Enabling a Flexible Infrastructure for Internet of Things: Challenges and Experiences

Two critical aspects of a platform for Internet of Things are the ability to manage heterogeneous data from a massive amount of sensors, and the ability to use that data to satisfy bespoke applications and analytics most of which are not known a priori. We take an RDF driven approach to these problems modeling the relationships between Infrastructure-Architecture-Analytics-Application components- and applying it to data exploration, real-time processing, and rapid onboarding of new use cases. We walk through a real implementation of a platform that brings to bear a linked enterprise data model for mapping data within the digital platform to a domain knowledge graph and a model of the heterogeneous data store technology (e.g., time series columnar, RDBMS, Hadoop, traditional EDW). We demonstrate how this platform rapidly enables the deployment and configuration and management of sensor data and applications for a Media Entertainment, Smart Grid, and Smart Water.

In this session we discuss:

RDF enables Google-like contextual exploration of data across heterogeneous data stores
Case study of implementations across domains: Media Entertainment, Smart Water and Smart Grid
Architecture of a real implementation featuring streaming data processing, hybrid storage to manage different kinds of data such as time series, binary/ media, denormalized data, and relational data
RDF drives platform orchestration and automation DevOps
Demo of a working system built with Apache Spark, Cassandra, MongoDB, and Redshift, Intel and Arduino (for connecting live pumps)

Teresa Tung is a senior manager at Accenture Technology Labs responsible for taking the best-of-breed next-generation software architecture solutions from industry, start-ups, and academia, and for evaluating their impact on Accenture's clients through building experimental prototypes and delivering pioneering pilot engagements. Teresa's work created assets across Accenture's API Management Suite, Accenture's Cloud Computing Suite, and Accenture's Green Technology Suite. Recently Teresa is focused on Internet of Things working on real-time streaming analytics, semantic modeling, and infrastructure automation for platforms like Accenture Digital Connected Products and Accenture Analytics-as-a-Service. Prior to joining Accenture, Teresa completed her Ph.D. in Electrical Engineering from the University of California at Berkeley.

Karthik Gomadam is an R and D principal with Accenture Technology Labs, San Jose. His primary interests lie in the areas of Data Integration, Data architecture, and Semantic Web. At Accenture, Karthik has focused on a variety of data problems including Data enrichment, Unstructured Data analysis in Healthcare, Quantified Self, and metadata driven Data architectures. Prior to joining Accenture in 2011, Karthik was a Research Scientist at the University of Southern California, where his work focused on developing algorithms for processing Smart Grid and Smart Oil Field data. During this time, Karthik also founded AppliedInformatics, a healthcare start-up focusing on clinical trials. Karthik got his Ph.D from the Kno.e.sis center at Wright State University in 2009. He attended the University of Georgia from 2002 to 2007. He has authored over 40 peer reviewed research articles in top academic and industry conferences, has been awarded 4 patents.