Spring 2016

This event was held on May 6, 2016 2:00 pm at FIU MMC ECS 241. This semester, 36 of your fellow students together with their mentors from industry and academia worked on 16 exciting projects that are listed below:
Addigy 5.0
BOLO 4.0
Car Recommendation
Contest Registration System 1.0
GenomePro 3.0
Go Local Staff 2.0
GPA Tracker 2.0
HyperDesk 1.0
LegalWise 2.0
Modern Touch 3.0
Robotic Arm 1.0
SkillCourt 4.0
Smart Buildings 4.0
Urban Decision Theatre 1.0
VIP 2.0
Virtual Roll Call 2.0

Senior Project terms:

Mentor(s):

Francisco Ortega

Product Owner(s):

Masoud Sadjadi

Instructor:

Masoud Sadjadi

Project Description

VIP 2.0 project.VIP 2. is a web application that connects faculty members with students in order to facilitate research opportunities that also allow students to get credits for their discipline

Team Members

  • Miguel Conde
  • Tiago Moore
  • Jorge Perez
  • Steven Rowe
  • Victoriano Vega
  • Rodolfo Viant
  • Andres Villa

Mentor(s):

Peeraya, Inyim, Paez, Juan Sotomayor

Product Owner(s):

Mostafavi, Ali, Bobadilla, Leonardo

Instructor:

Masoud Sadjadi

Project Description

Extreme events such as flooding and storm surges due to sea-level rise are significant threats to urban areas. The Urban Decision Theater (UDT) is a 3D Unity application that simulates these extreme event scenarios to allow Urban City Planners to practice and model their decisions, with real world constraints, to find the best available outcome for their cities. UDT simulates such things as traffic, city flood pumps, time, budget, sea-level, and tide.The events and decisions are monitored and routed to an external version of the application. The decisions are also stored in an external server to be reviewed by a moderator. The system supports virtual reality to provide an immersive decision experience in evaluating various scenarios. The main purpose of UDT 1.0 is provide experience to urban-planners to make serious decisions in extreme event scenarios with limited resources like budget and time.

Team Members

  • Tkachenko, Olena
  • Santana, Renan

Mentor(s):

Peeraya Inyim, Maria Presa

Product Owner(s):

Leonardo Bobadilla, Ali Mostafavi

Instructor:

Masoud Sadjadi

Project Description

The new version of Building Brain, which does not directly improve on the application itself, is a simulation, and more specifically, a fast and cheap test environment for the Android app’s features. The simulation will provide the project owner with a flexible experiment that can simulate an entire day of energy usage behavior in under 5 minutes. The use of the Oculus Rift will provide the user/subject with a more immersive experience that not only feels more real, but blocks out any peripheral vision that could suspend disbelief.

Team Members

  • Justin Fletcher
  • Emmanuel Vinas

Mentor(s):

Masoud Sadjadi

Product Owner(s):

Gumi Traustason, Jaime Borras

Instructor:

Masoud Sadjadi

Project Description

In current day, there are a lot of methods of training soccer players. The current systems of training, however, are downright primitive and usually require a field, an instructor, a team and an array of costly elements. Anyone that does not possess these things faces sub-par training. SkillCourt plans to alleviate these requirements through the use of technology. It offers a massive improvement over traditional methods due to personalized sequences and interactions. This document summarizes the requirements, functional and non functional of a SkillCourt Backed system. All established by the product owners Gumi Traustason and Jaime Borras

Team Members

  • Luis Puche
  • Sebastien Dolce

Mentor(s):

Nagarajan Prabakar

Product Owner(s):

Nagarajan Prabakar

Instructor:

Masoud Sadjadi

Project Description

TeleBot is a telepresence, humanoid robot built for the purpose of assisting disabled police and military veterans in their return to the workforce by providing a means of remote law-enforcement surveillance. The software solution discussed within this document is part of the third iteration of the TeleBot prototype. Existing and proposed features were developed to address usability, functionality, and testing limitations present in the previous versions of software in the robotic system.

Team Members

  • Curtis Cox
  • Shadeh Ferris-Francis

Mentor(s):

Jaime Borras

Product Owner(s):

Jaime Borras

Instructor:

Masoud Sadjadi

Project Description

LegalWise 2.0 is a web application that facilitates legal firms, lawyers, law associates, and law students to answer legal questions as well as find information about legal cases using artificial intelligence technologies. This application helps save time by filtering legal documents electronically. In this project, we are using modern technologies and cutting edge methodologies to achieve the expected outcome.

Team Members

  • Fernando Gomez
  • Yang Zhang

Mentor(s):

Pia Celestino

Product Owner(s):

Pia Celestino

Instructor:

Masoud Sadjadi

Project Description

HyperDesk system, a web application for listing/renting office spaces. Unlike current systems, HyperDesk gives users the freedom of naming their own price when wanting to rent a work space. In this document, we include a detailed description of the user stories that were implemented, as well as make note of the user stories that are still pending, supply the project plan including a discussion of each sprint and hardware/software requirements, describe the system design, and provide system validation.

Team Members

  • Rachelle Tobkes
  • Daniel Alvarez

Mentor(s):

Johann Henao

Product Owner(s):

Johann Henao

Instructor:

Masoud Sadjadi

Project Description

The FIU GPA Tracker and Forecaster is a website that assists students keep up with their academics. It does this by providing detailed information about how they are doing in their classes and what they need to earn to achieve their goal GPA by the of graduation. This information is broken down into manageable semester-long goals. In addition, a small Android app has been created that allows students to view and enter their semester grades. This document covers how these features have been improved in the 2.0 version of this system. Details of the makeup of the system and the functionality will be described in detail.

