Save Your Food with Arduino Freezer Temperature Sensor

“Arduino Freezer Temperature Sensor” is an Arduino based project which works as an indicator to notify you when the freezer isn’t work properly. This project was created by “John Saunders”.

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To make this project, you will need these parts:

What it is needed is to connect Arduino board , temperature sensor and LED all together. The sensor must be connected to an analog input port, and the LED to a digital output port as shown the figure below:

freez_circuit_bb

TMP36 is an easy to use temperature sensor with −40°C to +125°C operation range. It has three pins, supply voltage, output voltage, and ground. The input voltage can be between 2.7 and 5.5 V, so we can connect it with the 5V pin in the Arduino. The output voltage is 0.5V for (0°C) and increases by 10 mV/°C. Here is the full Datasheet.

temperature_tmp36pinout

The next step is preparing the code and uploading it to the Arduino board. The code reads the analog value on its pin, and then convert it to the matching temperature degree. If the temperature is in the normal range, the LED will be on, but if it goes above the threshold, the LED will be turned off.

You can download the code file from here.

Watch this step by step guide:

Rubidium Disciplined Atomic Clock

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Cameron Meredith build a real-time-clock module controlled by a rubidium frequency standard, and since it also includes a GPS clock he can track local time dilation effects by comparing the two.

An I2C multiplexer board allows for more than one RTC module (Since these have a hard coded I2C address you can normally only use one). I went for three – One tracking GPS time, another tracking the rubidium standard, and the last one as a control or reference clock – without compensation.

An arduino knock-off compares the relative delay between the pulse-per-second outputs from the Rubidium standard, Real Time Clocks, and GPS.

After some defined time divergence, the RTC aging compensation register is updated to refine or maintain overall agreement. Essentially herding the RTCs so that their output stays within bounded agreement with the Rubidium standard and GPS.

Rubidium Disciplined Atomic Clock – [Link]

Keep Tabs on the Devices Connected to Your LAN

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Would you like to monitor all the devices connected to you LAN. Then you can do it using a Rasberry Pi Zero and a few LEDs.

Like most people, we have tons of things connected via WiFi to our router.  Be it AppleTVs, Rasberry PIs, Amazon Echos, weather stations, overhead airplane trackers, security cameras, etc. etc. etc….  The problem arises when you think and expect a device to “work” and it doesn’t.  Is it the device? Is it the service being accessed? VNC server not running?  Most of the time “all is well“, but if it isn’t it can be frustrating.  Who knew the security camera was down?  Why can’t I VNC into that Raspberry PI?  Most of us have been there and this project helps solve the problem.

Keep Tabs on the Devices Connected to Your LAN – [Link]

Optomyography: A novel approach of detecting muscular signals using optical sensors

Optomyography is a novel, non-invasive, non-contact optical method to measure muscular signals of the human body for diagnosing muscular disorders. It is also considered as an emerging technique for making better human-machine interfaces. Matt, Amrit, and Maneesh conducted an optomyogram experiment at Cornell University to sense the movement of fingers and wrist, and eventually to detect hand gestures. The underlying principle of this experiment is that when you shine an infrared light on a muscle surface, the amount of light absorbed or reflected back depends on the blood volume underneath the skin. Because the blood volume changes with the contraction of muscles, by measuring the variation in the reflected IR light, it is possible to detect the motion of the muscles.

Optomyography for muscle movement detection
Optomyography for muscle movement detection

Their sensor unit consists of an infrared emitter and 4 infrared phototransistors arranged in the form of a wrist band. The infrared light emitted by the IR LED is scattered back and is collected by the phototransistors. An Opamp-based instrumentation circuit further filters and amplifies the phototransistor output to obtain nice and clean Optomygram waveform. The amplified signal then goes to a National Instrument’s Data Acquisition System (DAQ) for further processing.

PC application displays optomygram waveform
PC application displays optomygram waveform

Their team also developed a PC application based entirely in MATLAB. The application provides a nice graphical user interface and also performs sensor calibration. They also implemented a principal coordinate analysis method for the detection of the finger movements. The GUI not only plots the data from the sensor, but also displays which finger of the user was moved. This project was mostly successful and the designers were able to accurately detect the pointer, middle and thumb. However, with adding more sensors in the future, the system performance can be further improved to detect not only all the fingers but hand movements too.

Read More …

A full-featured, portable weather data recorder

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Do you wonder how to build a personal weather station with data logging capability? Well, Jesus Echavarria, a electronic engineer and DIY hardware maker from Spain, has shared the details of his design of a very professional-looking, full-featured, and portable weather data recorder that is capable of recording ambient temperature, humidity, and light level into a SD card along with a time stamp. The datalogger is based on the PIC18F2620 microcontroller and has options to be powered with a rechargeable 3.7V lithium battery as well as from a USB port. It also features a Lithium battery charger circuit on board using Microchip’s fully-integrated MCP73832 Li-Ion charge management controller IC that is configured to provide a charging current of ~200mA. Two on-board LEDs provide visual indications about the battery condition, such as fully charged or under charging.

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On the sensor part, the project uses HDC1050 for temperature and humidity measurements, and TEMT6000X01 for ambient light sensing. The time keeping is performed using M41T00SM6 RTC chip with a separate back-up power supplied from a coin-cell battery.  Two push buttons and two extra leds used in his design to provide a minimal user interface, and most of the configuration part (like time and date settings) is done through a PC terminal program using a command-line interface. The MCP2221 based USB-UART bridge provides the communication interface between the PC terminal program and the PIC microcontroller. Jesus also shares the design files of the 3D printed case he made for his data logger to get a more professional look.

