1. Capstone Project Fall 2015

2. Course Information Instructor Ye Zhao –Office: MSB 220 –Email: zhao@cs.kent.edu Fall 2015 (MSB162) –Time: Tue, Thu 10:45am – 12:00pm –Lab: MSB 162, Friday 8:50am-10:30am

3. Prerequisite Requested by CS catalog –CS 45201, 43901, 33006 and 43005 –Ask permission if not Programming skills

4. Course Introduction An integrative experience in an applied, hands-on real world project Focus on project design –Background study –Functional design –Schedule –Interface and algorithm implementation Lectures –Necessary backgrounds and technical topics –Most hours allocated for group discussion, procedural report, group or individual questions, as well as documentation and programming

5. Note The class time and lab time are for planning, trouble shooting, and problem solving Students are expected to do most of their development work outside of classes and lab. When project development has started evidence of weekly code development is required.

6. Team Work Equally important to technical development –Effective discussion –Collaboration –Route control –Progress report –Share of achievement and success Students grouped into teams (4-5 members)

7. Project Description Each team will design, develop and demonstrate a web-based, interactive visual analytics system of massive taxi trips in a big city (e.g., New York)

8. Taxi Trajectory Data A large amount of taxis move around streets in big cities –Taxis generate about 20 percent of traffic flow on road surfaces of Beijing Trajectory data “sample” city traffic and human mobility patterns 1/15/2016

9. Massive Taxi Data Big and complex for each day Trips: Origin/Destination Trajectories: including each sample point along the taxi path –Every a few seconds Millions of GPS sample –Geolocation: Latitude and longitude –Vehicle values: speed, direction, occupation

10. Example Data Daily trajectories of 21,360 taxis in Shenzhen Each taxi reports nearly three thousand GPS sample positions per day A total of 59,087,230 samples recorded in one day

11. Task Create a web-based system for users to query, visualize and analyze the big data of taxi trips. Use of New York City Taxi Data Documentation Report

12. Technological Approaches Database management Big data processing Web-based interactive system Information and Map Visualization Tools may include MongoDB, PHP, D3.js, JavaScript, etc.

13. Report and Assessment No paper examinations Biweekly report on class by each team –Progress and problems –Discussions Grading: –Reports and progress: 20% –Final project Result: 50% –Documentation: 30%

14. Questions?