EXECUTIVE SUMMARY

Congestion in the parking garages and lots enables tardiness, is a source of stress for students,and wastes hundreds of hours each week. Existing solutions are pricey, ranging from $400-$800per parking space, and require extensive installation. Our system - which monitors the availabilityof parking spaces and relays this information to a smart-phone application - offers an economical$15-$25 per parking space and requires a minimally invasive installation process. We are able toaccomplish this price reduction by using Amazon Web Services in combination with the affordableRaspberry Pi controller to take and store pictures from strategically placed cameras. Using astreamlined process, we upload the pictures, analyze them to determine which spaces are occupied,and update a database with the new information. Users of the phone application will be able toaccess the database, and will be able to determine where to park based on the information.

We plan to test this system in three distinct steps. First, we will build a small scale model of asection of the Elm parking garage, and will begin to test the hardware and software in a controlledenvironment. Second, we will install the Raspberry Pi controllers in the Elm parking garage andtroubleshoot the issues that arise. Once we have solved the problems posed by a real-world setting,we will scale up the system to encompass other garages and parking lots.

The phone application development will proceed alongside the hardware, and will be tested justas extensively as the camera system. To reduce as much friction as possible, the main screen willsimply be a map of the OU campus with pie charts located at each parking lot or garage. Eachpie chart will have a green or red area, and will update to represent the percentage of spaces thatare free relative to the total capacity of the area. When the user taps on the circle, they will moveto a more detailed screen consisting of a diagram of the parking lot that displays occupied spaceswith red rectangles and free spaces with green rectangles. Different tabs can be used to view thedifferent levels of parking garages.

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TABLE OF CONTENTS

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Proposed Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Phases of Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Evaluation Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Qualifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Budget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Total Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

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INTRODUCTION

The purpose of this proposal is to address a smarter parking solution for The University of Okla-homa. Parking is often a problematic situation for students and faculty on campus. The lack ofparking causes students to be late to class on a daily basis. With the quick advances in technology,it is possible to create a system that utilizes cameras in order to provide real time monitoring ofparking spaces. Using the data collected from the cameras, it will be feasible to create a databasethat tracks the availability of the parking spaces, as well as the cumulative time they are occupied.This data would be able to be converted into a smart phone application, allowing commuters knowexactly where there are available parking spaces prior to arriving on campus. The project will helpto serve students, faculty, and visitors at the University of Oklahoma find parking at an alreadyhighly congested campus.

Due to the size of the proposed program, we decided to limit our scope to have specific guidelines.Staying on the north side of campus is necessary due to the project emphasis of commuter andfaculty parking. Any of the dorms or anything south of that would not serve the purpose of helpingtraffic flow for students attempting to get to class. We want our program to be financially realistic.We expect an investment to be made for any change on campus, but that does not mean we needto ask hundreds of thousands of dollars per year. Like any other project, there will be a sizableupfront cost, we project that the total cost of this project will be approximately $150,000, includingmaterials and installation costs.

Based on the research done, there are different methods to detect availability of parking spaces,and the most cost effective is what we’re proposing. For example, one method of detecting vehiclesis an Anisotropic Magneto-Resistive sensor, which detects the disturbance of the Earth’s magneticfield caused by a car above the sensor. One source estimates the cost of an AMR sensor at $7-10[1], which for the 16,000 spaces on campus could cost upwards of $160,000 without taking intoaccount installation costs, the server, and the database to manage these sensors. Another problemwith magnetic sensors is that they are susceptible to “drift” caused by the interference of adjacentvehicles, and the software to manage the sensors must account for this to maintain high accuracy[2]. To avoid these problems, we suggest the use of cameras, although it is important to considerways to counteract the decreased accuracy during bad weather and at night.

In 2013, Rice University undergraduate engineering students started the company ParkiT, whichprovides real time data of parking spots [3]. Using their current technology, they estimate that itwould cost $50 per parking space. There was enough justification for Rice University to fund thisproject, which does not accomplish as much tasks as this one, and it’s more expensive. Due to theproprietary on their product, it is unknown what methods they are using to detect parking spaces.The estimate of cost per parking space for this project is less than $10 per parking space.

