App note: Implementation of a single-phase electronic watt-hour meter using the MSP430AFE2xx

Another energy meter from Texas Instruments using MSP430AFE2xx. (PDF)

This application report describes the implementation of a single-phase electronic electricity meter using the Texas Instruments MSP430AFE2xx metering processors. It includes the necessary information with regard to metrology software and hardware procedures for this single chip implementation.

App note: Implementation of a single-phase electronic watt-hour meter using the MSP430AFE2xx – [Link]

WINXI – Arduino ZERO M0 Stick

WINXI – arduino ZERO Pro M0 compatible stick, RGB led, Micro SD, AtSamD21E18. Arduino zero pro compatible board with USB programming suitable for experienced users.

WINXI – Arduino ZERO M0 Stick – [Link]

LT8650S – Dual Channel 4A, 42V, Synchronous Step-Down Silent Switcher

The LT8650S is a dual step-down regulator that delivers up to 4A of continuous current from both channels and supports loads up to 6A from each channel. The LT8650S features the second generation Silent Switcher architecture to minimize EMI emissions while delivering high efficiency at high switching frequencies. This includes integration of bypass capacitors to optimize high frequency current loops and make it easy to achieve advertised EMI performance by eliminating layout sensitivity. Spread spectrum operation can further reduce EMI emissions. The fast, clean, low-overshoot switching edges enable high efficiency operation even at high switching frequencies, leading to a small overall solution size. Burst Mode operation features a 6.2μA quiescent current resulting in high efficiency at low output currents.

LT8650S – Dual Channel 4A, 42V, Synchronous Step-Down Silent Switcher – [Link]

SMA Solar readout

Jean-Claude wanted to read SMA solar inverter data over Bluetooth and so he build this project.

This is the first post of a 3-part series about reading out an SMA solar inverter over Bluetooth and displaying some readings every few seconds. Long-time readers may remember the Solar at last weblog post from several years ago and the SMA Relay, based on a JeeNode v6. The Bluetooth readout code was derived from Stuart Pittaway’s Nanode SMA PV Monitor code.

SMA Solar readout – [Link]

Raspberry Pi Backup Guide

Make a sustainable Raspberry Pi backup server and save your files from occasional loss.

Raspberry Pi backup is what you really need if you work on Raspbian. Believe me, you do! If you backup your Raspberry Pi SD card in due course, someday it may save your files and your project. Alike any other hardware, the RPi devices may sometimes simply stop working.

It can occur due to a number of reasons: overheating, errors, energy supply issues, cable connection failure… All these problems will make you unplug and plug-in again the device to restart it. And such actions taken repeatedly will certainly lead to spoiling your SD card you are saving your work files to.

On the other hand, you can damage or delete your files occasionally with your own hands! There a lot of examples when we do something wrong because of the overall tiredness, inattentiveness or just being in a hurry.

Control a 12V Lamp via SMS with Arduino

In this tutorial we’re going to show you how you can turn a 12V lamp on and off by sending SMS to your Arduino with the text “ON” and “OFF”, respectively. You can also request the current lamp state by sending an SMS with the text “STATE”, the Arduino should reply back with the text “Lamp is on” or “Lamp is off”

Control a 12V Lamp via SMS with Arduino – [Link]

Get Sensor Data From Arduino To Smartphone Via Bluetooth

Hariharan Mathavan at designed a project on using Bluetooth to communicate with an Arduino. Bluetooth is one of the most popular wireless communication technologies because of its low power consumption, low cost and a light stack but provides a good range. In this project, data from a DHT-11 sensor is collected by an Arduino and then transmitted to a smartphone via Bluetooth.

Required Parts

  • An Arduino. Any model can be used, but all code and schematics in this article will be for the Uno.
  • An Android Smartphone that has Bluetooth.
  • HC-05 Bluetooth Module
  • Android Studio (To develop the required Android app)
  • USB cable for programming and powering the Arduino
  • DHT-11 temperature and humidity sensor

Connecting The Bluetooth Module

To use the HC-05 Bluetooth module, simply connect the VCC to the 5V output on the Arduino, GND to Ground, RX to TX pin of the Arduino, and TX to RX pin of the Arduino. If the module is being used for the first time, you’ll want to change the name, passcode etc. To do this the module should be set to command mode. Connect the Key pin to any pin on the Arduino and set it to high to allow the module to be programmed.

