns are the least significant bytes for the Right channel.  They should be 0x00 as the microphone is configured to only output sample data on the left channel (WS=low).  But they are 0x01 because the MSB of the Left channel is clocked in as the LSB of the Right channel by the ESP32.  A sharp eye will notice that every Left channel sample has the LSB equal to zero (e.g. always 0x80 and 0x00...never 0xC0 or 0x40) - that happens when the "19th" bit (which is pulled down to zero when the data bus goes tri-state) is sampled as the LSB "18th" bit.  Note that the data is in little endian format.

    I was able to use an oscilloscope to capture the I2S data bit stream that is associated with the above WAV file.  The scope capture below shows BCK, WS, and SD (top to bottom) of the 2nd non-zero audio sample.  The bit stream on the SD signal shows a sample value of 0xF9 0x41 0x00 0x00.  Now, compare to the 2nd Left channel sample in the WAV file above (in line starting with 0x70) which has a value = 0xF2 0x82 0x00 0x00 (converted from little endian) 

    if you take sample = 0xF9 0x41 0x00 0x00 (the "correct" value seen in the bit stream) and shift it L by one bit you get sample = 0xF2 0x82 0x00 0x00 (the "wrong" value sampled by the ESP32) which is seen in the WAV file data.

    This shows the compatibility problem between the ESP32 I2S interface and the SPH0645LM4H microphone.

    I was hoping for a workaround.  But, I could not find a means to adapt the timing of either the microphone or the ESP32 to make them compatible.  There is a (complex) firmware solution where the undesired bit shift can be undone.  I did not pursue that approach.  

    A simple solution...

    Read more »

  • New ADC

    Mike Teachman03/18/2019 at 16:17 0 comments

    A new Texas Instruments ADC was added to the design -- ADS1219

    The ADS1219 replaces the ADS1015 ADC.  This new ADC offers these benefits:

    • integrated input buffers -- allows measurement of high impedance inputs such as Vref coming from the Spec Sensor devices
    • separate inputs for analog and digital power/ground -- allows more options to mitigate power supply noise
    • better noise-free resolution than either of the ADS1015 or ADS1115 ADCs

    I wrote and published a MicroPython driver for the ADS1219 device.  The control of the device in MicroPython was quite simple.

    The V05 schematic includes the new ADC.   You will notice that the initial integration of this ADC is lacking most sensible approaches to minimize noise effects:

    • 3.3V digital rail supplies analog power for both the ADC and Spec Sensor gas sensors.
    • ADC soldered to a TSSOP-16 breakout board and then plugged into a breadboard

    This approach allowed me to write the MicroPython driver and get the device integrated into the rest of the MicroPython code.

    Given the lack of care to deal with power supply noise, it wasn't surprising to see poor results when reading the analog values from the ozone and NO2 sensors.  Results showed considerable variability in back-to-back measurements for gas concentration.   An oscilloscope capture shows that the Vgas outputs from the gas sensors oscillate during the time they are being sampled by the ADC. 

    • yellow = Vgas Ozone
    • aqua = Vgas NO2
    • purple = 3.3V rail

    You can see voltage fluctuations on the 3.3V rail that are associated with the oscillations. These oscillations happen each time the ADC performs a single-shot conversion.  

    Next steps:   Time to put on the analog design hat and investigate decoupling methods to provide low-noise analog power for the ADC and gas sensors.

  • Taming Noise From the Boost Converter

    Mike Teachman03/14/2019 at 23:07 0 comments

    The PM2.5 particulate sensor requires a 5V supply voltage.  Supplying this 5V requires special consideration when the unit is powered by a 3.7V Lipo battery.   Providing 5V of power with a 3.7V battery is accomplished using a type of switched-mode power supply called a boost converter.  The boost converter used in this design is built around the ME2108 IC.

    Switched-mode power supplies are notorious for injecting noise into circuits.  I investigated this concern.

    The purple trace in the scope capture below shows noise on the 3.3V rail -- measured as 132mV with a frequency of 34.7 kHz.  As a quick test, I removed the boost converter -- the 3.3V rail noise dropped dramatically - this shows that the boost converter is a significant source of noise.

    Many devices, including a noise-sensitive ADC is powered with the 3.3V rail.  My first results with the ADC are not encouraging - I see unstable results from the ozone and NO2 sensors.   I suspect that the switched-mode supply noise is contributing to the undesirable results.

