Tag Archives: instructable

Make Your Own Laser Scanning Microscope

A laser scanning microscope (LSM) is an optical imaging technique for increasing optical resolution and contrast of micrographs. It permits a wide range of qualitative and quantitative measurements on difficult samples, including topography mapping, extended depth of focus, and 3D visualization.

A laser microscope works by shining a beam of light on a subject in an X-Y plane. The intensity of the reflected light is then detected by a photoresistor (LDR) and recorded. When the various points of light are combined, you get an image.

Venkes had built his own DIY laser scanning microscope with a DVD pick-up, an Arduino Uno, a laser, and a LDR. He had also published an A-Z tutorial about making a similar device.

The result image consists of 256×256 pixels with resolution of 200 nm, about 1300 time enlargement, and it will not cost you a lot because you may have most of the parts. However, the scanning process is a bit slow, it may need half an hour for one image, and it is not crispy sharp.

The parts needed for this DIT LSM are:

  • 2 lens/coil parts of a laser pick-up (DVD and/or CD)
  • a bit of PCB
  • a piece if UTP cable (approx 15cm)
  • An Arduino UNO
  • An LDR
  • 2 x 10uF capacitors
  • 1 x 220 Ohm resistor
  • 1 x 10k resistor
  • 1 x 10k pot
  • 1 x 200 Ohm trim potentiometer
  • 1 breadboard
  • 1 switch
  • 1 3,5 mm jack plug
  • 1 audio amplifier
  • 1 laser with a good collimating lens
  • 1 piece of glass, a quarter of a microscope object glass or so to act as a semipermeable mirror
  • The under part of a ballpoint casing to put the LDR in

For the software side, an Arduino sketch is used to steer the lens, to read the LDR values, and to send information to a Processing sketch which will receive the data and translate it into an image.

You can find more details of this project with the source files at the project’s Instructables page. This video shows the device in action:

MyPart, An Open Source Portable Air Particle Counter

One of the most harmful airborne pollutants with respect to human health is particulate matter. Air particle counters are used to determine the air quality by counting and sizing the number of particles in the air. This information is useful in determining the amount of particles inside a building or in the ambient air. It is also useful in understanding the cleanliness level in a controlled environment.

Airborne particles with a diameter of less than 10 microns pose a large risk, they can travel deeply into the respiratory system, causing a variety of cardiovascular and respiratory diseases. Combustion (e.g. burning wood; automobiles) can generate particles less than 2.5 microns in diameter. Between 2.5 and 10 microns are particles such as dust, pollen, and mold. (More information about particulate matter can be found here.)

Four members of the Hybrid Ecologies Lab at UC Berkeley, Rundong Tian, Sarah Sterman, Chris Myers, and Eric Paulos, developed “MyPart”, a device that attempts to measure air particulate matter.

MyPart’s design focuses on four goals; accuracy, size and portability, cost, and open source.

Accuracy

In the test chamber, smoke concentration was allowed to decay naturally over about 2 hours. Three prototypes of MyPart gave similar accuracy results to an expensive instrument results ($5000 MetOne HHPC-6).

Additional experiments conducted with calibration particles of known sizes and in outdoor ambient environments, and more information about the tests can be found here.

Size & Portability

The overall size of the inner sensing chamber is 18mmx38mmx45mm. These dimensions include an onboard 400mAh battery. The components related to the sensing are completely separated from the outer casing, which allows various form factors to easily be explored, developed, and shared.

MyPart sensor consumes about 2 mA while sleeping, and about 70mA during sampling.

Cost

The total cost for the bill of materials is around $75 without the cost of the digital fabrication tools required to make the components (3D printer and CNC mill). This BOM prices are for electrical components in quantities of 1 or 2, which will drop dramatically when purchased in bulk.

Open Source

MyPart’s original design files and source codes are all open source in order to give people the base form which to make and modify their own sensors, to set up sensing in their own communities, and to generate reliable air quality data.

The full BOM can be found here. The fabrication files, as well as the original design files can be found here.

MyPart’s Parts

  • Top air channel, Contains the main flow channel, a light trap for the laser light, and the air inlet.
  • Bottom air channel, Contains features to hold the fan, and the air outlet
  • Analog cap, shields the sensitive analog circuitry from ambient light
  • Fan, pulls air through the channel
  • Laser, focused light source to illuminate particles in the airstream
  • Laser holder, aligns the laser to the photodiode

Limitations

Optical scattering: The quantity and direction of light scattered by a particle is dependent on the size, composition, and shape of the particle, as well as where it strikes the laser beam. Because of these factors, accurate sizing of particles tends to be difficult with optical scattering sensors. However, rough size cutoff bins can still be produced by using the amplitude of signal peaks.

Full documentation, technical details, and how to build guide are reachable at this seeedstudio article and this instructable.

Controlling A Robotic Arm By Gestures Using Kinect Sensor & Arduino

B.Avinash and J.Karthikeyan had developed a robotic arm that mimic their moves using a Kinect sensor with MATLAB Simulink and an Arduino. The arm was built based on servo motors that replicate the right arm shoulder, elbow and hand movements.

college-project-final-year-2016-9

ic568992The Kinect sensor is a horizontal bar of motion sensing input devices which enable users to control and interact with their computers through a natural user interface using gestures and spoken commands.

The sensor consists of a RGB camera, depth sensor, and multi-array microphone running proprietary software. It provides full-body 3D motion capture, facial recognition, and voice recognition capabilities.

MATLAB Simulink is a graphical programming environment for modeling, simulating and analyzing multidomain dynamic systems. It supports simulation, automatic code generation, and continuous test and verification of embedded systems.

Simulink is developed by Mathworks, and it offers integration with MATLAB environment, enabling developers to incorporate MATLAB algorithms into models and export simulation results for further analysis. Simulink is widely used in automatic control and digital signal processing for multidomain simulation and Model-Based Design.

To build a similar gesture-controlled arm you need these components:

Thanks to Simulink support for Kinect, the computer collects data from the connected kinect device and translates them into servo angles in MATLAB. These angles are sent to the servos through the arduino via TTL device, resulting movement of the arm with a slight delay.

TTL - Arduino & Arduino - Servo Connection Schematic
TTL – Arduino & Arduino – Servo Connection Schematic
Simulink Model
Simulink Model

This project has been chosen in the week’s (29/10/2016) Pick of the Week during Matlab Simulink Hardware Challenge 2016, and it also had won the 4th place in “MATLAB International Simulink Hardware Challenge 2016“.

Arduino code, other files and resources are reachable at this instructable and this hackster.io page.