IOT based Complete Home Automation System

import pandas as pd
import time
import json

while True:
	try:
		dfs=pd.read_html('http://oasis.caiso.com/oasisapi/prc_hub_lmp/PRC_HUB_LMP.html')     #reading the website for getting the electricity cost
		dfs1=dfs[1] #Shortlisting the actual value form other data
		val=dfs1.values.tolist()
		val0=val[0]
		val01=val0[1] #final value 
		electricity_cost=float(val01.replace('$','').replace(' ','')) #converting into redable format
		t = time.localtime() #getting current time
		current_date = time.strftime("%d:%b:%Y",t)
		current_time = time.strftime("%H:%M:%S",t)
		print(current_time, "==> ",electricity_cost,"$/MWh")

		dic = {                     #saving the values as a dictionary
		'cost' : electricity_cost,
		'cost_date':current_date,
		'cost_time':current_time,
		}
		with open('cost.txt', 'w') as outfile: # dumping the file in the already created text file in a JSON format
			json.dump(dic, outfile)
		
		time.sleep(60)
	except:          #in case some error in above script just wait for 60 seconds and the run the above script again
		time.sleep(60)	

import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from datetime import datetime
import json

Temperature = []
Light_intensity = []
Sensed_time = []
Cost = []
def figure(i): # defining the figure

	with open ('cost.txt') as f:  #getting the values from text files
		cost_data = json.load(f)
	with open ('bolt_data.txt') as f:
		sensor_data = json.load(f)
	date_time = datetime.strptime(sensor_data['sensed_date_time'], '%d:%b:%Y::%H:%M:%S') #converting the date time from text file to machine redable format
	Cost.append(float(cost_data['cost'])) #creating list for plotting
	Temperature.append(float(sensor_data['temperature']))
	Light_intensity.append(float(sensor_data['light']))
	Sensed_time.append(date_time)
	print(sensor_data['temperature'])
	print(sensor_data['light'])
	print(cost_data['cost'])
	plt.cla() # clearing the plot
	plt.plot(Sensed_time,Temperature) # plotting the graphs
	plt.plot(Sensed_time,Light_intensity)
	plt.plot(Sensed_time,Cost)
ani = FuncAnimation(plt.gcf(), figure, interval=30000) #running the function after every 30 seconds

plt.show() #display the graph

from boltiot import Bolt
import time 
import json
import matplotlib.pyplot as plt
from drawnow import drawnow
from datetime import datetime


API_KEY="xxxxxxxxxxxxxxxxx"
DEVICE_ID="xxxxxxxxx"

mybolt = Bolt(API_KEY,DEVICE_ID) #Create bolt object

cost_margin = 38 
pump_wattage = 3000 #3KW load
EV_wattage = 10000  #10KW load
					#Indoor lighting system 250W maximum
port0 = 0
port1 = 1
total_cost = 0



plt.ion()  # enable interactivity
fig = plt.figure()  # make a figure


def make_fig():         #update fifure values to the graph
    plt.plot(time_axis, Tot_cost)  

Tot_cost = list()
time_axis = list()

while True:
	try:
		with open ('cost.txt') as f:  #getting cost data from text file
			cost_data = json.load(f)
		with open ('bolt_data.txt') as f:  #getting light, temperature, PWM(u) and date-time data from text file
			sensor_data = json.load(f)
		cost = float(cost_data['cost'])
		lighting = float(sensor_data['u'])


		if cost < cost_margin:   #checking if current electricity cost is less than marginal cost
			bat_status = 1
		else:
			bat_status = 0

		response = mybolt.digitalRead(port1) #Reading the sensor value to check if battery is chargable or not
		response = json.loads(response)
		battery_status = int(response['value'])
		print(battery_status)
		if battery_status==0:
			bat_status=0

		if bat_status==1: #battery charging along with motor turns on if sensor value = 1 and cost < cost marginal 
			print("Batery and Motor ON")
			response = mybolt.analogWrite(port0, '255')
		if bat_status==0:
			print("Batery and Motor OFF")
			response = mybolt.analogWrite(port0, '0')	

		print(response)

		cost = (cost/(1000000*60*60))	#convert to $/Wsec
		print(cost)

		total_cost = cost*30*(((pump_wattage+EV_wattage)*bat_status)+lighting) + total_cost       #Calculating the total energy consumed up till current iteration
		print(round(total_cost,5), "$")
		
		date_time = datetime.strptime(sensor_data['sensed_date_time'], '%d:%b:%Y::%H:%M:%S') #converting the date time taken from text file(JSON format) into computer understandable date time
		print(date_time)
		dic = {                           #saving values in a dictionary
				'energy_cost' : total_cost,
				'sensed_time': str(date_time),
				}
		with open('energy_cost.txt', 'w') as outfile:  #opening the pre made text file and dumping the values in it
			json.dump(dic, outfile)