We found a multitude of sources during research. Our first primary source is a software engineerat a government nonprofit contractor; Mitre Corporation. Mr. Sandmael Essington provided uswith insight into our project and made recommendations for our project. In addition, we havealso found different scholarly articles that cover our methodology in detail. These articles providedifferent methods to use cameras to detect the image of vehicles in parking spaces, so it would bemore simple to implement this project. Based on the research, one camera can easily detect up to100 parking spaces, as shown in Figure 1.

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Figure 1: Proof of Concept, [4]

Our project will be split up into three stages. The first stage would be a very small scale test. Itwould include a series of matchbox cars with two cameras. The purpose of this would be to testthe cameras’ overlap and view distance, test the software and hardware, and learn to see how all ofthe technology works together. The second stage would be to implement the camera system into aparking garage on campus. We would start with the parking garage on Elm next to Catlett MusicBuilding due to its’ uniform floor plan and smaller size. The idea would be to set up camerason each floor to maximize camera coverage. Our estimate would include six cameras per floortherefore having two per row and two per ramp. The third stage would implement our system overthe entire campus. It would cover all of north campus to target commuter’s parking for efficiencyof travel.

The technology we propose to use would a series of Raspberry Pi’s mixed with software andadditional hardware to enable wireless capabilities and high definition pictures to be taken. Thesewould be placed all around parking lots on campus. We looked at many other technologies andcompared their advantages and drawbacks. We took each into careful consideration. One optionincluded car sensors that would be set on the ground, but these were determined in the studies to betoo expensive and inaccurate. A second option was to have a series of infrared cameras that wouldcover three to six spots each. While very accurate, they would still be too expensive and thereforenot fit the scope. The third option was the Raspberry Pi camera. These can cover many spots eachwith proper setup. They cannot be used efficiently at night, but our target drivers are using theparking spots during the day. With proper placement, this is the most cost efficient option. After

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thoroughly evaluating our options, we decided that the Raspberry Pi cameras would best fit ourscope.

This program is beneficial to the University of Oklahoma in ways that extend beyond ensuringcommuters have access to the availability of parking spaces. This project will allow parking at-tendants to have real-time access to parking violations, potentially increasing the income fromsuch. This project will also be able to increase parking revenue from the University’s sportingevents. The University of Oklahoma may market this project to help attract new students to thecampus. Since this project is cost-effective, the University may even mention the innovation oftheir students are helping change the future for the better.

PROPOSED PROGRAM

Our strategy to actively detect availability of parking spaces uses a network of Raspberry Pi con-trollers with cameras that take a picture of a specific subsection of a parking area every 10 seconds.Using the WI-Fi network, each controller will upload the picture to a single Amazon Web ServicesS3 server using its Internet of Things service. A dedicated computer located elsewhere will down-load the images from the server, process the images with MATLab to determine which spacesare empty, and update a database with the new information. The app will make requests to thedatabase, and will display the new information to the drivers looking for a space. A simplifiedflowchart of this process is shown in Figure 2.

Figure 2: Flowchart of Program

Raspberry Pi is a credit card-sized computer that has been used in a multitude of projects overthe past four years, and has sold over five million units. By using such a popular product thathas undergone several revisions over the years, one source of uncertainty in our parking system isnearly eliminated. Furthermore, the total cost of a Raspberry Pi that has a suitable camera and canconnect to WI-Fi is well below the cost of a prefabricated Internet-connected camera.

Our use of the Amazon Web Services S3 server and DynamoDB database comes with a numberof benefits: 99.999999999% durability, 99.99% availability, the ability to securely transfer data,

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and all at an extremely affordable rate [5], discussed further in the Budget section in this report.Amazon Web Services provide an easy interface to download data to mobile apps, and can interfacewith a Raspberry Pi controller as well. Instead of dealing with the hassle of building and managingour own server, we will essentially rent out space in Amazon’s servers, eliminating a second sourceof uncertainty.

MATLab will be used to process the images sourced from the Raspberry Pi cameras as it hasspecialized software to deal with the complex issues of image recognition. An additional benefitof using MATLab is the breadth of information already available about parking space availabilitydetection. Building on the progress of others who have explored this area before will save us timewhen developing the software, and steer us in the right direction.

