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https://github.com/schollz/howmanypeoplearearound

Count the number of people around you :family_man_man_boy: by monitoring wifi signals :satellite:
https://github.com/schollz/howmanypeoplearearound

location sensor tshark wifi

Last synced: 3 days ago
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Count the number of people around you :family_man_man_boy: by monitoring wifi signals :satellite:

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# howmanypeoplearearound 



Count the number of people around you :family_man_man_boy: by monitoring wifi signals :satellite:.



*howmanypeoplearearound* calculates the number of people in the vicinity

using the approximate number of smartphones as a proxy (since [~70% of people have smartphones nowadays](https://twitter.com/conradhackett/status/701798230619590656)). 

A cellphone is determined to be in proximity to the computer based on sniffing WiFi probe 

requests. Possible uses of *howmanypeoplearearound* include: monitoring foot traffic in your house

with Raspberry Pis, seeing if your roommates are home, etc.



Tested on Linux (Raspbian and Ubuntu) and Mac OS X.



### **It may be illegal** to monitor networks for MAC addresses, especially on networks that *you do not own*. Please check your country's laws (for US [Section 18 U.S. Code § 2511](https://www.law.cornell.edu/uscode/text/18/2511)) - [discussion](https://github.com/schollz/howmanypeoplearearound/issues/4).



Getting started

===============



For a video walkthrough on how to install, checkout [PNPtutorials](https://youtu.be/dLzouUfJyMM?t=3m2s).



## Dependencies



Python 2.7 or preferably Python 3 must be installed on your machine with the `pip` command also available.

```

  python -V

  pip -V

```



### WiFi adapter that supports monitor mode



There are a number of possible USB WiFi adapters that support monitor mode. Here's a list that are popular:



- [USB Rt3070 $14](https://www.amazon.com/gp/product/B00NAXX40C/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B00NAXX40C&linkId=b72d3a481799c15e483ea93c551742f4)

- [Panda PAU5 $14](https://www.amazon.com/gp/product/B00EQT0YK2/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B00EQT0YK2&linkId=e5b954672d93f1e9ce9c9981331515c4)

- [Panda PAU6 $15](https://www.amazon.com/gp/product/B00JDVRCI0/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B00JDVRCI0&linkId=e73e93e020941cada0e64b92186a2546)

- [Panda PAU9 $36](https://www.amazon.com/gp/product/B01LY35HGO/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B01LY35HGO&linkId=e63f3beda9855abd59009d6173234918)

- [Alfa AWUSO36NH $33](https://www.amazon.com/gp/product/B0035APGP6/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B0035APGP6&linkId=b4e25ba82357ca6f1a33cb23941befb3)

- [Alfa AWUS036NHA $40](https://www.amazon.com/gp/product/B004Y6MIXS/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B004Y6MIXS&linkId=0277ca161967134a7f75dd7b3443bded)

- [Alfa AWUS036NEH $40](https://www.amazon.com/gp/product/B0035OCVO6/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B0035OCVO6&linkId=bd45697540120291a2f6e169dcf81b96)

- [Sabrent NT-WGHU $15 (b/g) only](https://www.amazon.com/gp/product/B003EVO9U4/ref=as_li_tl?ie=UTF8&tag=scholl-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=B003EVO9U4&linkId=06d4784d38b6bcef5957f3f6e74af8c8)



Namely you want to find a USB adapter with one of the following chipsets: Atheros AR9271, Ralink RT3070, Ralink RT3572, or Ralink RT5572.



### Mac OS X

```

  brew install wireshark

  brew cask install wireshark-chmodbpf

```



You need to dissociate from any AP before initiating the scanning:

```

sudo /System/Library/PrivateFrameworks/Apple80211.framework/Versions/Current/Resources/airport -z

```



### Linux [tshark](https://www.wireshark.org/docs/man-pages/tshark.html) 

```

sudo apt-get install tshark

```



Then update it so it can be run as non-root:

```

sudo dpkg-reconfigure wireshark-common     (select YES)

sudo usermod -a -G wireshark ${USER:-root}

newgrp wireshark

```



## Install

```

pip install howmanypeoplearearound

```



## Run



### Quickstart



To run, simply type in

```bash

$ howmanypeoplearearound

Using wlan1 adapter and scanning for 60 seconds...

[==================================================] 100%        0s left

There are about 3 people around.

