State of RFID Dr. Ray Huetter CTO

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State of RFID Dr. Ray Huetter CTO

  1. 1. State of RFID Dr. Ray Huetter CTO
  2. 2. Large Volume Applications <ul><li>$500+M global industry; $3B by 2010 (Gartner) </li></ul><ul><li>State of the Art </li></ul><ul><ul><li>ePedigree </li></ul></ul><ul><ul><li>Global Supply Chain and Logistics </li></ul></ul><ul><ul><li>Maintenance Repair and Overhaul (MRO) </li></ul></ul><ul><ul><li>Real-time Location Sensors (RTLS) </li></ul></ul><ul><li>RFID Issues </li></ul><ul><li>Research </li></ul>
  3. 3. ePedigree <ul><li>Pharmaceutical Authenticity </li></ul><ul><ul><li>Combats counterfeiting and diversion </li></ul></ul><ul><ul><ul><li>No one knows the size of the problem </li></ul></ul></ul><ul><ul><ul><li>e.g. Epogen/Amgen, red blood cell production, needs storage requirements, dosage ripoff, vials look identical </li></ul></ul></ul><ul><ul><ul><li>Drug from 3 rd world into 1 st world, price point margin </li></ul></ul></ul><ul><ul><ul><li>Almost impossible to detect visually </li></ul></ul></ul><ul><ul><li>Regulatory requirement emerging in US and EU </li></ul></ul><ul><ul><li>ePedigree cut in date for California in Jan 2009 </li></ul></ul><ul><ul><ul><li>Driving force in the US </li></ul></ul></ul><ul><ul><ul><li>Forcing anyone selling product in CA to conform (China and India) </li></ul></ul></ul><ul><ul><ul><ul><li>India has 15,000 pharmaceutical companies </li></ul></ul></ul></ul><ul><ul><ul><li>RFID and serialized barcodes are both solutions </li></ul></ul></ul><ul><ul><ul><li>Key solution is data management </li></ul></ul></ul><ul><ul><ul><ul><li>Correlate location/state with everything that has been manufactured </li></ul></ul></ul></ul><ul><ul><ul><li>Food supply chain equivalent </li></ul></ul></ul><ul><li>Track & Trace Other Goods </li></ul><ul><ul><li>Emerging applications in luxury goods, media </li></ul></ul>
  4. 4. Supply Chain <ul><li>Track and trace for goods and containers (retail) </li></ul><ul><ul><li>Item level tracking on the horizon </li></ul></ul><ul><ul><ul><li>Not really used today </li></ul></ul></ul><ul><ul><li>Tracking of pallets and containers; end-to-end </li></ul></ul><ul><ul><ul><li>From manufacturer (world wide/cross-oceans) </li></ul></ul></ul><ul><ul><ul><li>Through ports, distribution centers </li></ul></ul></ul><ul><ul><ul><li>To stores </li></ul></ul></ul><ul><ul><li>Cooperative between all parties </li></ul></ul><ul><ul><ul><li>Manufacturer, shipping, truck, rail </li></ul></ul></ul><ul><ul><ul><li>Store: storeroom out to shelf </li></ul></ul></ul><ul><ul><li>Mainly pilot projects </li></ul></ul><ul><li>Defense Departments </li></ul><ul><ul><li>Would like to track all goods </li></ul></ul><ul><ul><li>Now are tracking high value goods </li></ul></ul><ul><ul><li>Primary goal is fighter readiness </li></ul></ul><ul><ul><li>Broad utilization </li></ul></ul>
  5. 5. MRO <ul><li>Maintenance, Repair, Overhaul </li></ul><ul><ul><li>Extension of supply chain tracking </li></ul></ul><ul><li>What happens to item after it has been bought/delivered </li></ul><ul><li>Tracking through </li></ul><ul><ul><li>Duty cycle of item </li></ul></ul><ul><ul><li>Warranty management </li></ul></ul><ul><ul><li>Over remanufacturing events </li></ul></ul><ul><ul><li>Through to disposal </li></ul></ul><ul><ul><ul><li>Dangerous items </li></ul></ul></ul><ul><ul><ul><ul><li>Environmental (electronic goods, etc) ROHS (e.g. lead content) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>National Security (defense surplus) eg. authority to purchase </li></ul></ul></ul></ul><ul><li>Greatest value / use case is complex assemblies with long life span </li></ul><ul><ul><li>Aviation </li></ul></ul><ul><ul><li>Automotive </li></ul></ul><ul><li>Can help in monitoring counterfeit replacements </li></ul>