Figure 3: Prototype Parking Application

The app will be centered around a main screen with pie charts correlated to how many spots arefilled, which lets the user know at a glance which lots are most open. On choosing a parking area,the user can see a detailed map of which spots are free, organized by floor in the case of a garage,an example of such as shown in Figure 3. Using this information, the user can then make a moreinformed decision about whether or not they should spend time looking for a space or save timeand park in a more available area. The more this app is used, the lower the congestion in garages,as drivers will not have to waste time driving through a garage to see if any spaces are open. The

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app will have a hands free feature available to mitigate using a mobile device while driving. Thisfeature will have voice features stating parking available and where. Placing a liability agreementstating that the driver will not use the app will ensure that the user does not use the app whiledriving. It will also ensure that the developers and stakeholders will not be held liable for anyincidents that result from using a mobile device while driving.

One important aspect of this parking availability system is the speed at which the information canbe updated. The actual time it will take to refresh the data will likely vary from any estimate,but can be determined in the second phase of our plan. Nevertheless, an estimate can be made.We estimate that it will take 30 cameras to cover the Elm garage, and considering that it will takeapproximately 0.5 seconds to upload one image, 0.5 seconds to download it to MATLab, 1 secondto process the image with MATLab, and 0.5 seconds to update the database, we could refresh theentire garage every 2.5 seconds x 30 cameras = 1 minute or so. This would be an unattainably highspeed for an employee, and provides fresh enough information that it would be useful.

PHASES OF IMPLEMENTATION

For our program to work in the most efficient manner while also performing at a high standard,it was deemed that the project should be split up into three phases. We wanted the ability to testthe idea off site in a small scale setting to test hardware and software setups. The second phaseincludes setting up a camera system in a garage to test system stability, data recording, and trendanalysis. Lastly the third phase is intended to implement the project across campus and cover allparking lots and garages. The development of the app will continue parallel to these three phases.

The first stage has a limited set up. Due to wanting to only test hardware and software, we wantedto keep it simple and cheap with only a few materials needed. We would buy a poster board andpaint or draw on it so that it resembles a parking lot. We also need matchbox cars of different sizedto simulate real vehicles and parking small vehicles next to large vehicles, Raspberry Pi’s withattachments, and completed software. The software would ideally have the ability to recognizeparking spaces and whether they were occupied or not. Furthermore, the connections between thedifferent Amazon Web Services will be established, and will connect to the app as well. At thispoint, the user interface will be functional, but not necessarily aesthetically complete, and will betested with a single user. We would set up a camera on each end of the simulated parking lot indifferent set ups to find the optimal viewing points for the cameras. We would also test different setups for vehicles to ensure that our system would be capable of recognizing parking spots inhabited,but only recognized so by one camera. This test may imply worries when concerned with scale,but with different camera placements, the test would perform similar compared a full sized test. Anexample of this happening would be a large vehicle parking in a manner that it obstructs anothersmaller vehicle parked in a neighboring spot. From these tests, we would be able to collect dataon what works and what does not work so that when we are ready for live tests we would be asprepared as possible.

The second stage also has a limited set up, but it much more applicable to a real world settingbecause it is in one. We decided to start in the parking garage next to Catlett Music Building onElm Street on the northwest side of campus. This location was chosen for a multitude of reasons.This garage is one of the busiest garages on campus and would therefore provide good data for test

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runs and data collection we would perform. It also has a uniform layout on all floors. This garagehas a two way ramp in the middle of the building with flat rows of parking on each side. Carsdrive in a clockwise manner up and down the garage. Due to the setup, we determined that eachfloor should have six cameras; one camera in each corner facing towards the parking aisles andtwo cameras on each side of each ramp. This setup would cover all of the parking spaces from twoperspectives and therefore be the most cost and work efficient. These cameras would be tied intothe existing electrical and wireless internet system that the campus provides. They would collectdata for trend analysis as well as parking data so we can provide up to date information on thestatus of parking in the garage. We would analyze and fix any bugs encountered here to be able toprevent or minimize problems from occurring in stage three. In terms of the app, the increase inthe number of cameras might cause some issues in terms of the total time it takes to analyze thephotos, but Amazon Web Services is designed to be easily scaled up. We will continue to refine theuser interface, performing usability tests with a small group and gaining insight into how peoplewould use this app in a real-world setting.

