Rahul
Published

Anomaly Detection with Light Intensity Monitoring Sensor

Anomaly detection using Z-score analysis with a light intensity monitoring sensor which sends alert messages on reaching threshold values.

IntermediateFull instructions provided5 hours759
Anomaly Detection with Light Intensity Monitoring Sensor

Things used in this project

Hardware components

Bolt WiFi Module
Bolt IoT Bolt WiFi Module
×1
USB-A to Micro-USB Cable
USB-A to Micro-USB Cable
×1
LDR, 5 Mohm
LDR, 5 Mohm
×1
Resistor 10k ohm
Resistor 10k ohm
×1

Software apps and online services

Bolt Cloud
Bolt IoT Bolt Cloud
digitalocean droplet
VmWare workstation
virtual box
SMS Messaging API
Twilio SMS Messaging API

Story

Read more

Code

Anomaly_detection

Python
import conf, json, time, math, statistics
from boltiot import Sms, Bolt
def compute_bounds(history_data,frame_size,factor):
    if len(history_data)<frame_size :
        return None

    if len(history_data)>frame_size :
        del history_data[0:len(history_data)-frame_size]
    Mn=statistics.mean(history_data)
    Variance=0
    for data in history_data :
        Variance += math.pow((data-Mn),2)
    Zn = factor * math.sqrt(Variance / frame_size)
    High_bound = history_data[frame_size-1]+Zn
    Low_bound = history_data[frame_size-1]-Zn
    return [High_bound,Low_bound]

mybolt = Bolt(conf.API_KEY, conf.DEVICE_ID)
sms = Sms(conf.SSID, conf.AUTH_TOKEN, conf.TO_NUMBER, conf.FROM_NUMBER)
history_data=[]

while True:
    response = mybolt.analogRead('A0')
    data = json.loads(response)
    if data['success'] != 1:
        print("There was an error while retriving the data.")
        print("This is the error:"+data['value'])
        time.sleep(10)
        continue

    print ("This is the value "+data['value'])
    sensor_value=0
    try:
        sensor_value = int(data['value'])
    except e:
        print("There was an error while parsing the response: ",e)
        continue

    bound = compute_bounds(history_data,conf.FRAME_SIZE,conf.MUL_FACTOR)
    if not bound:
        required_data_count=conf.FRAME_SIZE-len(history_data)
        print("Not enough data to compute Z-score. Need ",required_data_count," more data points")
        history_data.append(int(data['value']))
        time.sleep(10)
        continue

    try:
        if sensor_value > bound[0] :
            print ("The light level increased suddenly. Sending an SMS.")
            response = sms.send_sms("Decrese the brightness of the lights")
            print("This is the response ",response)
        elif sensor_value < bound[1]:
            print ("The light level decreased suddenly. Sending an SMS.")
            response = sms.send_sms("Increse the brightness off the lights")
            print("This is the response ",response)
        history_data.append(sensor_value);
    except Exception as e:
        print ("Error",e)
    time.sleep(10)

twillo_messenger

Python
SSID = 'You can find SSID in your Twilio Dashboard' 
AUTH_TOKEN = 'You can find  on your Twilio Dashboard' 
FROM_NUMBER = 'This is the no. generated by Twilio. You can find this on your Twilio Dashboard'
TO_NUMBER = 'This is your number. Make sure you are adding +91 in beginning'
API_KEY = 'This is your Bolt Cloud account API key'
DEVICE_ID = 'This is the ID of your Bolt device'
FRAME_SIZE = 10
MUL_FACTOR = 6

Prediction

JavaScript
setChartLibrary('google-chart');
setChartTitle('Polynomial Regression');
setChartType('predictionGraph');
setAxisName('time_stamp','temp');
mul(0.0977);
plotChart('time_stamp','temp');

Credits

Rahul
1 project • 0 followers

Comments