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]

Raspberry Pi NAS Tutorial

Building NAS on Raspberry Pi is a very smart way to create DIY NAS for safe and efficient file management. NAS (or Network Attached Storage) Server is a network storage system to serve and share files to other client computers in a local network area. This enables multiple users to access and share the same file storage.

The NAS server can use different file sharing protocols to share the data via the network. The mainly used protocol is SMB (Server Message Block).
Additional protocols are NFS (Network File System), FTP (File Transfer Protocol), SFTP (Secure File Transfer Protocol), SCP (Secure Copy) and more.

The main hardware components of the NAS storage system are the media storage devices, mainly hard drives. If you have more than one storage device mounted on your NAS server, the storage devices can be arranged via a RAID controller (Redundant Array of Independent Disks) into logical and redundant storage containers for redundancy and safety reason. There are various RAID levels to protect the data in case of a disk failure. The most common are RAID-0, RAID-1 and RAID-5.

by eltechs.com

Cubibot: New affortable 3D Printer

Cubibot is a small, clean, simple, stylish & cloud base 3D printer with a heated bed that brings fun and education to your life. Live on kickstarter:

Cubibot is an affordable, user-friendly, high-quality 3D printer with a compact and dynamic design made to fit your lifestyle. Cubibot balances functionality and ease of use without compromising features. Matching the performance and quality of expensive, professional 3D printers at an affordable cost, Cubibot enables you to realize all your imaginations!

Cubibot: New affortable 3D Printer – [Link]

Open Radiation Detector

Quickly identify radioactive materials with a pocket-sized ion chamber. Built from standard parts for easy manufacture and low cost. by Carlos Garcia Saura:

Nuclear radiation is invisible and can be harmful to life. The goal of this project is to provide a simple device that could prevent cases of radiation poisoning. Professional radiation meters can be very accurate, but are also expensive, complex and fragile (most use vacuum discharge tubes made of glass). However in many occasions we only want to determine whether an object is radioactive or not.

Open Radiation Detector – [Link]

Role Of Vision Processing With Artificial Neural Networks In Autonomous Driving

In next 10 years, the automotive industry will bring more change than we have seen in the last 50, due to technological advancement. One of the largest changes will be the move to autonomous vehicles, usually known as the self-driving car. Scientists from many universities are striving to implement vision processing with the artificial neural network to provide driver assistance in self-driving cars.

vision processing
Vision processing using convolutional artificial neural networks

Vision processing, as well as artificial neural networks, have been around for many years. Convolutional artificial neural networks (CNN) are sets of algorithms that extract meaningful information from sensor input. CNN’s are very computationally efficient at analyzing a scene. They are also able to identify objects as cars, people, animals, road signs, road junctions, road marking etc. enabling them to determine the relevant reality of the scene. As this system runs in real-time, the decision can be made as soon as the sensing part is complete.

One of the major steps in visual environment understanding for automotive applications is key points tracking and estimating ego-motion and environment structure subsequently from the trajectories of these key points. A propagation based tracking (PBT) method is popularly used to obtain the 2D trajectories from a sequence of images in a monocular camera setup.

The inputs from one or all of the sensors like LIDAR, RADAR, camera, IR, etc. are evaluated and decisions are taken accordingly. For example, if a car in the front suddenly brakes, the onboard computer would instantly verify the distance and calculate the speed with help of the existing sensors. Then it would apply the brakes faster than any human would be able to do. This method helps to prevent an accident with 90% efficiency.

The use of vision processing with CNN is rapidly increasing in automotive applications to enable camera-based autonomous driving. This technology sets a new driving standard. With this technology in our hand, fewer accidents, fewer fatalities, and less pollution are experienced. Vision processing in autonomous driving also enables efficient journeys, reduced crowding, car sharing, and packing cars in more tightly via vehicle to vehicle communication.

PICKit 3 Mini

Reviahh has published a new project, the PICKit 3 Mini:

Previously, I made a Pickit 3 clone – (see previous blog post). It works well, but I have often wondered just how little of its circuitry was needed to program and debug the boards I make. For instance – I primarily use the newer 3.3V PIC32 processors, so I really don’t need the ability to alter the voltage like the standard Pickit 3 can. I also have no real need for programming on the go, or even to provide power to the target MCU to program. Knowing this – I decided to see what I could do to remove the circuitry I didn’t need, yet still have a functioning programmer/debugger.