    The first mitigation step was to replace the 1N4001 diode in the USB/Battery selection circuit with a Schottky diode.  A Schottky diode is recommended for this circuit.  I found two types of Schottky diodes at our local Makerspace and chose the diode that reduced the noise the most.

    Adding the Schottky diode produced measurable improvements - noise was approximately halved.  Shown in the scope capture below.

    Adding a 220uF electrolytic capacitor to the input of the boost converter produced more measurable noise improvements on the 3.3V rail.  Apparently electrolytic capacitors are not the first choice capacitors for the input of boost converters (low ESR ceramic capacitors are preferred).  However, the electrolytic capacitor reduced the noise on the 3.3V rail by an additional 50% , shown below.

    Lastly,  I added a high-side MOSFET switch to turn off the boost converter using a GPIO pin on the ESP32 microcontroller.  The particulate sensor only needs to be powered-up on demand to make a periodic measurement.  When the boost converter is switched off the noise on the 3.3V rail is reduced further.

    These improvements are reflected in the latest V4 schematic release, link below.

    Schematic Version 4

  • Ozone and NO2 sensors

    Mike Teachman02/13/2019 at 22:16 0 comments

    With the I2S microphone and particulate sensors working well, the next step is integrating the ozone and NO2 sensors.  These sensors are manufactured by Spec Sensor and are used in the Array of Things project in Chicago.  Spec Sensor published a report showing that the Spec Sensor units perform well in side-by-side tests against calibrated industrial-grade sensors.  The credibility of these sensors appears promising. 

    I chose the analog module versions for both the ozone and NO2 sensors.  The modules include all the difficult analog amplification and biasing circuitry.  I have little of that skillset - it was an easy decision to purchase units that include the analog sub-circuits.

    Each sensor has an analog output, 0-3.0V range, that is proportional to the measurement of gas concentration.  This analog output will be converted to digital using an analog-to-digital converter (ADC) device that will connect to the ESP32 using an I2C bus.  In my parts stock I have the ADS1015 ADC by Texas Instruments.  It has 12-bit resolution and can operate with a 3.3V supply.  I like using ADCs having an I2C communication interface as it allows the ADC to be located in immediate proximity to the sensors  This allows short analog signals runs, thereby reducing coupled noise.  The ESP32 has some built-in ADCs, but reports are not flattering on the performance.  I might use these ESP32 ADCs for non-critical operations like reading battery voltage.

    Each sensor module has 3 outputs that can be measured.  Vgas, Vref, and Vtemp.  Vgas is the important one - the analog reading which represents the gas concentration.  It wasn't too clear on how the other two outputs are used.  I contacted the company and got a prompt response.  Spec Sensor indicated that good results can be achieved using only the Vgas output.  The other two outputs are high impedance outputs which are somewhat difficult to use with ADCs.  

    I expanded the breadboard prototype to include the two gas sensors and the ADC.  The gas sensors and ADC are shown in the left side of the photo below.  The V03 schematic is up-to-date with these new devices.

    The ADS1015 device is quite popular and there is a MicroPython driver available.  Unfortunately, the driver needed some small modifications as the I2C implementation on the Loboris MicroPython port introduces breaking changes compared to the mainline of MicroPython.  It's frustrating when a fork of a project does not maintain backwards compatibility with key interfaces like I2C.  

    Two new co-routines were added to the Street Sense MicroPython code to manage the two sensors.  The raw sensor values are displayed on the OLED display and are logged to the SD Card.

    What about results?   I observed that the gas values are not as stable as I expected.  I modified the driver configuration to select a slower sampling rate and the values become more stable.  But, still not what I need for the final unit.

    From my long 25 year career in measurement at Schneider Electric Victoria I knew that this stage of the project would be toughest to crack.  This is just the first step in what will be an iterative design.  I fully expect to try out a few ADCs, add filter capacitors, and who knows what else -- to get a stable and accurate digital representation that fully exploits the accuracy of these gas sensors.  Perhaps I'll need to seek some help from my ex-colleagues who are unbelievable world-class experts in analog design?

    One area that needs work is ADC resolution.  The ADS1015 devices have 12 bits of resolution.  That is good enough...

    Read more »

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