Kennesaw State University Hackathon 2017

Date of the event

October 5th-8th 2017

Location

Marietta Campus, J/Atrium Building

Cost

Free

Eligibility

This event is open to all KSU CCSE students (ACS, BASIT, IT, CS, SWE, and CGDD) who have passed their first few programming courses. Graduate students who have exempted all transitional courses or have passed at least three 5000 transition courses are also eligible.

HPCC Systems Hackathon Team

Machine Learning for Big Data Analytics on HPCC Systems

Are you interested in how analytics can identify trends which help businesses from a wide range of markets improve their decision making?

Join our team and learn how to use the open source HPCC Systems platform and ECL-ML machine learning libraries, to build predictive models in the fields of insurance, health care, finance, security and other vertical markets.

Challenge

Simulated Vehicle Traffic Monitoring

Driver behavior can encompass an individual’s driving behavior and external factors such as the drive path, volume of traffic, traffic encountered, number of trips, where the streets are and the low/peak activity time and much more.

We are providing some simulated data and would like you to establish whether this data reflects the patterns of driver behavior that we would expect to see in the real world. Meaningful data mining requires in the first instance knowledge about the shape of the data. Once this has been established, it is then possible to identify features which allow you to infer certain conclusions from the data. While we will provide some instructions about the sorts of conclusions we would expect you to discover, the main purpose of the challenge is for you to examine the data for yourself, extrapolate from that data and impress us with your own innovative thought processes and conclusions.

The project goal will be achieved using the HPCC Systems platform by importing, translating and aggregating the data points in conjunction with utilizing the HPCC Systems Machine Learning Library, which provides the tools you need to build learning models from the collected data points.

Although we will be looking at your final code and results, we are particularly interested in your methodology and whether your conjectures prove to be true or false.

The goal will be around building models to address the challenge of the coming traffic revolution due to the introduction of autonomous vehicles.

Watch Flavio Villanustre talk about this challenge.

Data Source

http://kolntrace.project.citi-lab.fr

General Instructions

1. Please follow all the guidelines specified by the data provider.

2. Provide a brief design/tech document describing the proposed solution (2-3 pages max).

3. Provide the bio of all participants and their roles on the project.

4. Use the HPCC Systems platform for executing the solution.

Rating Criteria

1. Innovation involved

2. Understanding of Big Data patterns and its application to HPCC Systems.

3. Team work and execution

4. Presentation quality

Mentors available during the Hackathon

The following mentors will be on site for the duration of the event: Dan Camper, Arjuna Chala and Richard Taylor.

The following mentors will be available to give assistance remotely: John Holt and Roger Dev.

More information about our mentors and how to contact them

Slack Channel

https://ksuccsehackathon.slack.com/