Using Open Source NoSQL technologies in Designing Systems for Delivering Electric Vehicle Data Analytics.
- Conference
- Location
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Indianapolis, Indiana
- Publication Date
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June 15, 2014
- Start Date
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June 15, 2014
- End Date
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June 18, 2014
- ISSN
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2153-5965
- Conference Session
- Tagged Division
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Computing & Information Technology
- Page Count
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9
- Page Numbers
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24.1339.1 - 24.1339.9
- DOI
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10.18260/1-2--23272
- Permanent URL
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https://peer.asee.org/23272
- Download Count
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526
Paper Authors
Vamshi Krishna Bolly Purdue University
Vamshi K Bolly is a Master of Science student at Purdue University, West Lafayette, Indiana. His research work is related to big data technologies and is concentrated around designing systems for performing electric vehicle data analytics. Prior to his graduate studies, he has about 4 years of industry experience as a software professional.
John Springer Purdue University, West Lafayette, IN, USA
John Springer is an Associate Professor in Computer and Information Technology (CIT) at Purdue University and the Lead Scientist for High Performance Data Management Systems at the Bindley Bioscience Center at Discovery Park. Additionally, he is the chair of the Data Management Curricular Subcommittee in CIT. Dr. Springer's discovery efforts focus on distributed and parallel computational approaches to data integration and analytics, and he serves as the leader of the Discovery Advancements Through Analytics (D.A.T.A.) Laboratory.
J. Eric Dietz Purdue University
Dr. Dietz’s research interests include optimization of emergency response, homeland security and defense, energy security, and engaging veterans in higher education. A professor in Computer and Information Technology and a Director in Purdue’s Discovery Park, Dr. Dietz is responsible for the catalysis of the Purdue’s homeland security research, increasing the impact of Purdue research on society, and organizing interdisciplinary projects within the university. Prior to his current responsibilities, Eric was on loan from Purdue to Governor Mitch Daniels to serve as the founding Executive Director for The Indiana Department of Homeland Security, a new state agency of over 300 people responsible for emergency planning, training, fire and building safety, and disaster response for 6.2 million Indiana residents. During this period, Eric led Indiana’s response to 7 Presidential Major Disasters and Emergency Declarations which included restoration and recovery of critical infrastructure. Eric also led the creation of the Indiana Intelligence Fusion Center and the Indiana Fire Training System both new government functions that were created with new laws and funding. Retiring as a Lieutenant Colonel from the U.S. Army in 2004, Dr. Dietz led a number of Army Acquisition and research programs throughout his career including power systems, chemical sensors and command and control systems. An Indiana native, Eric was graduated in 1984 from Rose-Hulman Institute of Technology after earning a bachelor of science in chemical engineering. He also earned a master’s of science from Rose-Hulman Institute of Technology in 1986 and a PhD in chemical engineering in 1994 from Purdue University.
Abstract
Using NoSQL in Designing Systems for Delivering Electric Vehicle Data Analytics.In the recent times, advances in scientific research related to electric vehicles led togeneration of large amounts of data. This data is majorly logger data collected fromvarious sensors in the vehicle. It is predominantly unstructured and non-relational innature, also called big data. Analysis of such data needs a high performanceinformation technology infrastructure that provides superior computational efficiencyand storage capacity. It should be scalable to accommodate the growing data andensure its security over a network. This research proposes architecture built overHadoop to effectively support distributed data management over a network for real-time data collection and storage, parallel processing, faster and random read accessfor information retrieval for decision-making.This system provides a simplified way of extracting from sensor data loggers andtransforms this raw data into classified buckets. Once imported into a database, thesystem can support efficient analysis and visualization methods to study the dataperform user-required analytics. These analytics can help understand correlationsbetween data parameters under various circumstances. This system providesscalability to support data accumulation in the future and still perform analytics withless overhead. Overall, these open problems in EV data analytics are taken intoconsideration and a low-cost architecture for data management is researched.
Bolly, V. K., & Springer, J., & Dietz, J. E. (2014, June), Using Open Source NoSQL technologies in Designing Systems for Delivering Electric Vehicle Data Analytics. Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--23272
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