Project Assignments
 
 
Team Member(s) Project Name
1 Taranjeet Singh Bhatia   NvrBAlone
2 Philip Shibly   SensEvent
3 Vignesh Saravanaperumal   Survey: The Urban Security and Privacy challenges
4 Lauren Ball   FitTogether
5 Michael Betancourt   WiFind
6 Brandon Ochs and Albert Park   PhotoSharing
7 Sara Gaffar   Private Space Detection
8 Travis Cossairt   SportTown
9 Samori Ball   Survey: Environmental Applications in Urban Sensing
10 Brent Horine   Visit Planner (a.k.a. Tourist Flow)
11 Rene Chacon   Detecting Noise Level Strengthens and Longevity
12 Steve Kopman   Bus Truck
13 Eric Minner and James Pittman   NovelSee
14 Siddharth Mohan   Survey: Healthcare Applications in Urban Sensing
15 Chau Ngo   aShockImpact
16 Jonathan Mohlenhoff   EnviroSense
17 Mireshkumar Shukla   Disaster- Help Tahiti

Research project submission requirements:

The project report should be written in the form of a conference paper, you're required to use the ``latex'' (version available for Windows and Linux). See the definition of Latex from Wikipedia. You can download the MikTEX. The The Not So Short Introduction to LATEX is a good manual that I would recommend. Please use Bibtex for the references. Please use the templates from IEEE publications site.

The project report should include:

If you have any questions, please post it to the class emailing address which would be useful for the other students since there are some students in the class who have experience with latex.

NOTE If you would like to propose your own project (individual or as a team), please provide 1 page summary of the proposed project. The project proposals must be turned in to the instructor by the beginning of the third week of classes.

Class Projects

Project 1: Pace of life

We use expressions such as "hectic", "slow" etc. to describe the pace of life in different cities, but is it possible to measure the "pace of life" in a quantitative manner? Can we perhaps use the average speed at which people walk in a city to measure the pace of life in a city?

Given that a lot of people carry mobile phones, we can use these mobile phones to help us to measure the walking speed of people. If many people from many cities contribute data, we can get an idea about the pace of life from many cities. We can perhaps use the data to verify whether it is true that the pace of life in Tokyo is faster than that in Oslo.

A starting point of the project is to look into how to determine whether someone is walking and his/her walking speed, and the get the data contributed to a web site. It may be interesting to think about other metrics too, say do people in one city talk faster than that in another city? How do you measure the speed of talking? etc.

Project 2: Social distance relating to urban space

Houses, enterprises, universities, temples and churches, governmental institutions, etc. represent entities that can be understood in different levels of social proximity to the population. Find a way, how to assign places to social distances using social interactions and community structures. Related question: What is the average Euclidean distance between places with the same social distance in one urban area?

Project 3: Private Space Detection

In dense and crowded cities, private space where people can be alone to relax are rare. Use mobile sensors to find patterns of spatial-temporal private spaces, i.e. spaces that at a certain time more likely to be less crowded.

Project 4: Density Probing for Population Estimation

The population of a city changes not only over several years with birthrate and death rate, but also over several hours. For instance in Luxembourg, the population is about 500k but increases dramatically over the day when people come from Germany or Belgium to work there. Similar dynamics can be observed on Holiday places. Use mobile sensors to locally detect the population density and try to estimate the dynamics in the population changes by interfering local data.

Project 5: NovelSee

Participatory sensing often relies on receiving a great number of varied inputs to provide a useful service. For this project, you are to create a proof of concept, specifically designed to find novel images in the world. Users will snap and upload pictures from their mobile devices to the central server. The server will use an image search system (e.g. Lire: http://www.semanticmetadata.net/lire/) to determine which images received over a certain period of time are the most novel (that is, least like the existing photos in the database). It should then post a photo of the day. This system will help encourage a stream of interesting and novel shots.

