---
tags: mininet-wifi-tutorials
---

# Machine Learning

:::info
**In this short demo you will:**
- Learn on how to use whereami to make some predictions

**Requirements**
- Mininet-WiFi - https://github.com/intrig-unicamp/mininet-wifi
- Whereami - https://github.com/ramonfontes/whereami
:::

Firstly you have to take the code below:

#!/usr/bin/python

'''@author: Ramon Fontes
   @email: [e-mail]'''

import sys

from mininet.log import setLogLevel, info
from mn_wifi.link import wmediumd
from mn_wifi.cli import CLI
from mn_wifi.net import Mininet_wifi
from mn_wifi.wmediumdConnector import interference


def topology(args):
    "Create a network."
    net = Mininet_wifi(link=wmediumd, wmediumd_mode=interference,
                       noise_th=-91, fading_cof=1)

    info("*** Creating nodes\n")
    ap1 = net.addAccessPoint('ap1', ssid='new-ssid', mode='a', channel='36',
                             position='125,30,0')
    ap2 = net.addAccessPoint('ap2', ssid='new-ssid', mode='a', channel='36',
                             position='50,30,0')
    ap3 = net.addAccessPoint('ap3', ssid='new-ssid', mode='a', channel='36',
                             position='50,90,0')
    ap4 = net.addAccessPoint('ap4', ssid='new-ssid', mode='a', channel='36',
                             position='125,90,0')
    net.addStation('sta1', ip='10.0.0.1/8', position='10,20,0')

    info("*** Configuring Propagation Model\n")
    net.setPropagationModel(model="logDistance", exp=4)

    info("*** Configuring wifi nodes\n")
    net.configureWifiNodes()

    net.plotGraph(max_x=200, max_y=200)

    info("*** Starting network\n")
    net.build()
    ap1.start([])
    ap2.start([])
    ap3.start([])
    ap4.start([])

    info("*** Running CLI\n")
    CLI(net)

    info("*** Stopping network\n")
    net.stop()


if __name__ == '__main__':
    setLogLevel('info')
    topology()

Considering that the filename is `predict.py` you run it as below:

sudo python predict.py

Then you open xterm and run whereami from sta1's terminal.

mininet-wifi> xterm sta1
whereami learn -l ap2 --device sta1-wlan0

Change the position to ap1 and run whereami again.

mininet-wifi> py sta1.setPosition('150,25,0')
whereami learn -l ap1 --device sta1-wlan0

Change the position to ap4 and run whereami.

mininet-wifi> py sta1.setPosition('125,125,0')
whereami learn -l ap4 --device sta1-wlan0

Change the position to ap3 and run whereami one more time.

mininet-wifi> py sta1.setPosition('50,125,0')
whereami learn -l ap3 --device sta1-wlan0

At this time you are able to see some txt files at ~/.whereami as well the pkl model.

~/.whereami/*.txt
~/.whereami/model.pkl

Lastly, you can change the position of sta1 and make the prediction with whereami as below:

whereami predict --device sta1-wlan0

:::info

Demo :mega:: https://www.youtube.com/watch?v=8hijoFLS_PU
:::