The third stage would be the most extensive as we would be servicing all of the planned parking,but with proper time and project management, the implementation would go smoothly. The ideawould be to start at the northwest side of campus and head southeast. After the phase two Catlettparking garage, we would establish our system in the faculty parking by Goddard and then themultiple parking lots behind and just north of Dale Hall. For parking lots, our cameras would stillbe built into existing electrical and internet networks. We would then go to the North Oval for im-plementation and to make sure that data collection and analysis is working as intended. We wouldhit our next large project with the Union Parking Garage. This garage would be time intensive dueto its setup. With proper planning our team could analyze and implement our system efficientlyinto this garage with its’ long rows and odd layout. From the Union Garage our team would headto the parking next to McCasland field house and then across the street to the commuter parkingthere. A quick jaunt across the street would land us in the Duck Pond parking lots. Completingthis series of lots would be a bit time consuming with the amount of parking available, but no lessfeasible than any of the parking garages. After the Duck Pond lots, we would finish the third stagein the stadium parking garage. This garage has a somewhat similar layout the the Union parkinggarage with its ramps and parking format. This would simplify the camera system layout in thegarage. With only a few minor changes, we would have a complete coverage of the parking in thegarage. With the Stadium parking finished, our third stage would be complete and implementationof the system would be complete. We would gradually make the app available to the public overthe next month by emailing or passing out fliers with unique access codes, to ensure that scalingissues can be resolved as they appear, and to minimize the effect of any possible problems thatarise.

From here we would keep a troubleshooting and maintenance team on campus in case a need cameup. They would ensure proper data analysis for the app and make sure all cameras and systemshad a strong uptime. There would most likely be large amounts of downtime, so the workers couldbe tasked with other duties to keep their productivity at a high. Figure 4 shows a Gantt Chartoutlaying the proposed plan to implement this project.

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App Development

Phase 1 Set-up

Phase 1 Testing

Phase 2 Installation

Phase 2 Troubleshooting

Phase 3 Installation

Phase 3 QA

05 06 07 08 09 10 11 12 01 02 03 04

2016 2017

Figure 4: Gantt Chart

EVALUATION METHODS

Our project will entail a series of deliverables to the University of Oklahoma to utilize and ad-vertise. First of all, we offer a service. The ability to provide students and faculty with a meansto check parking on campus allows people to plan ahead and save time while also reducing theamount of people late to class and meetings. The current parking and expected future parkingwithin the app will work together to ensure that commuters have the easiest time possible finding aparking spot. Second, we offer a product and an idea. Our cameras set up all over campus parkingfacilities enable parking services with a real time option of monitoring parking status. Combinethis with data collection and analysis, parking services can create a better argument to expressneeds when they may arise. For example, if for some reason a parking lot was not being used atall, parking services could re-utilize the area for other, more productive activities. The data anal-ysis would also help on game days or other days when campus has a large influx of people fromother areas. The data gathered about how people travel around campus during these days couldallow for better planning for the city and university. These plans could enable traffic managers tocreate better processes to make traveling in Norman during these days as quick and efficient aspossible. There are many events throughout the year where this app could be implemented duringcampus events. Concerts, holiday celebrations, any sports event, or any large event could use ourapp. Users can plan out parking for said events instead of driving around looking or waiting for aparking spot. Users would also be able to add their own parking spots that they have available. Inthe future, within our app, a user would have the ability to add a series of parking spaces they haveavailable near campus and how much they are demanding for the parking. Users could see howmuch parking is available around campus.

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We have come to expect this project to take a year to complete based on the scope that was createdfor the project. The first phase where we test everything in a small scale should take four to sixweeks. The second phase of implementation into the test parking garage is estimated to take twomonths. From here, the process will be mostly streamlined and all of the bugs and issues will haveresolutions or fixes available. We expect the rest of the project to take eight and a half months tocomplete therefore completing the expected year. Having an idea of this time line will encourageus to stay on schedule while also ensuring that investors do not have any worries about time. Afterthe completion of the project, the University of Oklahoma would have the ability to expand thisservice to south campus and their other campuses as administration saw fit.