PICKit 3 Mini – [Link]

BeanDuino Attiny85 – super small Digispark clone

The BeanDuino is an ATtiny85 based microcontroller development board similar to the Arduino line highly inspired by DigiSpark , BeanDuino is hardware compatible with Adafruit Trinket / Gemma.

Specifications:

  • Support for the Arduino IDE 1.0 and later (OS X, Windows, and Linux)
  • Built-in USB
  • 5 I/O pins (2 are used for USB only if your program actively communicates over USB, otherwise you can use all 5 even if you are programming via USB) or 6 I/O pins if you dissable reset fuse
  • 8 KB flash memory (about 6 KB after bootloader)
  • I2C and SPI (vis USI)
  • PWM on 3 pins (more possible with software PWM)
  • ADC on 4 pins
  • Internal temperature sensor
  • On-board PB1 led – no shield required !!!
  • Keyboard or other HID devices emulation (mouse, gamepad …)
  • reset is enabled you can program this board with USBASP or Arduino via ISP you can easy replace/repair/remove bootloader
  • slim design 11×20 mm
  • breadboard compatible

BeanDuino Attiny85 – super small Digispark clone – [Link]

10A 400V DC Intelligent Power Module (IPM)

10 Amp 400V DC Intelligent power module board has been designed using ON Semiconductors STK544UC62K. This Inverter IPM module includes the output stage of a 3-phase inverter, pre-drive circuits, bootstrap circuits, protection circuits, op-amp based current sense circuit, comparator circuit for fault/Over current output, Bus voltage output, onboard 5V DC regulator for op-amp circuit. This board can be used to drive AC Induction, BLDC, PMSM motors and Brushed DC Motors. The module integrates optimized gate drive of the built-in IGBTs to minimize EMI and losses, while also providing multiple on-module protection features including under-voltage or over voltage , over-current , and fault reporting. The built-in, high-speed HVIC requires only a single supply voltage and translates the incoming logic-level gate inputs to the high-voltage, high-current drive signals required to properly drive the module’s internal IGBTs. Separate negative IGBT terminals are connected to shunt resistor to provide the current feedback to the micro-controller. This IPM module helps to develop various power applications and also can be used as H-Bridge for brushed DC motor. The module mainly helps to drive Hall sensor based, encoder based motors and 3 Phase AC Motors. The IC has Built-in dead-time for shoot-thru protection. Internal substrate temperature is measured with an internal pulled up thermistor. PWM frequency is up to 20 KHz. The board can be used in application like small machines as speed controller, washing machine, refrigerator, Air condition, automation, AC motor speed controller, dc motor speed controller, brushless dc motor driver, ac servo driver.

10A 400V DC Intelligent Power Module (IPM) – [Link]

Attiny Programmer (using Arduino UNO)

by @ instructables.com:

The Arduino UNO is small, but if you require your project to be in a small enclosure, the UNO might be way too big. You could try using a NANO or MINI, but if you really want to go small, you go tiny, Attiny to be precise.

They are quite small, cheap chips (basically small Arduinos) and can be programmed in the Arduino IDE, however you might notice that there is no USB connection. So how do we program it???

Attiny Programmer (using Arduino UNO) – [Link]

Windows PC Lock/Unlock Using RFID

by kksjunior @ instructables.com:

How often have you felt tired of typing in the password to unlock your PC/laptop every time it got locked? I’m used to locking it down quite a number of times, everyday, and nothing is more annoying than typing the password/pin over and over again, every-time I want to unlock it. When the need for something becomes essential, you are forced to find ways of getting it. As the saying goes, “necessity is the mother of invention”, the lazy mind in me started to think of an easy and a cheap way to unlock my personal Computer/Laptop every time I had to lock it. As I went through my stuff I found a RC522 RFID module. That’s when I decided to make an RFID system

Windows PC Lock/Unlock Using RFID – [Link]