Team Members

  • Lizette Mendoza
  • Alex Sanchez

Mentor(s):

Francisco Ortega

Product Owner(s):

Eduardo Garcia

Instructor:

Masoud Sadjadi

Project Description

Go Local Staff is an iPhone application that aims to eliminate the need for staffing agencies by connecting employers directly to their staff. The app allows employer users to search for, employ, and manage staff. The app also allows staff users to search for and apply to jobs that have been posted by employers. This system removes the bottlenecks of staffing agencies. Users can carry out their desired actions on their own time, inside the app without the need for email, fax, or other software. The process of connecting employers to staff is handled by the app itself. User only need to search for the staff or jobs they are interested in and the app will provide the necessary tools and services to fulfill the user’s needs.

Team Members

  • Stephenson Petit-Homme
  • Daniel Gonzalez

Mentor(s):

Masoud Sadjadi

Product Owner(s):

Michael Robinson

Instructor:

Masoud Sadjadi

Project Description

The purpose of the new system is to create a web application that will be able to automate and accelerate the task of processing staggeringly large genomic data files. The new system will offer users the power to efficiently process genomic data files and generate resultant documents containing accurate information about the differences, similarities, and various statistics between/concerning the associated input data files. In addition, a link to the resultant document will be emailed to users once the system is done processing the input data. Moreover, the new system will allow the users to create and manage their account in which they can keep track of a history of jobs submitted by them and results processed by the system. The new system will also eliminate the need to manually perform these data calculations done by users, which can considerably reduce the amount of errors the users can have while doing it manually. Additionally, the new system will provide to the users the speed, performance and accuracy to make their research advance in a faster pace, while allowing users to parallelize job execution using GenomePro tools.

Team Members

  • Daniel Gonzalez
  • Roberto Arciniegas

Mentor(s):

Kip Irvine

Product Owner(s):

Kip Irvine

Instructor:

Masoud Sadjadi

Project Description

Registration System v1.0 is an interactive website for coaches and administrators to collaborate in the creation and updating competition information. In the newly introduced system, a multiple role system has been added that allows for a coach and an administrator to have separate views of information that they can interact with. A coach can now create an account within the system for easier access to information that pertains to their role. Originally a coach would sign up a team on a form, then submit it to the administrator for review. In the new system a coach will still be able to create a team and add participants, but it will also give a detailed view of all the teams a coach has created. A coach can also modify any information about the participants he has added to a team. The administrator also has the ability to log into the system, but has access to more detailed information about the teams participating in the competitions. The administrator now gets a easy to navigate view of all schools/coaches participating, and is now able to search for a particular school/coach and get that information in a tabular format. The administrator also now has the ability to remove schools from a competition at the click of a button instead of having to remove them through excel. The administrator can now take all the information about a contest(participants, schools, coaches) and archive them for a later viewing with the same ease as the other features.

Team Members

  • Eduardo Guerra
  • Wayne Curling

Mentor(s):

Robert Loredo

Product Owner(s):

Samuel Ceballos, Jason Cohen

Instructor:

Masoud Sadjadi

Project Description

BOLO 4.0 is a private web application that offers police officers the chance to distribute electronic BOLOs(Be on the Lookout flyers) so that their colleagues in the area can have instant access to them. This is meant to agilize the current system, which is considered slow by certain high ranking officers in the force. BOLO 4.0 has a user interface that lets officers upload media and crime details through an electronic form which is contained in a persistent storage provided by IBM.

Team Members

  • Edwin Alvarez Sosa
  • Alejandro Henao
  • Leonardo Martin
  • Piero Messarina

Mentor(s):

Masoud Sadjadi

Product Owner(s):

David Villegas

Instructor:

Masoud Sadjadi

Project Description

Recommendation systems are taking more importance in online businesses, where the ability to propose a new item or product that a user will like can increase sales substantially. In this project, we propose to implement a web page where users can view certain types of items, for example cars, and give their feedback about them, either explicitly (thumbs up / down, likes, ratings...) or implicitly (clicking on item, spending time reading its description, sharing it..) Then, the system will run algorithms to come up with similar items to show to the user, and optionally collect feedback about the quality of the recommendation. Algorithms can range from simple similarity measures, to more complex machine learning models such as the SVM. Different topics of Data Science were applied, such as retrieving information, cleaning it for processing and storing it, evaluating algorithms for recommendation, and implementing big data processing pipelines. In other words, the system will study the user input throughout time, and recommend cars based on machine learning algorithms. This way the user can look into prospective cars that meet his or her expectations.

Team Members

  • Zeev Feldbeine
  • Brenda IzquierdoDavid Villegas

Mentor(s):

Francisco R. Ortega

Product Owner(s):

Francisco R. Ortega

Instructor:

Masoud Sadjadi

Project Description

This project is a software solution to solve the problem of showcasing FIU's OpenHID lab Smart Desk. The desk can contain various devices that have different input methods. Currently implemented devices consist of a Multi Touch Monitor, Tobii EyeX, Intel Real Sense Device, as well as a Leap Motion Controller. Our goal was to create a Painting Application which showcases these various devices and certain functionality they can provide such as Hand Tracking, Facial Recognition, Eye tracking, and finger tracking on a touch pad. We also wanted an environment where we have some sort of control over what the devices do. This experience is designed to be fun and interactive, and provide a way for students using the Smart Desk to get accustomed to and learn about the various devices available.

Team Members

  • Andrew Mitchell
  • Garrett Lemieux