Automated light intensity

Electricity is the need for future. This project will help to minimize the use of electricity in the operation of a led light.

IntermediateFull instructions provided2 hours185

Things used in this project

Hardware components

Bolt IoT Bolt WiFi Module

LDR, 5 Mohm

LED (generic)

Resistor 1k ohm

Software apps and online services

Bolt IoT Android App

Twilio SMS Messaging API

Story

1.INTRODUCTION:

This project is to alter the intensity of the LED automatically according to the surronding light intensity by the LDR sensor. This is done with the python code. The readings of the LDR are mapped to the range of the intensity of the LED and the variable output is generated using Pulse Width Modulation (PWM).If this system is used to monitor the light intensity of a photosensitive environment, such as a certain medicine storage, then a sudden change in light intensity can be harmful. This sudden change is detected using Z-score analysis and an alert system has created in Twilio to send a SMS alert.

2.AUTOMATED CONTROLLINGOF LED :

In this section we study the 'AUTO' functionality of the project i.e. automated change of the intensity of the LED based on the brightness of the surroundings. The brightness of the surroundings is measured using LDR.

2.1Circuit Connections for LED and LDR

Given below are the circuit connections of LED and LDR with the bolt module for automated LED intensity based on the brightness of the surroundings.

The input from the LDR is taken at analog pin A0 and the output to the LED is written at digital pin 0. LDR terminals don't have polarity. The power supply to the LDR is given using 3.3V pin of the bolt module. The resistance across LDR changes with change in light intensity falling on it. Since the Bolt Module cannot read resistance values, but it can read voltage values, hence a voltage divider circuit is made and the input to the Bolt module is the voltage across 10k resistance (since it is connected between an LDR terminal and ground) which depends on the resistance across LDR. The longer terminal of the LED is connected to the higher potential and the shorter terminal to the lower potential. Here the shorter terminal is connected to ground and the longer terminal is connected to the digital pin 0 through a series 330k resistor. The digital pin 0 output (dependent on LDR/A0 pin input) acts as the power supply for the LED and hence determines. its intensity.

2.2Connectingbolttocloud:

First we have to connect the bolt to the cloud.After connecting to clocd the device will be online.

The above picture will ensure that the device is online.

Then go to API section to know about the API value which is used for sending sms alert.

2.3Mapping of LDR values to LED values

The range of values of the LDR are from 0 to 1024 and that of the LED is from 0 to 255. As evident, one to one mapping is not possible but an approximate 4:1 mapping can be done. It is done as follows:input_to_LED = 255 - (output_from_LDR / 4)The output from LDR is subtracted from 255 (maximum intensity of LED) because the mapping must be done inversely i.e. more brightness in the surroundings must correspond to less brightness of the LED.

2.4Detection of Sudden Change in Light Intensity (Z-Score Analysis)

Z-score analysis is used for anomaly detection. Anomaly here means a variable's value (light intensity of the surroundings) going beyond a certain range of values. The range of values is called bounds (upper bound and lower bound). These bounds are calculated using the input values, frame size and multiplication factor. The frame size is the minimum number of input values needed for Z-score analysis and the multiplication factor determines the closeness of the bounds to the input values curve.

Given above is the formula to calculate the bounds. Here the input is represented as 'Vi', 'r' denotes the frame size and 'C' is the multiplication factor. Firstly we calculate the mean (Mn) of the input values (for every new input, the mean is calculated again). The variation of each input value (from the mean) is given as (Vi - Mn)^2. The Z-score (Zn) is calculated as shown above ( square root of the mean of the variation of each input value multiplied by the multiplication factor). The bounds are represented as 'Tn' and the upper bound is calculated as (Vi + Zn) and the lower bound is calculated as (Vi - Zn).

The frame size and multiplication factor are determined using trial-and-error method.

2.5Creating Twilioaccount:

Go to the twilio website and create a account using the mail id which you have used to create the cloud.

After creating a trial version in twilio make sure that you have given necessary details asked and enter the mobile number which you like receive the alert sms.

The above page will appear after completing all the above mentioned steps.

Note down the SID number and AUTH TOKEN for writing in the python code.

AlertSMSFromTwilio:

Code

Automated light

mport requests, json, time, math, statistics //import various python libraries
from boltiot import Bolt
//import the boltiot module from the Bolt python library
import conf                  //import the configuration file
  
//---------FUNCTION TO COMPUTE BOUNDS OR Z SCORE ANALYSIS------------//
def compute_bounds(history_data, frame_size, factor): 
//Function to compute bounds
    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]    //Returns Low Bound and High Bound
  
//---------------FUNCTION FOR SMS ALERTS----------------------//
    sms = Sms(conf.SSID,conf.AUTH_TOKEN,conf.TO_NUMBER,conf.FROM_NUMBER)
//-----------------------------------------------------------------//
  
mybolt = Bolt(conf.API_KEY, conf.DEVICE_ID)    //To identify your bolt device
history_data = []                //Array of input values from LDR
  
while True:
  
//---------------------READ INPUT FROM LDR--------------------------//
    response_ldr = mybolt.analogRead('A0')     //Read input from LDR at A0 pin
    ldr_data = json.loads(response_ldr)//Retrieve the input data in json format
    if ldr_data['success']!='1':
        print("There was an error while retrieving the data")
        print(ldr_data['value'])
        time.sleep(10)
        continue
    try:
        sensor_value = int(data_ldr['value'])
        //store current input value in variable 
    except e:
        print("There was an error while parsing the response")
        print(e)
        continue
    print("LDR sensor value is: "+str(sensor_value)) //Print LDR input value
    print(response_ldr)
  
//----------------------MONITORING INTENSITY OF LED--------------------------//     
    led_value_1 = int(sensor_value/4)
    if led_value-1 > 255:
        led_value_1 = 255
    led_value = 255 - led_value_1//Output value to LED based on LDR input value
    response_led = mybolt.analogWrite('0', led_value) //Write output at pin 0
    print("Automated LED value is: "+str(led_value)) //Print LED output value
    print(response_led)
  
//----------------PERFORMING Z SCORE ANALYSIS--------------------------//
    bound = compute_bounds(history_data, conf.FRAME_SIZE, conf.MUL_FACTOR)
    //Call compute_bounds function
  
//-------------COLLECTING SUFFICIENT DATA FOR Z SCORE ANALYSIS---------//
    if not bound:
    //If number of inputs are not sufficient to do Z score analysis
        required_data_count = conf.FRAME_SIZE - len(history_data) -1
        if (required_data_count != 0 and required_data_count != 1):
            print("Not enough data to compute Z score. Need",required_data_count,"more data points.")
        elif (required_data_count == 1):
            print("Not enough data to compute Z score. Need 1 more data point.")
        else:
            print("Enough data to compute Z score.")
        history_data.append(int(ldr_data['value']))
        //Append each new input to array history_data[]
        time.sleep(10)    //Wait for 10 seconds
        continue
  
//-----------DETECTING ANOMALY AND SENDING ALERTS--------------//
    try:
        if sensor_value > bound[0]: //If input crosses upper bound
            print("The light level has increased suddenly.Sending a SMS")
            response = sms.send_sms("Someone turned on the light")
            print("This is the response",response)
        elif sensor_value < bound[1]: //If input crosses lower bound
            print("The light level has decreased suddenly.Sending a SMS")
            response = sms.send_sms("Someone turned off the light")
            print("This is the response",response)        
            history_data.append(sensor_value) 
        //Append each new input to array history_data[]
    except exception as e:
        print("Error")
        print(e)
    
    time.sleep(10)    //Wait for 10 seconds