		Tot_cost.append(total_cost) #appending the values in a list
		time_axis.append(date_time) 
		drawnow(make_fig) #making the real time graph

		plt.pause(30) #pausing the graph display for 30 seconds
	except:
		time.sleep(30)

import email_conf
from boltiot import Email, Bolt
from boltiot import Sms, Bolt
import json, time, math, statistics

mybolt = Bolt(email_conf.API_KEY, email_conf.DEVICE_ID)
mailer = Email(email_conf.MAILGUN_API_KEY, email_conf.SANDBOX_URL, email_conf.SENDER_EMAIL, email_conf.RECIPIENT_EMAIL)
sms = Sms(email_conf.SID, email_conf.AUTH_TOKEN, email_conf.TO_NUMBER, email_conf.FROM_NUMBER)

history_data=[]
conf=email_conf
def compute_bounds(history_data,frame_size,factor): #calculating Z-score using equations and setting high and low 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]

while True:
    with open ('cost.txt') as f: #OPENING THE TEXT FILES AND READING THE DATA
        cost_data = json.load(f)
    with open ('bolt_data.txt') as f:
        sensor_data = json.load(f)
    with open ('energy_cost.txt') as f:
        energy_cost = json.load(f)    
    print ("Total cost is: " + str(energy_cost['energy_cost']))
    print ("Time of cost calculation: " + str(energy_cost['sensed_time']))
    
    bound = compute_bounds(history_data,conf.FRAME_SIZE,conf.MUL_FACTOR) #computing z-score
    if not bound: #if not enough data
        required_data_count = conf.FRAME_SIZE-len(history_data)
        print("Not enough data to compute z-score. Need",required_data_count,"more data ponts")
        history_data.append(float(energy_cost['energy_cost']))
        time.sleep(30)
        continue
    sensor_value = float(energy_cost['energy_cost'])
    try:
        if sensor_value > bound[0]: # enough data is present and the energy consumption increases suddenly
            print ("The energy consumption increased suddenly. Sending a mail")
            response = mailer.send_email("Alert","Sudden increase in energy consumption please monitor")  #sending a mail
            print("This is the response",response)

            print("Making request to Twilio to send a SMS")
            response = sms.send_sms("Sudden increase in energy consumption please monitor. ")  # sending an sms
            print("Response received from Twilio is: " + str(response))
            print("Status of SMS at Twilio is :" + str(response.status))


        if float(cost_data['cost']) > 50:  # if cost of electricity is more than 50$/MWh ten again send an alert
            print ("The energy cost is very high. Sending a mail")
            response = mailer.send_email("Alert","Cost is very high reduce consumption immediately")
            print("This is the response",response)

            print("Making request to Twilio to send a SMS")
            response = sms.send_sms("Cost is very high reduce consumption immediately ")
            print("Response received from Twilio is: " + str(response))
            print("Status of SMS at Twilio is :" + str(response.status))

        history_data.append(sensor_value)
    except Exception as e:
        print("Error",e)-
    time.sleep(30)

MAILGUN_API_KEY="XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX" 
SANDBOX_URL="XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
SENDER_EMAIL="XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
RECIPIENT_EMAIL="himanshugoyel05@gmail.com"
API_KEY="XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
DEVICE_ID="XXXXXXXXXXXXX"
FRAME_SIZE = 10  #number of readings to calculate z score
MUL_FACTOR = 3   #multiplication factor


SID = "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
AUTH_TOKEN = "XXXXXXXXXXXXXXXXXXXXXX"
FROM_NUMBER = "XXXXXXXXXXXXX"
TO_NUMBER = "+919653203388"