Project 6: FitTogether

Working out is often a boring and isolating experience. People work out on rows of machines, on treadmills and the like, typically passing time in solitary pursuits like listening to music or watching TV. Your job is to make a participatory fitness application. Users at a gym would download this app to their device, and start it when they start their work out. They could enter information into it about their current work out (their number of reps, their personal bests, etc, optionally from a sensor like the one available from Nike). The application would encourage competition, cooperation and cohesion. Users should be able to compete in small fitness competitions (e.g. most reps on the machine during the day). Users who like to lift weights may ask for spotters. These are just a few suggestions, but the app can include anything that you think could make the workout more fun and engaging for gym-goers.

Project 7: SensEvent

Special events, including weddings, bar mitzvahs and quinces have long been hot beds of participatory sensing. People typically bring cameras and share their pictures with fellow guests. It is popular to give the guests disposable cameras with which to take pictures. Those who put on the event later mine those photos for ones that are valuable. Your job is to create an application that supports participatory sensing of a special event. The event organizers will first be able to send out invites to the attendees, which they will receive with the application. At the appointed time, the application will become active on the mobile device. Users can then take pictures, record video and audio, which will be timestamped and geocoded. Finally, at the end of the event, the organizers will be able to login to a website which will assemble all of this content by various criteria (by user, in chronological order, by area, etc).

Project 8: Disaster Model

Participatory and urban sensing have huge potential applications for the area of crisis informatics. With platforms like Ushahidi (http://www.ushahidi.com) users with mobile devices can share information that, if properly aggregated, can make coping with a disaster easier. However, in order to create worthwhile applications in this domain, and to be confident that they will do more good than harm, is is imperative to have a model of how events unfold during a disaster. You job is to create such a disaster model for a well known disaster (e.g. the September 11th attacks, Hurricane Katrina, the recent earthquake in Haiti, etc). Using the best available records and research, assemble a simple multiagent model of the events and the response of the victims. Your model should include a simple grid of the area, where grids can be inhabitable, uninhabitable, dangerous, etc. The model should replay events that changed these areas over time, and show how agents responded. Then, you should model a participatory sensing application for these users and gather various simulation statistics about the application. Models like this will be invaluable to assessing the efficacy of crisis sensing applications before they are deployed.

Project 9: GoingMyWay

Ride sharing has become a popular way of reducing transportation costs as well as environmental impact. There are now several web sites that are dedicated to matching up people to car pool. You job is to make these kinds of ride sharing match ups even more convenient and useful, as well as extend them to other types of activities. Build an application that tracks the routes of a user throughout the day. This information should be uploaded (securely and encrypted) to a central web server. Then, the system should look at these routes, and find other users with similar routes. Some work will need to be done to create or adapt a suitable algorithm for this kind of clustering. The application should then connect users together who share common routes, whether those routes are during their daily commute, or part of their recreation time.

Project 10: PhotoSharing

A photo sharing application lets you read the exif data for an image to extract the gps data and display where the image was taken on the map. The goal is to create a social networking photo application that friends can use to share pictures with each other on the iPhone. It will automatically show dots on the map where each image was sent from, and when they select that image it will show an image of the user who sent it (an avatar or some kind of icon) as well as an area for them to chat about the photo.

Project 11: WiFind

Sometimes it is difficult to find open wireless networks to connect to when you are in a new location. Even worst is when there is something critical that you must take care of and your own home network connection is down. My proposal is to make a peer supported map of wireless networks in the area. Data collected would include the GPS location of where a reading was taken as well as the following information about the possible connections:

One key function to the system is to allow for storing of wireless network information locally until a proper network connection can be found. This will provide the database with a bigger data set and can speed up data collection over a large area. Since, we are also recording the cell phone signal strength, a peer based cell phone reception map could also be made. Other applications to the system include raising awareness of how to properly configure routers. Public service announcements could be directed in areas where people do not have security and make sure they are aware of the risks of doing so. Users of the system could register their own access points to the site as a welcomed network connection to those in need. They could also set if their internet connection is down making others in their neighborhood aware of possible outages. This information could be forwarded to Internet Service Providers (ISPs) for instant reporting of problems within their networks.