  6. 6. Issues <ul><li>Standardization </li></ul><ul><ul><li>No “perfect” tag </li></ul></ul><ul><ul><ul><li>Many different kinds of tags for many different types of applications </li></ul></ul></ul><ul><ul><ul><ul><li>E.g. active v. passive; cold chain </li></ul></ul></ul></ul><ul><ul><ul><li>RF standards HF vs UHF </li></ul></ul></ul><ul><ul><ul><ul><li>E.g. in pharma: How are biologicals (large molecular weight drugs) affected by RF? Push back from manufacturers. </li></ul></ul></ul></ul><ul><ul><ul><li>Placement on tagged object </li></ul></ul></ul><ul><ul><ul><ul><li>Size, material, liquid viscosity (can change RF characteristics) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>E.g. only one tag fitted on Viagra packaging </li></ul></ul></ul></ul><ul><ul><li>Installation still requires skill; not DIY </li></ul></ul><ul><ul><ul><li>Antenna placement </li></ul></ul></ul><ul><ul><ul><li>RF interference </li></ul></ul></ul><ul><ul><li>Access standards </li></ul></ul><ul><ul><ul><li>EPCIS starting to make an impact </li></ul></ul></ul><ul><ul><ul><li>SQL databases not a good fit </li></ul></ul></ul>
  7. 7. Our View of RFID <ul><li>RFID & sensors augment the physical world </li></ul><ul><ul><li>Goal: assist people and machines to make better use of physical objects </li></ul></ul><ul><ul><ul><li>plan & observe use, identify misuse, predict service </li></ul></ul></ul><ul><ul><ul><li>analyze systemic cause and effect </li></ul></ul></ul><ul><ul><li>Succeed when ROI is demonstrated </li></ul></ul><ul><ul><ul><li>coincides with maximal assistance </li></ul></ul></ul><ul><ul><ul><li>reduction in time, space, matter & energy of processes </li></ul></ul></ul><ul><li>This is common across many domains </li></ul><ul><ul><li>Supply chain, ePedigree, health care, MRO, logistics, … </li></ul></ul>
  8. 8. Potential of RFID <ul><li>RFID will make many contributions </li></ul><ul><ul><li>Economic, environmental, social (health) </li></ul></ul><ul><li>Effectiveness & ROI will be substantial </li></ul><ul><ul><li>Physical optimization (more for less) </li></ul></ul><ul><ul><li>Correct distribution, location and usage </li></ul></ul><ul><ul><li>Safety and correctness </li></ul></ul><ul><ul><li>Prevents harm (food safety) </li></ul></ul><ul><ul><li>Reduction in resources, waste and errors </li></ul></ul><ul><ul><li>Physical process improvements </li></ul></ul><ul><ul><li>Lead to new opportunities… </li></ul></ul>
  9. 9. Best ROI Results <ul><li>Successful pilot projects are showing 5 to 10 times ROI when end-to-end visibility occurs </li></ul><ul><ul><li>Single, accurate timely view </li></ul></ul><ul><ul><li>Across physical & logical boundaries </li></ul></ul><ul><ul><li>By multiple parties </li></ul></ul><ul><li>Why? </li></ul><ul><ul><li>Able to see what happened and when </li></ul></ul><ul><ul><li>Able to reason about it, as and when it happens </li></ul></ul><ul><ul><li>Discover cause and effect </li></ul></ul><ul><ul><li>Use it to ones advantage or correct it </li></ul></ul><ul><ul><li>Optimize: time, space, energy & matter </li></ul></ul>
  10. 10. Control-Feedback Loop Holistic View
