Vertically Integrated Projects (VIP) ECE 279, 379, 479 · PDF fileVertically Integrated Projects (VIP) ECE 279, 379, 479 Introduction Session Jan Allebach School of Electrical and

Vertically Integrated Projects (VIP) ECE 279, 379, 479

Introduction Session

Jan Allebach School of Electrical and Computer Engineering

Purdue University 9 January 2013

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Shared responsibility Teaching each other Leadership

Provide undergraduate students an opportunity to work one-on-one with a faculty member and/or graduate student mentor Give undergraduate students exposure to faculty member’s

research area Provide undergraduate students an opportunity to experience

team-work Collaboration Mutual respect Communication Allow undergraduate students to stretch their imagination

and express their creativity

What are the goals of VIP?

Vertically Integrated Projects (VIP), Spring 2013

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What are the problems? What do they plan to do

next?

Typical elements of the VIP experience

Weekly review meetings with the faculty advisor and/or graduate student mentor Weekly homework assignments to learn background

for project during early part of semester Mixture of hardware and software experiences with

real applications Each group gives a presentation on their project What were the goals? What did they accomplish? How does it work? Poster session and call-out at mid-point of semester Final project presentations and review


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Chih-Chun Wang

Ed Delp

Aaron Ault

Jim Garrison (AAE)

Charles Bouman

James Ogg (EAS)

Dimitri Peroulis David Ebert

Jim Krogmeier David Love

Jan Allebach

VIP Faculty/Staff Team Leaders

Eric Nauman

(ME)

Mark Johnson

Matthew Swabey

Samuel Midkiff

Yung-Hsiang Lu

Vincent Drnevich

(CE)

Niklas Elmqvist


Thomas Talavage

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VIP Projects for Spring 2013 Smart Phone Earth History Visualization Time Domain

Reflectometry Software Defined Radio Visual and Data Analytics Precision Agriculture Cornell Cup Big (Imagery) Data SoCet Autonomous Aerial Vehicle Technologies for

Neuroimaging Wideband software defined

radio for Remote Sensing with Signals of Opportunity

Wireless Energy Harvesting Vertically Integrated Projects (VIP), Spring 2013

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VIP Coordinators

VIP TAs

Jan Allebach Jim Krogmeier

VIP Sponsors

Shao-Fu Xue Alex Layton

VIP Administrative Staff and Sponsors


VIP Lab provides space and facilities for team discussion and collaboration. Lab Guidelines: VIP group-work has the highest priority for use of space and computers. VIP team meetings may require a quiet working environment at times Please do not leave items occupying table space when you leave.

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VIP Laboratory (MSEE 140)


VIP Hardware Lab provides space and facilities for hardware development No fume hood! Windows!

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VIP Hardware Laboratory (EE 238)


https://engineering.purdue.edu/vip/

VIP Website


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Join us on Facebook!

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Poster Session


You MUST: Set your “Team Preference” on VIP Webpage, visit “MyVIP” after login Between Wednesday (01/09) 8:00pm and Friday (01/11) 11:59pm Get your individual picture taken in MSEE140 Turn in a final report (individual or team) Submit a poster for the poster session (team) Turn in your key at the end of the semester

Picture Taking / Key Pick-up Hours (MSEE 140) Monday 1/14 11:00 AM – 12:00 PM Tuesday 1/15 11:00 AM – 12:00 PM Wednesday 1/16 11:00 AM – 12:00 PM Thursday 1/17 11:00 AM – 12:00 PM Friday 1/18 11:00 AM – 12:00 PM

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VIP Requirements


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Have a great semester!


Earth History visualization via Time-Scale Creator package (“time machine”)

www.tscreator.org (Made at Purdue;

hosted here in Engineering)

http://www.tscreator.org

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Spring program -- (1) Visualization

“Evolution Tree” maker (with images)

QuickTime™ and a decompressor

are needed to see this picture.