Project 12: SportTown

Users activate this mobile iPhone app to mark the physical activity/sport they are doing each day and uses GPS data to record the location and time and type of activity. Interface will be simplified to popular categories: walk/run, bike, skate, swim, team sports, gym, etc. and then plotted color-coded on a central map of the city for others to view. Other user's can use the app to filter out to see what other parts of the city are the most physically active, and to find out what kind of activities are available around the area. This would be useful for other people looking to find better/new places to run/bike/skate/swim and be around others of the same physical hobby & sport.

Project 13: Detecting Noise Level Strengthens and Longevity

An app will be created for the Android, that will have two main uses. First, to detect various characteristics of audio signals such as decibel level (via microphone), duration of sound levels (via timer), location of sound levels (via GPS) and possible more. The detection will be performed at specified times and specified locations via user preferences. For example a user might select that once he or she has entered the UCF library (GPS coordinates used) the application will sample the sound levels (turning on the microphone for 10 seconds) for a defined amount of time (every 30 minutes). The app will strive to alleviate any needed interaction with Android phone owner. The app will activate and utilize the microphone and GPS without user interaction but this introduces possible issues such as What if the Android Phone is located inside a sweater inside a bag, the microphone will give incorrect data such as very low noise levels? Is it feasible to instruct the user to not cover or hide the phone, hence leave the phone exposed to environment? What if the APP is programed to only gather data when the phone is being used such as sending text messages, checking time, browser the web or using camera ?

The second main use of the app will be to display visually in a form similar to an audio equalizer the noise levels for specific decibels values for a specified location such as UCF library. The app should be able to convey to a user whether the noise is a result of whispers or loud arguments. In addition the app will specify using coordinates or labels for well known coordinates such as the UCF library where noise levels are being recorded. Finally the app will contain a history of the number of sensors used in a defined area and the sampling rate of the sensors for a defined amount of time such as half a day, 12 hours or less. This data will provide a means for a user to determine the validity and likeness that the observed noise level will indeed remain around the same for the time the app is run.

Project 14: Visit Planner (a.k.a. Tourist Flow)

Issues to be addressed include

Project 15: Bus Truck

Problem: Current mass transit systems rely on printed or website distributed time tables that do not account for weather, traffic or other delay issues. Commuters that use these systems rely on timely departure and arrival times to get to work, meet their friends and attend appointments. Accurate arrival and departure information is not provided to them real-time except in a small number of cases. In addition, users and transit operators do not know accurate wait times for passengers and the number of passengers waiting in line.

Current State of the Art: The Chicago Transit Authority (CTA) has buses and trains that provide detailed route information and location to a mobile application. The system covers the real-time location aspects of the problem but does not cover the wait time tracking. It also requires every bus and train to have a trackable device on-board (GPS or otherwise) to send data to a central processing center.

The University of Utah has a text messaging system where the user can send a text message to a specific number with their bus stop and it will return accurate information on the location of buses and their ETA. This however requires the user to utilize text messaging for each time they want updated status on a buses location. If each user checked the bus location twice per day for 30 days, 120 total messages (one transmit, one receive) would be required. Standard text messaging rates of $0.10 per message would require the user to spend $12/month to have this information.

Proposed Solution: The ubiquity of smartphones provides a logical platform for real-time, user-driven mass transit tracking. The focus of the project is to provide the user real-time feedback on mass transit locations and ETAs on a map. To ensure success on a semester long project, a scaled down version, focusing on one single bus system, is proposed.

The BusTrack application allows the user to enter their current status (waiting, on-the-bus or off-the-bus) and receive real-time status of the bus they are interested in aggregated from other users. The information will be provided using Google Maps.

The scenario for a user is as follows. When the user arrives at the bus stop they start the application. The application uses their current GPS position to present the user with a list of bus routes that service that location or allows the user to select from a list. After this information is entered, the user enters the waiting state and the wait timer is started. A map displays the current location of the bus and an ETA for its arrival at the users location. Once the user is on the bus, they enter the on-the-bus state and the wait timer is stopped. Their current location is recorded and uploaded to a central processing center and aggregated with other users data. When the user exits the bus they enter the off-the-bus state. All GPS tracking is stopped. The mapping information could be viewed from a website as well. This is a stretch goal for the project.