  11. 11. Maximizing ROI <ul><li>Maximal ROI occurs when optimization takes into account </li></ul><ul><ul><li>As much fine-grained detail as possible </li></ul></ul><ul><ul><li>Of as many physical objects as possible </li></ul></ul><ul><ul><li>Across as many boundaries as possible </li></ul></ul><ul><ul><li>In as short a time-frame as possible </li></ul></ul><ul><ul><li>For the least price possible </li></ul></ul><ul><li>Conversely, ROI will be limited by </li></ul><ul><ul><li>coarse-grained, filtered / summarized, isolated, untimely or expensive systems </li></ul></ul>
  12. 12. Not Possible Today <ul><li>Most contemporary systems substantially constrain effectiveness & ROI </li></ul><ul><ul><li>Are expensive (relative to the cost of tags) </li></ul></ul><ul><ul><li>Are isolated “stove-pipes” </li></ul></ul><ul><ul><li>Are not real-time </li></ul></ul><ul><ul><li>Do not support continuous operation </li></ul></ul><ul><ul><li>Do not scale with hardware </li></ul></ul><ul><ul><li>Do not cope with volume </li></ul></ul><ul><li>Will be suboptimal </li></ul><ul><ul><li>There is a missing link here… </li></ul></ul>
  13. 13. Requirements <ul><li>Build systems to maximize ROI </li></ul><ul><ul><li>Collect sensor based-data (notably RFID) of arbitrarily large physical systems in real-time </li></ul></ul><ul><ul><li>Use that data to create fine-grained models of in real-time </li></ul></ul><ul><ul><li>Enable new & existing applications / systems to securely </li></ul></ul><ul><ul><ul><li>observe, reason & optimize physical systems </li></ul></ul></ul><ul><ul><ul><li>by querying the current state and history of the model </li></ul></ul></ul><ul><ul><ul><li>adjust the physical system continuously in real-time </li></ul></ul></ul><ul><li>Do this by supporting </li></ul><ul><ul><li>Real-time write back to tags </li></ul></ul><ul><ul><li>Apply rules to produce actionable alerts in real-time </li></ul></ul><ul><ul><li>Pushing changes to applications as they happen </li></ul></ul><ul><ul><li>Applications querying history (prior state) as required </li></ul></ul><ul><ul><li>Replay history of events as they occurred </li></ul></ul>
  14. 14. Holistic View of Physical Systems
  15. 15. SensorConnect System Qualities <ul><li>High performance </li></ul><ul><ul><li>> 50,000 events per second per 64-bit CPU </li></ul></ul><ul><ul><li>< 100 millisecond response time per event, including write-back </li></ul></ul><ul><ul><li>Balance queries with ingestion </li></ul></ul><ul><ul><li>maintain detailed history; replay event history </li></ul></ul><ul><li>Indefinitely scalable </li></ul><ul><ul><li>Support models with billions .. trillions of physical objects </li></ul></ul><ul><li>Widely compatible </li></ul><ul><ul><li>Devices & systems </li></ul></ul><ul><li>Standards compliant </li></ul><ul><ul><li>EPCIS (repository) </li></ul></ul><ul><li>Highly reliable </li></ul><ul><ul><li>Continuous operation via hot failover </li></ul></ul><ul><li>Secure </li></ul><ul><ul><li>Access & authorization controls </li></ul></ul>
  16. 16. University of Arkansas <ul><li>University of Arkansas invited to test SensorConnect core </li></ul><ul><li>Run tests indicative of loads of an entire supply chain </li></ul><ul><li>Motivations: </li></ul><ul><ul><li>Interested in scalable grid technology with application to sensor networks and identity </li></ul></ul><ul><ul><li>Have skills and technology to do synthetic data generation </li></ul></ul><ul><ul><li>Longer term collaboration with RFID technology </li></ul></ul>
