Team 12- Blind Eye.pptx
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Team 12 created a device to allow visually impaired users to sense their environment without sight. The device uses ultrasonic transmitters and receivers to detect objects from 0-5 meters away. The signals are amplified, digitized by an ADC, and processed by a microcontroller to generate audio outputs indicating the distance and direction of detected objects. The device is powered by batteries and includes linear regulators to supply stable voltages. It will be wearable and hands-free, using beamforming and beamsteering of ultrasonic signals to provide spatial awareness through headphones.
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The document outlines a research proposal on detecting arthritis using thermal imaging. It discusses the literature surrounding using infrared thermography and machine learning to diagnose arthritis. The proposed methodology would involve collecting thermal images of knees, extracting statistical features, and using support vector machines for classification of images as normal or arthritic. The expected outcomes are more accurate detection of arthritis at earlier stages to improve treatment. The timeline outlines the stages of data collection, model development and testing over months.
Ofdm.pptx
This document provides an overview of simulating and synthesizing an OFDM transmitter/receiver in VHDL. It discusses:
- Using simulation to verify functionality and synthesis tools to convert the design into components for the target technology.
- The key blocks of an OFDM transceiver including scrambler, convolutional encoder, interleaver, constellation mapper, IFFT, guard interval addition/removal, and equalizer.
- Challenges in implementing the FFT/IFFT algorithms and mapping the full design to an FPGA due to its size.
PPT FINAL (1)-1 (1).ppt
Rahul Ghore presents a comparison of different MPPT techniques for photovoltaic systems. A fuzzy logic MPPT controller is designed and simulated using MATLAB/Simulink. Simulation results show the fuzzy logic controller tracks maximum power point more effectively than perturb and observe method under changing irradiance levels. The MPPT system with fuzzy logic controller and buck-boost converter maintains continuous source current and delivers power to both DC and AC loads, improving reliability.
Seat Belt IoT 00.pptx
This document describes a project to design and develop a driver safety system using alcohol detection, seat belt detection, and IoT. The system will use a NodeMCU microcontroller, alcohol sensor, IR sensor for seat belts, and ESP32 camera. It will only allow the car to start if the seat belt is worn and no alcohol is detected. All data will be sent to the cloud and viewed on a dashboard. The project aims to reduce accidents from drunk and unbelted driving through real-time monitoring and preventing unsafe vehicle operation.
rain.pptx
This document describes a rain detection system using an Arduino that can trigger an alarm when it rains. The system uses a rain sensor module that detects rain by measuring changes in resistance from water on its surface. When rain is detected, the sensor outputs a signal to an Arduino board that then triggers an alarm. The sensor can be used to automate rainwater harvesting or sprinkler systems by detecting the onset of rain. The document provides details on the components, wiring, and code needed to interface the rain sensor with an Arduino board and respond to rain detection with an alarm.
imagefiltervhdl.pptx
This document provides an overview of a project that implemented image filtering using VHDL on an FPGA board. It discusses designing filters like average, Sobel, Gaussian, and Laplacian filters. Cache memory and a processing unit were developed to hold pixel values and apply filter kernels. Different methods for multiplication in the convolution process were evaluated. Results showed the output images after applying each filter both in software and on the FPGA board. In conclusion, FPGAs provide reconfigurable, accelerated processing for image applications like filtering compared to general purpose computers.
V13I1006.pdf
This document summarizes a study that evaluated the performance of tuned PID controllers for speed control of a DC motor. The researchers developed linear and nonlinear mathematical models of a DC motor and represented the system using state space equations. They then simulated four different PID controllers using MATLAB/Simulink to control the motor speed in response to a step input signal. The system responses under each controller were analyzed and discussed in terms of their performance.
anas.pdf
The document provides a literature review on PM brushless motors, PID controllers, and PID tuning methods. It discusses how PM brushless motors have advantages over other motor types due to their high efficiency, power density, and reliability. It then describes how PID controllers are widely used in motion control despite other advanced control techniques due to their robustness and ease of implementation. Finally, it reviews traditional PID tuning methods like Ziegler-Nichols and relay feedback and discusses how these methods identify critical process parameters to calculate PID gains.