To ensure the quality of the products and services we are wanting to provide, we have come upwith a series of tests for our processes. These tests will help us evaluate problem areas as wellas what is working as expected so that we can create fixes quickly therefore reducing the amountof work that needs to be redone. Within our program, we will implement measures to monitorserver uptime with our third party service. This will ensure that the app is updated as expectedand therefore having the most up to date data for commuters to use. During the second stage,we would have team members record incoming and outgoing traffic from the garage to measurecamera accuracy for parking. Our goal is a 98% accuracy for the cameras. If this is not up toour standards, then we will have to recalibrate our software and hardware to ensure high accuracy.Pretty much the entire first stage is an experiment and a quality control setting for our project. It ismeant to ensure that the hardware and software is working as expected before we put any time oreffort into implementing our project into campus parking facilities. Most of this testing will occurin the first stage, but testing will occur throughout the project to ensure high quality work. We wantto ensure the highest quality product and service to be delivered when our project is completed.As students ourselves, we want to have a working system in place so that commuters can be oncampus when planned without too much hassle.

QUALIFICATIONS

Our team is comprised of a multi-talented group of collegiate level individuals. Among us, wehave studies in music, programming, information systems, engineering systems, and research ex-perience. As seniors, we have spent a thorough amount of time watching the University grow froma student’s perspective and seeing what works and what does not. Through our time at the Univer-sity of Oklahoma, we have come to experience areas of campus that need updating and reevaluatedso they can be efficiently utilized for the future of the campus.

Our consultant of whom we asked a series of questions about our project comes from the Universityof Oklahoma. Mr. Sandmael Essington graduated from the University of Oklahoma with hisbachelors and masters degrees in Electrical Engineering. Mr. Sandmael Essington’s professionaltitle is a software engineer and currently works for Mitre corporation. Mitre is a nonprofit thatdoes work on research contracts for the government and most notably the Department of Defense(DoD), Internal Revenue Services (IRS), and the Federal Aviation Administration (FAA).

These qualifications all together give the authors and project a strong foundation to analyze techni-cal problems that might not be realized by administration. This provides our team with a technicaloutlook on issues with a strong emphasis on how to achieve our goals in a realistic and efficient

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manner. Our team was able to recognize the parking problem on campus and look at it from an-other view than just building another parking garage. Our technical solution combined with theexpertise of our own majors and our consultants allow us to objectively see the parking problemand find a solution that makes sense.

BUDGET

Our budget is primarily based off of the findings of the measurements and observations made fromthe different parking facilities we deem fit for our project. The main cost would be the cameraitself. Each Raspberry Pi and all attachments would cost approximately $100 each. For eachgarage, based on floors and set up, we would estimate 30 camera systems needed totaling $3000for equipment per garage. Parking lots are a bit different. They vary greatly in size from theteacher parking lot by McCasland Field House to the Duck Pond Parking Lot. For a lot as smallas the teacher lot by McCasland, we would estimate needing at most 5 cameras. The Duck PondParking Lot would need anywhere from 15-20 cameras. Each parking system needs to be evaluatedindividually to calculate exact costs, but based on estimates, we can create a budget with a range.

Amazon Web Services are very generous with their services. All inclusive with the different as-pects of Amazon Web Services would cost less than $10 a month. On top of that, the first yearunder 5 GB a month would be free of cost. Due to this low cost, we really are not worried about themonetary aspect of this part of the project. It is an impressively low cost for the service provided.

Each phase of our project has costs associated with it. In order to properly make this project areality, we would need to first invest time in the initial research of the project. This primarilyincludes small scale testing. Two cameras are needed to ensure that we can have multiple sourcesof information that can overlap to provide double checking. Model cars / trucks are needed tomake sure that the size of a vehicle does not interfere with a smaller vehicle behind it. We wouldalso need a makeshift parking lot to put the cars on. It could be something simple that we canpaint to resemble a parking lot. Lastly, the cost of the programming software tasked with the jobof distinguishing the vehicle’s parking situation needs to be taken into account. Overall, we wouldexpect this to cost $500.

