Aquatic Spectrometer & Turbidity Meter ECE 4007 L1, Group 8 Paul Johnson Daniel Lundy John Reese Asad Hashim

Introduction & Background  What is it? A device to detect the colour and clarity of a uniform flowing water sample  How does it work? LED’s, a diffraction grating, a photo- detector array and an on-board PC  Why do we need it? Demand from Aqua-culturists and Water Regulation Authorities for a cheap and easy to use device

High Level Block Diagram

Key Components  Electronics & Optics Controlling the LED’s, collimating the light, obtaining a diffraction pattern  Software Designing code to interpret sensor data and provide useful information  Mechanical Aspects Designing an enclosure, water proofing circuits and designing an interface with existing pipe fittings  Interfacing Controlling LED power, and establishing two-way communication with photo sensor

Electrical Characteristics PARAMETERMINTYPMAX Supply Voltage4.75V5V5.25V Supply Current450mA7251A Operating Temperature-20°+70°C Bandwidth1Hz30Hz

Micron vs. Kodak Image Sensor MicronKodak Cost$30$14 Speed30fps580fps Resolution1280 x x 96 Sensitivity2.1V/lux-sec22V/lux-sec NotesLarger active areaDiscontinued

Micron Image Sensor  10bit parallel data bus  1MHz – 48MHz  I2C control

LED Control  Independent LED control  3V IO lines  OFF for dark current measurement  Transmission measurement  Scatter measurement

Single Board Computer  TS-7250 ARM9 Single Board Computer 200 MHz 32 MB RAM  Programming in C  Compiling with special ARM9 compiler obtained from vendor  Networking software with wireless networking capabilities  Four source files: Main.c SquareWave.c Process.c Networking.c

Software Flow Chart

Photo Sensor Interfacing  Sensor will be clocked at 1.3 MHz  A 1 byte intensity value corresponds to each pixel on the sensor  Sensor acts as a slave device controlled by the SBC  Computer will communicate with the sensor through 8 data lines.  Each wavelength’s intensity value must be multiplied by the inverse of the sensor’s white curve at that particular wavelength to normalize the overall spectrum

Color Analysis - Obtaining Spectrum Values  Intensity values are obtained via serial connection  Values are stored in a vector  Vector is divided into 3 (or more) regions  Total intensity of each region is calculated  The resulting regional intensities are compared to each other and stored as ratios  Ratios are compared to predetermined ratios from known algae samples to determine the algae's growth stage

Spectrum Division

Turbidity Analysis  Regional intensities from color analysis are summed to create an overall intensity  The weaker the overall spectral intensity, the greater the turbidity  Intensity to turbidity conversion will be calibrated by finding the spectral intensities of various samples of water with known turbidities

Networking (if time permits…) SBC sends resulting data to a centralized web server which can be accessed remotely by computer

Scheduling

Parts Cost Analysis PartCost LEDs$9 SBC$184 CMOS Image Sensor$14 Optics Kit$10 Power Supply$20 Misc. Hardware$120 Total$357

Marketing & Cost Analysis  Development Costs: Parts: $357 Labour: $50,000  Final Price: $ Includes parts, marketing, overhead, labour, testing and assembly  Expected Revenue: $374,998  Expected Profit: $91,445 (24.4%)

Conclusions  Electronics Controlled LED’s through power control module and designed photo sensor board  Optics Designed collimating apparatus and positioned diffraction grating & photo sensor  Mechanical Designed enclosure and interfaced with existing pipe fittings  Software Programmed SBC to provide information on colour and clarity of water sample based on ‘dummy data’  Interfacing Have yet to establish useful two way data communication between SBC & photo sensor

Questions?