Circuit to connect HC-05 with Arduino
Circuit to connect HC-05 with Arduino

To program the module, a set of commands known as AT commands are used. Here are some of them:

AT Check connection status.
AT+NAME =”ModuleName” Set a name for the device
AT+ADDR Check MAC Address
AT+UART Check Baudrate
AT+UART=”9600″ Sets Baudrate to 9600
AT+PSWD Check Default Passcode
AT+PSWD=”1234″ Sets Passcode to 1234

The Arduino code to send data using Bluetooth module:

//If youre not using a BTBee connect set the pin connected to the KEY pin high
#include <SoftwareSerial.h>
SoftwareSerial BTSerial(4,5); 
void setup() {
 String setName = String("AT+NAME=MyBTBee\r\n"); //Setting name as 'MyBTBee'
 BTSerial.print("AT\r\n"); //Check Status
 while (BTSerial.available()) {
 BTSerial.print(setName); //Send Command to change the name
 while (BTSerial.available()) {
void loop() {}

Connecting The DHT-11 Sensor

To use the DHT-11, the DHT library by Adafruit is used. Go here to download the library. When the letter “t” is received, the temperature, humidity, and heat index will be transmitted back via Bluetooth.

circuit to connect DHT-11 with Arduino
circuit to connect DHT-11 with Arduino

The code used to read data from the DHT sensor, process it and send it via Bluetooth:

#include "DHT.h"
#define DHTPIN 2 
#define DHTTYPE DHT11 
void setup() {

void loop()
{ char c; 
 c =; 
void readSensor() {
 float h = dht.readHumidity();
 float t = dht.readTemperature();
 if (isnan(h) || isnan(t)) {
 Serial.println("Failed to read from DHT sensor!");
 float hic = dht.computeHeatIndex(t, h, false);
 Serial.print("Humidity: ");
 Serial.print(" %\t");
 Serial.print("Temperature: ");
 Serial.print(" *C ");
 Serial.print("Heat index: ");
 Serial.print(" *C ");

Developing The Android App

The flow diagram of the Android app is illustrated below,

Flow diagram of the Android app
Flow diagram of the Android app

As this app will be using the onboard Bluetooth adapter, it will have to be mentioned in the Manifest.

uses-permission android:name="android.permission.BLUETOOTH"

Use the following code to test if Bluetooth adapter is present or not,

BluetoothAdapter bluetoothAdapter=BluetoothAdapter.getDefaultAdapter();
if (bluetoothAdapter == null) {
Toast.makeText(getApplicationContext(),"Device doesnt Support Bluetooth",Toast.LENGTH_SHORT).show();

The following part of the code deals with reading the data,

int byteCount = inputStream.available();
 if(byteCount > 0)
 byte[] rawBytes = new byte[byteCount];;
 final String string=new String(rawBytes,"UTF-8"); Runnable() {
 public void run()

To send data, pass the String to the OutputStream.


The complete source code of the Android application can be downloaded from here.


Power up the Arduino and turn on the Bluetooth from your mobile. Pair with the HC-05 module by providing the correct passcode – 0000 is the default one. Now, when “t” is sent to the Arduino, it replies with the Temperature, Humidity, and Heat Index.

the application screen
the application screen

Intel Introduces Loihi – A Self Learning Processor That Mimics Brain Functions

Intel has developed a first-of-its-kind self-learning neuromorphic chip – codenamed Loihi. It mimics the animal brain functions by learning to operate based on various modes of feedback from the environment. Unlike convolutional neural network (CNN) and other deep learning processors, Intel’s Loihi uses an asynchronous spiking model to mimic neuron and synapse behavior in a much closer analog to animal brain behavior.

loihi - Intel's self-learning chip
Loihi – Intel’s self-learning chip

Machine learning models based on CNN use large training sets to set up recognition of objects and events. This extremely energy-efficient chip, which uses the data to learn and make inferences, gets smarter over time and does not need to be trained in the traditional way. The Loihi chip includes digital circuits that mimic the brain’s basic mechanics, making machine learning faster and more efficient while requiring much lower computing power.

The chip offers highly flexible on-chip learning and combines training and inference on a single chip. This allows machines to be autonomous and to adapt in real time instead of waiting for the next update from the cloud. Compared to convolutional neural networks and deep learning neural networks, the Loihi test chip uses many fewer resources on the same task. Researchers have demonstrated learning at a rate that is a 1 million times improvement compared with other typical neural network devices.

The self-learning capabilities prototyped by this test chip have huge potential to improve automotive and industrial applications as well as personal robotics – any application that would benefit from the autonomous operation and continuous learning in an unstructured environment. For example, recognizing the movement of a car or bike for an autonomous vehicle. More importantly, it is up to 1,000 times more energy-efficient than general purpose computing.


  • Fully asynchronous neuromorphic many core mesh.
  • Each neuron capable of communicating with thousands of other neurons.
  • Each neuromorphic core includes a learning engine that can be programmed to adapt network parameters during operation.
  • Fabrication on Intel’s 14 nm process technology.
  • A total of 130,000 neurons and 130 million synapses.
  • Development and testing of several algorithms with high algorithmic efficiency for problems including path planning, constraint satisfaction, sparse coding, dictionary learning, and dynamic pattern learning and adaptation.

Real Time Clock and Temperature Monitor using DS3231 Module

The DS3231 is a very low power RTC chip, it has the ability to keep time with incredible accuracy such that even after power has been disconnected from your product, it can run for years on a connected coin cell battery. This module has the ability to communicate via I2C or SPI but for this tutorial we will be using the I2C mode for communications between our arduino and the DS3231. The module also comes with a quite accurate temperature sensor which we will be using to get temperature readings. The collected temperature and clock data is then displayed on the 16×2 LCD via the Arduino.

Real Time Clock and Temperature Monitor using DS3231 Module – [Link]