  17. 17. Proof of Concept Experiments <ul><li>Purpose </li></ul><ul><li>Test configuration </li></ul><ul><li>Synthetic Data Generation (SDG) </li></ul><ul><li>Descriptions, results, and analysis </li></ul>
  18. 18. Purpose <ul><li>Measure performance of the SensorConnect system while accepting data from an independent, outside source </li></ul><ul><ul><li>Ingestion (insertion) </li></ul></ul><ul><ul><li>Balanced (concurrent ingestion and queries) </li></ul></ul>
  19. 19. Test Configuration <ul><li>ACE four node grid (provided by NSF grant #0410966) </li></ul><ul><ul><li>64-bit dual processor AMD Opterons 1.6 GHz </li></ul></ul><ul><ul><li>2 GB RAM </li></ul></ul><ul><ul><li>60 GB Hard Drive </li></ul></ul><ul><ul><li>1Gbps Ethernet </li></ul></ul><ul><ul><li>Rocks 4.2, Linux Kernel 2.6.9 </li></ul></ul><ul><li>Part of the Open Science Grid </li></ul>
  20. 20. Synthetic Data Generation (SDG) <ul><li>Written in Java </li></ul><ul><li>Accepts Synthetic Data Description Language (SDDL) file as input </li></ul><ul><li>Capable of generating data sequentially or in parallel </li></ul><ul><li>Partitioning algorithms assure that the resulting data set will be consistent regardless of the degree of parallelism used during generation </li></ul><ul><li>Capable of direct-to-database generation, but generating to intermediate text file is more common, and faster </li></ul>
  21. 21. Application:Simple RFID Supply Chain Data <ul><li>Problem: Generate synthetic RFID events (“arrive” and “depart”) for 10 million unique objects traversing 100 read points (total = 2 billion events) </li></ul><ul><li>Row: TagID, ReaderNum, BizEvt, Timestamp </li></ul><ul><li>Total data generated: 86 GB (2B rows) </li></ul>Reader 1 Reader 2 Reader 3 Reader 100 . . .
  22. 22. Experiments Run <ul><li>Peak ingestion </li></ul><ul><li>Event replay </li></ul><ul><li>Query item </li></ul><ul><li>Query history </li></ul><ul><li>Query location description </li></ul>
  23. 23. Peak Ingestion Test
  24. 24. Event Replay Test
  25. 25. Query Item Test <ul><li>A balanced test that returns a tag’s current, or most recent, location </li></ul>
  26. 26. Query History Test <ul><li>This balanced query returned the event history of a tag, or all records recording an “enter” or “leave” event for a given tag </li></ul>
  27. 27. Query Location Description Test <ul><li>A balanced test that returns all tags at a given location, or position, within a supply chain </li></ul>
  28. 28. Experiment Conclusions <ul><li>SensorConnect is designed for multi-core, multi-cpu </li></ul><ul><li>System allows for an unbalanced 400,000 events/second peak ingestion rate </li></ul><ul><li>Balanced tests were able to query data at a rate greater than ingestion </li></ul><ul><li>Deployment of the SensorConnect system in a foreign environment was accomplished with relative ease </li></ul><ul><li>Ultimately the test results far exceeded expectations indicating great promise for the system </li></ul>
  29. 29. Summary <ul><li>Goal of RFID is to assist people and machines to make better use of physical objects </li></ul><ul><li>Successful projects demonstrate ROI </li></ul><ul><li>ROI coincides with maximal assistance </li></ul><ul><li>SensorConnect is a high-volume real-time EPCIS system which models the real-world </li></ul><ul><li>Tests by University of Arkansas show peak performance >400,000 events per sec </li></ul>

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