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Stephen B Miles
Research Affiliate
Adjunct Research Professor, Zaragoza Logistics Center (ZLC) - MIT CTL SCALE Network
Primary DLC
Center for Biomedical Innovation (CBI)
MIT Room:
E19-604
(978) 884-0214
s_miles@mit.edu
Areas of Interest and Expertise
Internet of Things
RFID+Big Data
Supply Chain/WMS automation
Mobile Applications Specifications/SaaS
Location Based Services
Information Architecture
Start-ups
Entrepreneurship
Strategic Planning
Requirements Analysis
Innovation Management
Risk Management
Product Lifecycle Management
Business/Partnership Strategies
Research Summary
Stephen Miles research has centered around the adoption of Auto-ID systems specifications, which are now instantiated in ISO, for capturing, modeling and optimizing processes in the physical world. Research projects with support from leading technology industry sponsors have included specifying systems for Track and Trace, ePedigree, Supply Chain and Product Lifecycle Management for organizations ranging from the European Commission and the World Customs Organization to the Universal Postal Union.
Current research interests include developing programs for multi-stakeholder data exchange using Application Programming Interfaces (API's) for Electronic Product Code (EPC) and sensor data. Components include developing reference architectures and open frameworks to integrate "big data" from rapidly expanding data sources including High Throughput Analytics (HTA) telemetry data to generate a stream of standardized metadata associated with the content source, and open scaleable systems to support queries/search and event/alert notification based on rule sets.
By assigning URI's for serialized products (UID, EPC, serialized bar codes...) and agreeing on metadata references as proposed in the W3C Linked Data initiative, we can begin to identify relationships between things. Further, by separating data flows into separate layers, we can begin to analyze data from the smallest of systems including genomics, proteomics, metabolomics and data from the human microbiome, to tracking where things are in time and space as well as shared business processes and related outcomes.
(summary updated 12/2014)
Recent Work
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