Presentation1.pptx
The document discusses the preprocessing stages for classifying and extracting features from brinjal leaf images. The stages include:
1) Reading RGB images of leaf samples
2) Performing histogram equalization and resizing images to increase quality
3) Using k-means clustering to segment diseased portions of leaves from healthy portions for analysis
4) Converting images to HSI color space and extracting texture features using GLCM to classify images using SVM.
13104 2019 4880_moesm6_esm
The document discusses overall protection systems for overloading protection and interfaces. It appears to be referring to a figure labeled Figure S6 that shows or diagrams the protection systems. The figure aims to illustrate the high-level design or components of a system that protects against overloading and manages various interfaces.
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- 1. Team 12: Blind Eye Aaron Castagna, Dawid Minorczyk, and Nikola Ivancevic
- 2. Introduction ● Over 7 million people in the US suffer from severe visual impairment ● Can we find a way to see without the use of eyes? 2
- 3. Objectives Grant the operator the ability to sense the environment without the use of sight or light. The device will be wearable and hands-free, providing a smaller and more lightweight alternative to a cane. The user will only need to switch the power on and adjust the volume knob on the headphones in order to fully activate and operate the device. Over the range of 0 [m] to 5 [m], sound sensing devices offer a cheaper alternative to light based methods of sensing. 3
- 4. 4
- 5. Power Module: Batteries 2 MN1604 Batteries with 200 mAH charge capabilities. Arranged in series connection with central node grounded. Produces about +9.33 and -9.33 voltage at output rails. Dual output power supply essential for proper amplification. For timespan of 1 hour, [(200 mA) / (320 mA)]*60 = 37 minutes of operation. 5
- 6. Power Module: Linear Regulators MC7805, MC7808, and MC7908 linear regulators with 1A current limits. Two MC7805 regulators used to output 5.01 volts DC to Teensy 3.2 and ADC. One MC7808 and MC7908 used to output +7.998 and -7.955 volts for Op-Amps. 6
- 7. Ultrasonic Sensing: Transmitter and Receiver Following the idea of SONAR and how bats navigate we chose to use ultrasonic transducers, which transmitted/received 40 kHz signals. What are the limitations? Why not LIDAR/RADAR? 7
- 8. Ultrasonic Sensing: Inputs and Amplification 40 kHz, 3.6 volt square wave output from Teensy 3.2. Sent through op-amp with an inverting amplifier configuration. Op-amp has a gain of 2.1 to produce skewed 40 kHz. 7.56 volt square wave. This amplified square wave will then be sent to the transmitter for emission. Total of three transmitters and amplifiers used to allow for beam forming. 8
- 9. Ultrasonic Sensing: Amplification and Output Echoes from transmitted ultrasonic signal are picked up by the receiver. Receiver has built in bandpass filter centered around 40 +/- 1 kHz. Output from receiver is sent into another inverting op-amp circuit . This op amp circuit has a gain of 13.75. Total of three receivers and amplifiers used to allow for beam steering. 9
- 10. Signal Modulation: Rectification and Clamping TLC1518 ADC can only convert analog signals from 0 to 5 volts. Thus, the amplified receiver signal must be modulated. The signal is first rectified with a 1N5819 Schottky Diode and 33KΩ resistor. The signal is then sent through a 1N4733A zener diode to clamp the amplitude at 5.1 volts. A total of three circuits are built to match each of the receiver circuits. 10
- 11. Beamforming and Beamsteering Based off of the principle of constructive and destructive interference of waves A line array of transducers can be utilized to create and steer an acoustic beam in a desired direction. 11
- 13. Digitization: ADC The Teensy needs to be able to read the signals coming from the receivers. Needs a minimum total sample rate of 240ksps. This was calculated from knowing Nyquist sample rate is frequency x 2. Since we are sending at 40 kHz need a sample rate of 80 kHz per channel. 13
- 14. Digitization: Microcontroller Teensy 3.2 Why Teensy over ATMEGA? Clock speed: 96 MHz Bus Speed: 48 MHz DMA, SPI, and Floating Point 14
- 15. Processing: Output Overview Utilization of two nested interrupt timers to create output waveforms Precision of over 200ns in phasing times 15
- 18. Output: Headphones Model S6HBGY Designed to output 3.6 volt square waves into audible frequencies Higher frequencies indicate a close object (880 Hz Max) Lower frequencies indicate a distant object (55 Hz Min) Coupled with beam steering, operator can hear if object is in front of them to within 1.2 meters 18
- 19. PCB 19