Introduction to the GS1 Innovation Network

Transcription

1 Introduction to the GS1 Innovation Network Steve Bratt, CTO and President of Standards Development and EPCglobal, Inc. March 2015 GS1 2015

2 Purpose of the GS1 Innovation Network Develop business and technology foresight and actionable products for GS1 to support strategic, proactive planning and investment GS

3 GS1 Innovation and Standardisation very roughly Timeframe Standards (IE, GSMP, Solutions) < 3 years (sometimes yesterday! sometimes later) Innovation Network (pre-standards) > 3 years Sectors GS1 core GS1 core, but also on periphery Biz needs & solns. Options understood Initially less clear Community Key orgs ready to standardise Few, core orgs ready to explore Process Thorough, focused Light, flexible, exploratory Risk Lower Higher GS

4 GS1 Innovation Network: Making Ideas Happen Innovation Board Prototypes Industry Workshops Pilots GS1 MOs & GO InZone Brainstorming Promising ideas Incubators Actionable products Action Labs External Experts Hackathons Accelerators New Standards New Systems New Solutions GS

5 WHAT S HOT IN THE INNOVATION NETWORK (as of 6 March) Hot Topics 300+ Innovators and growing IZ Brainstorm: Hackathons: Learnings from HackZurich * 52 views GS1 and the Internet of Things * 64 views IZ ID and Capture: Barcode / ID beyond package and POS * 27 Views 2D barcodes at the POS? * 21 Views * Most Exciting Post Most Interesting Tags Internet of Things Internet of Goods Hackathons Pilots Prototypes Exciting News GS1 Spain will be hosting a GS1 Innovation Network Workshop late May Innovation Webinar 25 March 5 GS1 2015

6 Join. Engage. Innovate! GS

7 Auto-ID Lab Japan Research Update March 17, 2015 at GS1 Global Standards Event Shigeya Suzuki, Ph.D. Project Assistant Professor, Keio University Associate Director, Auto-ID Lab, Japan

8 Current Research topics of Auto-ID Lab Japan Application agnostic visibility platform Category based data exchange Open-source Implementation of EPCIS Auto-ID Lab Japan, Keio Research Institute at SFC 8

9 Application agnostic visibility platform Problem: There is duplications of code among EPCIS client to achieve various functionalities Why: There are often common functionalities required among multiple EPCIS clients, such as: SKU based lookup Box and contents relationship handling when communicating with other part of system such as stock management system Auto-ID Lab Japan, Keio Research Institute at SFC 9

10 Application agnostic visibility platform How: As experiments, we have created Aggregation Tracker, and Fulfillment Helper which has generic application functionalities These applications (we categorize them Adaptation Layer) has modified (extended) EPCIS Query Interfaces Can apply similar practice Auto-ID Lab Japan, Keio Research Institute at SFC 10

11 Category based data exchange Problem: There is a case such as disaster supply management, where category based search is required but very challenging Why: There is no common category code available among countries There is discrepancy among currently available category codes, and often difficult Product category code GPC, UNSPSC, JICFS etc. Unique Identifier GTIN, SGTIN, SSCC etc. Unique Identifier GTIN, SGTIN, SSCC etc. Auto-ID Lab Japan, Keio Research Institute at SFC 11

12 Category based data exchange How: Before we will have globally agreed category code, we need a system (or user interface) to create and maintain category code to/from product code mapping We have developed such a system which provide easy to use search interface by using machine learning and collaborative filter Machine learning common use of category code category code search system collaborative filter to recommend popular code New scheme (yellow) outperforms simple search (blue) SCM system Item management system Traceability system Auto-ID Lab Japan, Keio Research Institute at SFC number of selected category code 12

13 Open-source implementation of EPCIS Problem: Open source based EPCIS implementation Fosstrak is not flexible enough compare to nowadays software development standards Difficult to add new features Why: Fosstrak designed and developed long ago, thus haven t make use of newer software development techniques such as: Use of dynamic language for extensibility (such as Ruby) Achieve consistent result by test driven development Use of flexible database mapper to support easier program modification to extend, support for multiple database backends Auto-ID Lab Japan, Keio Research Institute at SFC 13

14 Open-source implementation of EPCIS : EPCIS.rb How: New Implementation of EPCIS: EPCIS.rb Written in Ruby language, which popular among web application developers Very compact (only 1500 lines of code) Flexible Extensible (easy to extend) Easy to setup and deploy Comes with test suites Run with various Database Servers as backend Currently EPCIS 1.0 based. Will support 1.1 before release Will available as Open Source, provided as free software (BSD two clause: Freely redistributable even commercially) Auto-ID Lab Japan, Keio Research Institute at SFC 14

15 Integrating Integrity Into IoT

16 MIT Auto-ID Lab We design, develop, & deploy technology to enable the Internet of Things and the new Digital Economy Bedrock of this economy is ID IP and MAC enabled the Internet of Computers Barcodes, EPCs enable the Internet of Things Auto ID Labs, MIT

17 MIT Auto-ID Lab Getting the ID out there Visibility Usability We try to put the tag on the can Novel Antenna and Substrate Designs Steganographic Methodologies Tracking vaccines in developing countries Applications to enable caregivers in remote areas Employ linked data to integrate product information into Health Department records Auto ID Labs, MIT

18 MIT Auto-ID Lab Beyond ID - use the ID to sense Physical Properties Temperature, Strain Threshold Events Auto ID Labs, MIT

19 MIT Auto-ID Lab Creating Big Data Deploying Sensors Making the Most of the Data Sampling Theory Field Reconstruction Auto ID Labs, MIT

20 MIT Auto-ID Lab Data from Things Auto ID Labs, MIT

21 MIT Auto-ID Lab Data from Things Auto ID Labs, MIT

22 MIT Auto-ID Lab An open standard for object virtualization in the cloud Auto ID Labs, MIT

23 IoT Issues Good News: Lots of Devices are Connected Lots of Data is Generated Bad News: Data is meaningless without context Data is trapped in proprietary systems Auto ID Labs, MIT

24 IoT Issues Siloing Limits interoperability Stifles innovation Auto ID Labs, MIT

25 Opening IoT Siloing Example Automotive Industry What if cars could be un-siloed? Better Data Richer Applications Auto ID Labs, MIT

26 Opening IoT Auto ID Labs, MIT

27 Opening to IoT What if data could be un-siloed? For Consumers User Experience Functionality Access to goods and services For Retailers and Service Providers Richer Logistics B2B and B2C Auto ID Labs, MIT

28 Opening to IoT Taking IoT Further InZone Pilot GS1 Germany Missed boat on vehicles Insert Idea Here A standard for Open Data Interoperable Unfragmented Non-siloed Auto ID Labs, MIT

29 Drive Home Conclusions ID is the Backbone of IoT Connected Devices Generating Big Data Open Standards Needed Auto ID Labs, MIT

30 Integrating Integrity Into IoT