Date of Award
5-2016
Culminating Project Type
Starred Paper
Degree Name
Engineering: M.E.M
Department
Mechanical and Manufacturing Engineering
College
College of Science and Engineering
First Advisor
Dr. Ben Baliga
Second Advisor
Hiral Shah
Third Advisor
Kasi Balasubrahmanian
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Abstract
Implementing Hadoop for data processing and analytics of large dataset helps to store and process large amount of wireless engine data collected from large number of vehicles. This project is mainly focusing on collecting data from Data logger, Telematics and Insite data sources. This project explains us what type of engine data and parameters are getting collected every day. It also describes how this large data is transformed and stored on IBM Big-Insight cluster and how map-reduce framework is used to generate the report. Furthermore, it gives us an idea about how fault codes are analyzed and status is updated to the customers in the form of notifications. This project eventually helps us to understand how Hadoop is effective and faster than MATLAB in terms of speed and volume to process the data from above explained data sources.
Recommended Citation
Rao, Tanvi R., "Performance Improvement and Feature Enhancements of Legacy Machine Data System" (2016). Culminating Projects in Mechanical and Manufacturing Engineering. 40.
https://repository.stcloudstate.edu/mme_etds/40