For more details: http://www.jechavarria.com/2016/08/31/portable-temperature-humidity-light-ambient-datalogger/

Wireless temperature and humidity monitor for baby’s room

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This project describes a DIY wireless temperature and humidity monitor for kids’ or infant’s room using the Arduino platform, and inexpensive and easily available ASK transmitter/receiver modules. On the transmitting end, an Arduino nano senses the ambient room temperature and humidity using the DHT22 sensor and transmits the data to a receiving end Arduino over a 433 MHz ASK RF link. The receiving side Arduino decodes the received bytes and displays the information on a LCD screen. The indoor range of the RF transmission is about 100 ft, which is mostly sufficient for a decent size house.

Wireless temperature and humidity monitor for baby’s room – [Link]

Atmel SAMD21G Sensor Board

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Mike Rankin created this tiny sensor board with an ARM Cortex M0+ microcontroller and OLED display:

It’s pretty tiny so a 4 layer board made the whole job easier. The top and bottom are pretty much dedicated for components, layer1 are tracks and power traces, layer2 is a ground plane. Mixing up an internal plane and routing layer was interesting.

Atmel SAMD21G Sensor Board – [Link]

48V/12V DC/DC for automotive dual-rails offers bidirectional power flows

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LTC3871 is a 100V/30V bidirectional two phase synchronous buck or boost controller, for 48V/12V automotive dual battery systems; it provides bidirectional DC/DC control and battery charging between the 12V and 48V boardnets, operating in buck mode from the 48V bus to the 12V bus or in boost mode from 12V to 48V. by Graham Prophet @ edn-europe.com

The LTC®3871 is a high performance bidirectional buck or boost switching regulator controller that operates in either buck or boost mode on demand. It regulates in buck mode from VHIGH-to-VLOW and boost mode from VLOW-to-VHIGH depending on a control signal, making it ideal for 48V/12V automotive dual battery systems. An accurate current programming loop regulates the maximum current that can be delivered in either direction. The LTC3871 allows both batteries to supply energy to the load simultaneously by converting energy from one battery to the other.

48V/12V DC/DC for automotive dual-rails offers bidirectional power flows – [Link]

pcDuino4 Nano, A $20 Development Board

A new low cost development board is available for pre-ordering at $20, it is called “pcDuino4 Nano”. pcDuino term comes from combining Mini PC with Arduino and it is a platform that runs PC-like OS such as Android ICS or Ubuntu.

pcDuino boards can be used to learn programming and understand how to use linux OS. It also works as an interface with electronics hardware alongside the typical activities such as browsing internet and watching movies.

pcduino4-nano

pcDuino4 Nano based on Allwinner H3 SoC, which has a 1.2 GHz quad core Cortex A7 CPU 512KB cache, with an ARM Mali-400MP2 GPU up to 600 MHz. This chip supports DDR2 and DDR3 memories, Ultra HD 4k and Full HD 1080p video decoding, camera and audio integration.

pcDuino4 Nano comes with 1GB RAM memory, microSD card slot, USB 2.0 and micro USB ports, HDMI port, 3.5mm jack, 10/100 M ethernet, DVP interface, pin headers for expansions and powered by 5V.

Here is the full specifications:

  • SoC – Allwinner H3 quad core Cortex A7 @ 1.2 GHz with an ARM Mali-400MP2 GPU up to 600 MHz
  • System Memory – 1GB DDR3 SDRAM
  • Storage – microSD card slot
  • Video & Audio Output – HDMI and 3.5mm jack for CVBS (composite + stereo audio)
  • Connectivity -10/100M Ethernet
  • USB – 3x USB 2.0 host ports, 1x micro USB OTG port
  • Camera – DVP Interface
  • Expansions – 40-pin Raspberry Pi compatible header with UART, SPI, I2C, PWM, GPIOs, etc…
  • Debugging – 4-pin header for serial console
  • Misc – Power and reset buttons; 2x LEDs; IR receiver; on-board microphone.
  • Power Supply – 5V/2A via micro USB port; 4.7V ~ 5.6V via VDD pin on “Raspberry Pi” header.
  • Dimensions – 64 x 50mm (smaller than Arduino UNO and Raspberry Pi)

You might notice that this board is very similar to another one called NanoPi M1. They have the same design, features, ports and schematic and according to CNXSoft the manufacturer is the same. The main difference we can detect is that pcDuino4 has a white PCB and the other has a blue one.

pcduinonanopi

Source: CNXSoft

Whisper Trigger – An Ultra-low Power Voice Detector

For long period of time, we were using our muscles and bodies to control various machines. However, with the growth of technology, things became much easier. We moved to the use of keypads and buttons to get jobs done. Today, touchscreens have appeared and made everything very simple to use. But we did not get enough, and the near future will be for the voice commands.

Using voice commands implies the need to use detection systems and circuits, which must provide high accuracy results, reliable at both near and far distances, not affected by noise, simultaneously sensitive, fast, and also have low power consumption. Power consumption is very important factor nowadays, especially with the application of Internet of Things (IoT) devices which are powered using batteries and have to work for long time.

Most of current solutions for voice recognition use digital signal processors (DSPs) connected with A/D converters and they work in permanent wake mode which make them consume high amounts of  power in case of IoT applications and smartphones.

The conventional Approach
The conventional Approach

Dolphin Integration, a French corporation works on enabling low-power Systems-on-Chip and provides a solution called Whisper Trigger, an ultra-low power voice detector with outstanding performance of detection, enabling wake-up voice acquisition and recognition when needed. In comparison with other devices, this technology reduces power consumption by 80-90%. It consumes only 20 µA, and needs just 1 millisecond to wake up.

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Dolphin Integration provides also another solution for text recognition and detection of keywords, the Microelectromechanical System (MEMS) which should be connected to DSP and circular buffer to perform the process of conversion, decimation and filtering.

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Source: Elektormagazine