Spring program -- (2) On-line Datapack makers

“Transect” maker

Spring program -- (3) Data Mining

TDR for Soil Compaction Quality Control

Implement new Time Domain Reflectometry to measure water content and density of soil for construction control

Multiple Rod Probe

TDR Implementation for earth

construction control

New Technology, Patent Pending, ASTM Standard approved, Journal Pubs.

1

1.2

1.4

1.6

1.8

2

2.2

2.4

1 1.2 1.4 1.6 1.8 2 2.2 2.4

rd

(Mg

/m3 )

by

TDR

rd (Mg/m3) by Total Density and Oven-Drying w

0

0.1

0.2

0.3

0.4

0.5

0 0.1 0.2 0.3 0.4 0.5

wb

y TD

R

w by Oven-Drying

Water content comparisons

Density comparisons

Join the TDR Implementation Team

You’ll learn about: An electronic technology, TDR, applied to construction control of soil

Converting electronic measurements to engineering properties of soil

Programming TDR’s for practical field applications

You’ll learn to: Write Apps for wireless communication

Translate TDR signals to engineering properties

Test TDR system in field applications

Contact: Vince Drnevich ([email protected]) or Jim Krogmeier ([email protected])

mailto:[email protected]

mailto:[email protected]

The Software Defined Radio Team

J. V. Krogmeier

School of Electrical and Computer Engineering

Purdue University, West Lafayette

January 9, 2013

Software-Defined Radio

Ideal SDR

• Connect Antenna to an ADC/DAC

• Sampling frequency limitation in RF

• Dynamic range limitation

Practical SDR

• Tunable RF Front-end implemented in hardware

• All digital signal processing in software

VIP has two SDR platforms

• Ettus Research, LLC + GNU Radio

• Rice WARP + Matlab

GNU Radio / USRP Hardware

GNU Radio

• Open source software

• Provides APIs for flexible PHY and MAC support

• Based on C++/Python programming

Universal Software Radio Peripheral (USRP) by Ettus

• Designed to work with GNU Radio

• Combination of

Various RF front-ends daughter boards

(0-100MHz, 400MHz, 900MHz, 2.4GHZ)

ADC / DAC with data rates up to 64 MSample/sec

All DSP functions in software on general-purpose CPU (PC)

Possible SDR Projects

FM Transmitter for iPod Using Radio Broadcast Data System (RBDS)

Software Defined FM Receiver for Inductive and Magnetic Vehicle Detectors

Spectrum Sensing and Modulation Classification

Receiver for NIST’s Radio Station WWVB

January 2012

Visual and Data Analytics Team

PI: Dr. David S. Ebert

Visual Analytics for Command, Control and Interoperability Environments

(VACCINE)

January 2012

Mobile Visual Analytics Law Enforcement

Toolkit (iVALET)

• iVALET uses visualization

tools and techniques to

analyze crime, traffic and civil

incidence data

• Goal: Social media (e.g.,

Twitter) integration & support

January 2012

Web based Visualization for Twitter

Movable Lens showing most

prominent key terms in an area

Used to topically examine

suspicious areas of high

message density

January 2012

• Good programming skills

• Typically: Have taken ECE 264

• Desire to build/develop mobile/web apps

• No prior iPhone programming experience required

• Great resume builder!

Who are we looking for?

Precision Agriculture Systems Join ECE379

We need good, Do-It-Yourself Makers.

Precision Ag: 2 Teams Mobile Apps: - You’ll learn to:

Write apps that interface directly with engine controllers, sensors, and GPS on modern tractors

Write apps that use LiDAR elevation maps to visualize 3-dimensional water flow

Write apps that are cloud-synced to handle large amounts of farm management data

Hardware: - You’ll learn to: Build a CAN-to-Bluetooth adapter board

Interface with a Rasberry Pi Linux device

Build an embedded Linux device

Join ECE 379: Precision Ag

Team

Write Real Apps. Build Real Things.