In the second phase of testing, we would install the cameras at one of the parking garages/lots. Wewould be able to have an up and functional app at this point developed by a team member and haveit so it could be available to the public. We would do occasional spot checks, making sure that theprogram runs as flawlessly as possible. We want something close to a 98% accuracy in order tovalidate our results. This test includes about 30 cameras due to the test occurring in Catlett ParkingGarage. We would also need to take into account the cost to establish an Amazon web server. Thistest would cost an estimate of $4,000.

The third phase would include the final costs of all the cameras, the installation, and all of thesupporting software. The only goal left would be installing the cameras, and making sure they cancommunicate with our server properly. All the kinks that we might experience would be found inour start up phase and our beta phase. After this phase is complete, our project will be completed.These costs are summed up in the next section: Total Costs.

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TOTAL COSTS

There are three parking garages we are focusing on which will need similar amounts of camerasbased on size. It would therefore be safe to assume that the total cost for the three garages based onearlier calculations would be an estimated $4,500 for the cameras. Now to focus on the uncoveredparking around campus that commuters and teachers can park at. Asp Ave. has parking availableon the street needing 5-10 cameras. The teacher lot by McCasland would need 3-6 cameras. TheDuck Pond lot all inclusive would need 15 - 25 cameras. Sarky’s parking would need 10-15cameras due to layout. The parking lot by Dale would need 7-12 cameras. This brings the totalto 40 - 68 cameras needed for an estimated cost to $4,000 - 6,800 for the uncovered parking oncampus. This bring the total equipment cost to $13,500 - 15,300.

Man hours will be easier to calculate. We expect the project to take a year for a small team tocomplete. A team of four people at $30,000 salary each would come out to $120,000 for the year.Afterwards, the support team could be built into a preexisting group to save administrative costsand mixed responsibilities on top of monitoring the parking cameras. We expect that two full timeworkers could handle these responsibilities as well as other responsibilities given as seen fit bymanagers. Paying these workers based off of responsibilities is advised, but we would expect topay an IT employee with multiple responsibilities anywhere from $35,000 - 43,000 a year.

Overall first year costs to completely implement the project would come out to $135,000 - $145,000.For support and to keep the system secure and updated, we would expect the University to pay$75,000 - 90,000 a year for employees and equipment. This is based off hiring two employees plusthe equipment they will need for updates and repairs. Figure 5 is a detailed estimate breakdown ofall required expenses for the proposed program.

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Expenses Quantity Cost TotalPhase 1

Raspberry Pi 2 40 80Camera Attachment 2 30 60Small Scale Model 1 40 40Salary 3 months 10,000/month 30,000

Subtotal 30,180Phase 2

Raspberry Pi 30 40 1,200Camera Attachment 30 30 900Weather Proof Encasement 30 25 750Installation Materials 30 10 300Salary 4 months 10,000/month 40,000

Subtotal 43,150Phase 3

Raspberry Pi 100 40 4000Camera Attachment 100 30 3,000Weather Proof Encasement 100 25 2,500Installation Materials 100 10 1,000Salary 5 months 10,000/month 50,000

Subtotal 60,500Total Expenses

$133,830

Figure 5: Budget Table

REFERENCES

[1] S. Elaouad, S. Benmakhlouf, N. Tobaji, M. A. Dmini and Y. Salih Alj, Car parking manage-ment system using AMR-sensor technology, Electrical and Information Technologies (ICEIT),2015 International Conference, 2015, pp. 414-418.

[2] Z. Zhang, X. Li, H. Yuan, and F. Yu, A Street Parking System Using Wireless Sensor Networks,International Journal of Distributed Sensor Networks, vol. 2013, Article ID 107975, 10 pages,2013.

[3] Hard, Andrew. ParkiT’s Open Spot Detection Technology Is like an ’X-ray for Parking Lots’Digital Trends. N.p., 05 May 2015. Web. 20 Apr. 2016.

[4] C. Huang and Y. Tai and S. Wang, Vacant Parking Space Detection Based on Plane-BasedBayesian Hierarchical Framework, in IEEE Transactions on Circuits and Systems for VideoTechnology, vol. 23, no. 9, pp. 1598-1610, Sept. 2013.

[5] Amazon Simple Storage Service (S3) - Cloud Storage. (n.d.). Retrieved April 20, 2016, fromhttps://aws.amazon.com/s3/

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