```



You will be prompted for the WiFi adapter to use for scanning. Make sure to use

an adapter that supports "monitor" mode.



### Docker alternative



If Docker is installed locally and you want to take *howmanypeoplearearound* out for a quick spin, you can try the following:

1. Copy Dockerfile from this repo in your current working directory

2. `docker build -t howmanypeoplearearound .`  # that . at the end is important

3. `docker run -it --net=host --name howmanypeoplearearound howmanypeoplearearound`



NOTE: This Docker alternative is known to work on Ubuntu but *not* on Mac OS X.  Feedback on other platforms would be appreciated.



### Options



You can modify the scan time, designate the adapter, or modify the output using some command-line options.

```bash

$ howmanypeoplearearound --help



Options:

  -a, --adapter TEXT   adapter to use

  -z, --analyze TEXT   analyze file

  -s, --scantime TEXT  time in seconds to scan

  -o, --out TEXT       output cellphone data to file

  -v, --verbose        verbose mode

  --number             just print the number

  -j, --jsonprint      print JSON of cellphone data

  -n, --nearby         only quantify signals that are nearby (rssi > -70)

  --nocorrection       do not apply correction

  --loop               loop forever

  --sort               sort cellphone data by distance (rssi)

```



### Print JSON



You can generate an JSON-formatted output to see what kind of phones are around:

```bash

$ howmanypeoplearearound -o test.json -a wlan1

[==================================================] 100%         0s left

There are about 4 people around.

$ cat test.json | python3 -m json.tool

[

  {

    "rssi": -86.0,

    "mac": "90:e7:c4:xx:xx:xx",

    "company": "HTC Corporation"

  },

  {

    "rssi": -84.0,

    "mac": "80:e6:50:xx:xx:xx",

    "company": "Apple, Inc."

  },

  {

    "rssi": -49.0,

    "mac": "ac:37:43:xx:xx:xx",

    "company": "HTC Corporation"

  }

]

```



A higher rssi means closer (one of these phones is mine, and the other two are my roommates' who were upstairs). 



### Run forever



You can add `--loop` to make this run forever and append new lines an output file, `test.json`:

```bash

$ howmanypeoplearearound -o test.json -a wlan1 --loop

```



### Visualize 



You can visualize the output from a looped command via a browser using:

```bash

$ howmanypeoplearearound --analyze test.json 

Wrote index.html

Open browser to http://localhost:8001

Type Ctl+C to exit

```



Then just open up `index.html` in a browser and you should see plots. The first plot shows the number of people over time. Here you can see that people start arriving at work place around 8-9am (when work starts!).



![newplot](https://cloud.githubusercontent.com/assets/6550035/26174159/b478b764-3b0b-11e7-9600-2aa215b789d0.png)



The second plot shows the RSSI values for the mac addresses seen. You can double-click on one of them in particular to highlight that trajectory, as I have done here for my phone (you can see when I leave from and when I arrive to work!):



![newplot 1](https://cloud.githubusercontent.com/assets/6550035/26174160/b4911ae8-3b0b-11e7-93b2-92c3efaa01aa.png)



How does it work?

==================



*howmanypeoplearearound* counts up the number of probe requests coming from cellphones in a given amount of time.

The probe requests can be "sniffed" from a monitor-mode enabled WiFi adapter using `tshark`. An accurate count does 

depend on everyone having cellphone and also scanning long enough (1 - 10 minutes) to capture the packet when 

a phone pings the WiFi network (which happens every 1 to 10 minutes unless the phone is off or WiFi is disabled).



This is a simplification of another program I wrote, [find-lf](https://github.com/schollz/find-lf) which uses a similar idea with a cluster of Raspberry Pis to geolocate positions of cellphones within the vicinity.



License

=======



MIT