Contact:

Aaron Ault ([email protected]) Jim Krogmeier ([email protected])

Mark C. Johnson

Director, Instructional Laboratories

COMPETE WITH

TEAMS ACROSS

THE US

WE ARE HEADED

TO DISNEY

WORLD AGAIN!

Jan. 9, 2013

INTEL/CORNELL CUP

COMPETITION

DESIGN TEAM

2011/2012 Entry

“The Incredible HUD”

Aditya Balasubramanian, Blaine

Gardner*, Marcelo Leone, Nikil

Sureskumar (on version 1) * Now here as grad students

Table-It • Gesture control • Presentation control • Pan-tilt image capture • Recording & timeline

INTEL/CORNELL CUP

2013 ENTRY

SEMESTER TWO

Design it, Build it, Test it, repeat

Online Design reviews with Intel

Prepare presentation, demo,

report

Make trip to competition

DESIGN, BUILD,TEST, REVISE,

TEST, REVISE,TEST, REVISE,…

Big (Imagery) Data Team

• Problem: The amount of imagery data (video and

images) is growing much faster than the speed of

computers. A significant portion of data is captured and

thrown away (e.g. streaming video). Meanwhile, many

computers are idle or under-utilized

• Approach: Use volunteer computing to analyze data.

• Goals: Demonstrate the feasibility, understand the

capability, and explore the limitation of this approach

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Big (Imagery) Data Team

• Exemplary analysis: detect cars in traffic video,

evaluate sea level from beach cameras, count crowd

• Technologies: distributed computing, image and video

analysis

• Activities: identify data sources, analyze data, develop

software (based on existing open-source tools)

• Prerequisite: ECE 264

• Team size: min 1, max 5, desired 3

• Advisors: Yung-Hsiang Lu (contact person,

[email protected]) and Edward Delp

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SOCET – DESIRABLE SKILLS SYSTEM ON CHIP EXTENSION TECHNOLOGIES

Problem: ARM has recently made a processor design available to be integrated into System on

Chip designs for education but It is limited, especially as it comes without the

standard debug unit

Solution:

Help me develop a world class debug unit that we can distribute

Help me port the standard CMSIS startup code for the DesignStart Cortex-M0

Opportunity:

Get to know digital design techniques and technologies

Get to know one of the worlds dominant CPU families (more ARM cores have been

made than people on this planet and it outsells x86 by many times)

Get to learn real, applicable skills for your course(s)

Help the cause of System on Chip education

SOCET SYSTEM ON CHIP EXTENSION TECHNOLOGIES

Skills needed:

ECE 362

ECE 337

- or -

Basic Microcontrollers

ASM/C for microcontrollers or similar

HDL (either Verilog or VHDL)

Linux / Unix

Come and talk to me

If you have any Analog VLSI experience come talk to me anyway

• The drone takes off after instruction is sent to it via the computer.

• Automatically tracks once red object comes in view.

AR Drone Team Instructors: Shao-Fu Shih, Prof Charles Bouman,

Prof. Samuel Midkiff

Purdue University


AR Drone Team

Instructors: Prof. Charles Bouman and Prof. Samuel Midkiff

Purdue University


• AR Drone is French made robotic flying

product that can be controlled by Iphone/Ipad

via a wifi connection.

• By modifying Drone’s the C programs, we

can fly the AR Drone with joysticks freely.

• We use the LabView toolkit as a new

interfaceing platform instead of using C

programming. .

• With the tracking info, AR Drone could

navigate automatically.

• AR Drone will be also capable be identifying

different objects to accomplish tasks.

Project Background Future goals

• Track a path using the bottom

camera.

• Trac based on depth

A.R. Drone Linux

Windows, Linux, iOS

Via

Wi-Fi

Joystick

OpenCv

LabView

*NOTE: There are two ways of making the drone fly. Red

designates the hard coded platform in C. The black track is the

current model being used with Urbi.

• Last semesters team worked on the AR Drone during the summer and fall.

