sankarcheppali

// Load Grove module
var groveSensor = require('jsupm_grove');
var FormData = require('form-data');
var fs = require('fs');
// we want mraa to be at least version 0.6.1
var mraa = require('mraa');
var version = mraa.getVersion();

var tSampFileName='t_samp.csv';

sankarcheppali

04-24 22:12:03.830 18041-18139/com.xxx.xxx.smarthook E/AndroidRuntime: FATAL EXCEPTION: MQTT Con: 02:00:00:00:00:00
                                                                       Process: com.xxx.xx.smarthook, PID: 18041
                                                                       java.lang.NullPointerException: cancel() called with a null PendingIntent
                                                                           at android.app.AlarmManager.cancel(AlarmManager.java:890)
                                                                           at org.eclipse.paho.android.service.AlarmPingSender.stop(AlarmPingSender.java:86)
                                                                           at org.eclipse.paho.client.mqttv3.internal.ClientComms.shutdownConnection(ClientComms.java:327)
                                                                           at org.eclipse.paho.client.mqttv3.internal.ClientComms$ConnectBG.run(ClientComms.java:608)
                       

sankarcheppali

#include<reg51.h>
void delay_us(unsigned int us_count)
 {  
    while((us_count*4)!=0)
      {
         us_count--;
       }
   }

sankarcheppali

sudo apt-get update 
sudo apt-get upgrade 
sudo apt-get install build-essential 
sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev 
sudo apt-get install python-dev python-numpy libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev 
sudo apt-get install python-opencv 
sudo apt-get install opencv
sudo apt-get install python-matplotlib

sankarcheppali

import io
import picamera
import cv2
import numpy

#Create a memory stream so photos doesn't need to be saved in a file
stream = io.BytesIO()

#Get the picture (low resolution, so it should be quite fast)
#Here you can also specify other parameters (e.g.:rotate the image)

sankarcheppali

#Load a cascade file for detecting faces
face_cascade = cv2.CascadeClassifier('/home/pi/Desktop/opencv/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('/home/pi/Desktop/opencv/haarcascade_eye.xml')

#Convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

#Look for faces in the image using the loaded cascade file
faces = face_cascade.detectMultiScale(gray, 1.3, 5)

sankarcheppali

import io
import numpy
import cv2
face_cascade = cv2.CascadeClassifier('/home/pi/Desktop/opencv/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('/home/pi/Desktop/opencv/haarcascade_eye.xml')
img = cv2.imread('sachin.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
    cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)

sankarcheppali

serOut=2 --SER pin
clk=1 --shift register clock (SRCLK)
latch=3 -- Storage register clock (RCLK)
loadStatus=0 --use only 16 bits

gpio.mode(clk,gpio.OUTPUT)
gpio.mode(serOut,gpio.OUTPUT)
gpio.mode(latch,gpio.OUTPUT)

local function sendClk()

sankarcheppali

local function consume_data( payload )
    --we will parse the payload and excute it,publish the return value
     print(payload)
     msg=cjson.decode(payload)
     loadNumber=msg.ln
     targetStatus=msg.ts
    if(targetStatus==0) then  loadStatus=bit.clear(loadStatus,loadNumber)                 
    else loadStatus = bit.set(loadStatus,loadNumber)  end   
    serialOut(loadStatus)
    print ("Status of the loads : ")

sankarcheppali

package example.siva.com.hellokotlin

import android.support.v7.app.AppCompatActivity
import android.os.Bundle
import kotlinx.android.synthetic.main.activity_main.*
import org.jetbrains.anko.toast

class MainActivity : AppCompatActivity() {

    override fun onCreate(savedInstanceState: Bundle?) {