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Group #6 Evan Davidson Afsaan Kermani Viker Lamardo Scott Moriarty.

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Presentation on theme: "Group #6 Evan Davidson Afsaan Kermani Viker Lamardo Scott Moriarty."— Presentation transcript:

1 Group #6 Evan Davidson Afsaan Kermani Viker Lamardo Scott Moriarty

2 What is Park Sense? Park sense is a system which maps out a parking lot and detects and displays which parking spaces are vacant and which are occupied.

3 Motivation We wanted to solve an everyday problem that is relevant to UCF students Can take up to 30 minutes to find parking during peak traffic hours 55,000 students at UCF and only 15,500 parking spaces available, not all of which are available to students Help students and faculty get to class on time

4 Objectives Accurate car detection Detect the car in all weather conditions and also during all times of the day *** Lighting conditions, no weather ***** Capable of accommodating a network of cameras so that the project is scalable and can be applied to most of the parking lots in the real world

5 Features LCD display that greets the user as they drive in to the parking lot Website showing live updates on the status of the parking spaces in the parking lot It doubles as a security system because we are using live video feeds Parking stats/data analysis **** move to aditional features *****

6 How it works Image capture Image processing Data output System refresh – Update display

7 Requirements Cost effective and easy to install Weather resistant Fixed position Tamper detection Wide range of view Time stamp and text caption overlay Scheduled day/night mode

8 Specifications Range: minimum of 2 spaces Cost: under $10 per parking space Power source: standard 120VAC (wall outlet) or 12V battery powered Accuracy: 95% and a system refresh time of less than 20 seconds Operating environments -  Temperature: 0 to 115 °F  Humidity: 80% RH

9 System Block Diagram Sensor/CameraServerDisplay Power Data Power

10 Ultrasonic Sensors Would require a large number of sensors to cover a full parking lot Too expensive and too high maintenance Wide range allowed us to possibly use one sensor per two parking spots AdvantageDisadvantage Ultrasonic Emitter/Receiver 1.64’’

11 Infrared Sensors Infrared Range was not as wide as the ultrasonic sensor In the long run, ended up being as expensive as the ultrasonic system Less expensive than the ultrasonic sensor Had longer range than ultrasonic AdvantageDisadvantage

12 Camera 2.34’’ 5.91’’ We decided to use the Vivotek IP7330 for the Park Sense System Description: bullet-style network camera designed for outdoor applications Advantages: shields from harsh conditions such as rain and dust supports tamper detection (i.e. blockage, redirection, & spray-painting) Functions as a security camera for students in the parking lot Has both a long and wide range Has both day and night vision capabilities Easy connection router and server to perform image processing Supports PoE (power over Ethernet)

13 Software Breakdown Capture image Sample and store one JPEG frame from the MJPEG stream Compare JPEG image to control image Output to.csv Update parking lot display Majority of software written in C++ Image capture (MJPEG -> JPEG) Detect a new captured image Store JPEG in memory Compare to control image Output to a.csv file containing row, column, 1 or 0 for vacant and occupied Update displayed information based on spreadsheet data

14 MJPEG to JPEG class Program { static void Main(string[] args) { MJPEGStream stream = new MJPEGStream("http://146.176.65.10/vivotek/mjpg/video.cgi"); stream.NewFrame += (sender, e) => { e.Frame.Save("test.jpg", ImageFormat.Jpeg); Console.WriteLine("frame saved into test.jpg"); // stop capturing frames ((MJPEGStream)sender).Stop(); }; // start capturing frames stream.Start(); Console.ReadLine(); }

15 Image Processing 6+ control images for different lighting situations throughout the day Use Photoshop to determine what grid of pixels fall into our regions of interest (parking spots) Pixel to pixel to comparison, with a set tolerance (to be determined during test), of mapped out region If enough pixels fall outside the tolerance we declare the parking space occupied

16 Final Output Generate a model of the parking lot Use the.csv output to continuously update the model which will be hosted on a website Along with the graphical model we will give a count of vacant and occupied spaces with a percent full figure as well.

17 Display Because we are already generating a webpage, all we have to do is keep that site displayed on an LCD screen mounted at the entrance to the parking lot

18 Server We are utilizing a standard desktop computer with the following specs: Pentium Core2duo - 3.2 GHz 4GB DDR3 RAM HD 750GB

19 Networking Originally we planned on using multiple sensors in a mesh network design, but due to budget constraints and design modifications we decided to use a basic Ethernet network to allow for scalability in practical applications

20 Power The server and display will be powered by a standard 120 V AC outlet within the garage The Vivotek IP 7330 will utilize PoE and be hard wired directly to the server

21 Testing The key aspect of the testing is determining the test location and acquiring control images Different control images are needed for different times of day Through testing determine the tolerance of the pixel to pixel comparison

22 Problems Financing – No sponsorship has made low cost a priority **** cascade, open cv *** We are all hardware oriented in a mostly software project Bad parking – overlapping spots Lighting conditions in the parking lot Cars that are the same color as the asphalt

23 Budget

24 Milestones

25 Percentage Complete

26 Q & A


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