• Successfully got the drone to track a red object and follow object

• Explored LabView capabilities

Technologies for

Neuroimaging

• Functional Magnetic

Resonance Imaging (fMRI) is a

powerful tool for the study of

how we think and behave.

Functional Magnetic Resonance

Imaging (fMRI) is a powerful MRI

technique for the study of the brain,

allowing us to understand how we

perceive and think about the world,

and how we interact with it.

The goal of this team is to build

devices that can augment (1) our

ability to how we perceive and think

about the world around us, and (2)

virtual environments in which we

may better probe how we interact

with the world.

Prof. Thomas Talavage

Technologies for Neuroimaging: Goal #1

• fMRI has revealed many aspects of

brain function, particularly regions of

the brain involved in processing

specific stimuli or in performance of

specific tasks. – e.g., Retinotopic maps in visual cortex,

Tonotopic maps in auditory cortex,

Somatotopic maps in motor cortex

• However, the temporal resolution of

fMRI – O(s) – is glacially slow

compared to the speed of inter-

neuronal communication – O(ms).

• We wish to combine the spatial

localization of fMRI with the sub-

millisecond sampling rate of

electroencephalography (EEG).

• We will build an MR-compatible

EEG system.

• Caveats! – Our MRI system is a 3 Tesla

system...60,000 times as strong as the

earth’s magnetic field!

– Unsurprisingly, EEG systems involve a

lot of wire and electronics.

– These two concepts don’t usually mix!

Technologies for Neuroimaging: Goal #2

• fMRI generally requires that the

subject remain still during

experimentation.

• However, we often require the

subject to interact with a stimulus

(game, virtual environment, etc.)

so we can measure performance,

attention or ability. – Current systems are primarily simple

button boxes:

• We will build a fiber-optic based

joystick/button system! – Re-Design, actually ...

Former ECE graduate student

Angela Hoffa playing Super

Mario Bros while using the

prototype joystick. [June 2005]

Garrison: Cyclone Global Navigation Satellite System (CYGNSS) [Pi: Chris Ruf, U Mich]

Microsat constellation to use GNSS reflectometry to observe air-sea interaction in core of developing hurricanes

Selected by NASA (out of 19 proposals) as first Earth-Venture class space mission 151.7M$/7 year effort

NASA HS-3 Globalhawk

Wideband Software Defined Radio for Remote

Sensing with Signals of Opportunity Advisors: Professors James Garrison (AAE) & James Krogmeier (EE)

Graduate Student: Nicole Quindara

Research Goal

• DESIGN a wide-band (20

MHz) multi-channel

recording system for GNSS

signals.

• BUILD flight box prototype

using Universal Software

Radio Peripheral (USRP)

technology.

• TEST full system remote

sensing capabilities.

Project Objectives

• Demonstrate coherent

recording of GNSS signals

from two antennas, using a

highly stable frequency

reference.

Motivation

• New instrumentation for

airborne remote sensing of

ocean winds and

roughness, soil moisture,

and atmospheric

temperature.

Preferred Qualifications

• CAD

• Machine/Electronics Work

• Linux & Bash Scripting

• MATLAB

• USRP

• EE301

Technologies

• Software Defined Radio

• GNSS

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VIP Project with Profs. Peroulis/Scott

What: Wireless Energy Harvesting

Required Background: Electromagnetics

Applications: Wireless powering for cell phones, tablets, or

other consumer electronics

Students: Expect to work > 10h/week in this team. Working

hardware deliverables are required for passing grade

Value in dollar and number of harvesters

sold in 2011 and forecasted for 2017

http://www.energyharvestingjournal.com/articles/energy-harvesting-for-wireless-sensors-1-6-million-units-2011-00004158.asp

Documents

Vertically Integrated Projects (VIP) ECE 279, 379, 479 · PDF fileVertically Integrated Projects (VIP) ECE 279, 379, 479 Introduction Session Jan Allebach School of Electrical and