Project 16: EnviroSense

Bringing the next innovation to urban sensing and allowing millions of individuals to use their cell phones to sense their environments, EnviroSense. This sensor attaches to an iPhone and turns the user's iPhone into an environmental sensor. This custom made board will connect to the iPhone via the 30 pin docking connector and will utilize the serial interface in the connector. A custom designed app will communicate with the board and display the values of the environmental sensors. A possible extension of the project would be to incorporate pushing the data to a central server and logging the timestamp and location of the sensor data via the built in GPS. This custom sensor will incorporate three main environmental sensors: temperature, humidity, and barometric pressure. Other sensors could be included if available.

Project 17: aShockImpact

Motivation: Shock caused by the feet striking the ground is transmitted up the legs, through the pelvis, to the lower back. The difference in amount of sock absorb by a person depends on various factors such as surface, speed, type of footwear, pronation (natural inward roll of the foot as the arch collapses (much like a spring) when walking, between the time the heel contacts the ground and toe-off), etc. It can potentially cause pain in legs, knees, and back.

In this project, we will develop an Android software application that utilizes Android phone accelerometer to measure the amount of shock, in g-force, that impacts a person while walking or running.

Designs/Plans: The initial designs/plans for this project are listed below.

Types of data will be provided to users

  • Counts (total number (> threshold) of shocks within time intervals: 1 hour, 1 week, 1 month, etc and total number of shocks within a walking/running distance)
  • Biggest shock
  • Smallest shock
  • Average of all shocks
  • Sum of all shocks
  • Graphs

    • Compare impacts when the user wearing no shoe and different types of shoes. This analysis might potentially help user with the following actions.

  • Determine time to buy new shoe
  • Evaluate shock absorbing shoes quality
  • Determine what type of shoes are needed if provided information about how much shock they can absorb

    • Compare impacts between different speeds
    Compare impacts between different surfaces
    Compare impacts between different left and right leg emphasizes
    Relate collected data to feet, back pain, and any other health issue

    Project 18: Disaster - Help Tahiti

    Motivation: Natural disaster, like earth-quake, flood, drought etc., is unavoidable. And, a big number of people can be affected by these. So we should develop such mobile friendly application in which community can take part and help such disaster affected people.

    Proposed Solution:

  • This mobile application will provide the information (like current news, pictures, videos etc) regarding such natural disaster to the community.
  • The total affected area by disaster on map.
  • The application will show current improvement of the place.
  • How the life has been changed after such disaster?
  • Statistics graph: Like growth, population, etc.
  • We can include “Donate” tab in application, if somebody likes to give donation.

    • Platform:

  • Android Platform will be used to build this application.

    • Project 19: Survey: The Urban Security and Privacy Challenges

    Is there truly a way to be protected? The phone is automatically on because of 911 services. The cell phone company knows where you are traveling- instead of technological issue, this may be a political or legal issue. People will know where you are. If it's not you, someone will pick up the bluetooth signal coming from your phone. Passive monitoring of your presence will be everywhere. Is there going to be a privacy? Similarly, is our personal data sensed and stored somewhere in the cloud really secure?

    This project should survey the security and privacy issues within urban sensing research. The survey should provide summaries of the most widely used techniques and/or applications and evaluate them based on common metrics.

    Project 20: Survey: Technical and Engineering Challenges in Urban Sensing

    Continuous sensing application access hardware sensors on the phone, they use signal processing techniques to extract information from raw data and use classification algorithms or machine learning algorithms software running on the phone or in the cloud. This pipeline of raw data, classification and communication with back-end presents a number of different problems.

    This project should survey the technical and engineering challenges within urban sensing research. The survey should provide summaries of the most widely used techniques and/or applications and evaluate them based on common metrics.

    Project 21: Survey: Healthcare Applications in Urban Sensing

    This project should survey the healthcare applications within urban sensing research. The survey should provide summaries of at least 10 applications (from academia and commercial) and evaluate them based on common metrics.

    Project 22: Survey: Environmental Applications in Urban Sensing

    This project should survey the environmental applications within urban sensing research. The survey should provide summaries of at least 10 applications (from academia and commercial) and evaluate them based on common metrics.