1. Expansion of Remote Sensing Using Radio Frequency Identification (RFID) Technology for Seasonal Load Restriction (SLR) Timing Technical Advisory Committee Meeting Paul J. Fortier † Heather Miller ‡ Ramprasad Balasubramanian ¥ †Electrical and Computer Engineering ‡Civil and Environmental Engineering ¥ Computer and Information Science University of Massachusetts Dartmouth 1

2. Agenda Project Goals Technical Advisory Committee Introductions Project Overview Technical Project Status Business Problems Encountered Next Quarter Plans 2

3. Project Goals Problem Determining placement/removal of SLR for remote/secondary roads Goal is to provide tools for scheduling SLR (become more efficient and more accurate) Develop Architecture and implementation –Flexible –Extensible –Cost effective Develop commercialization plan for concepts 3

4. Technical Advisory Committee Function: to provide project technical assistance and guidance towards commercialization goals Members -Mr Caesar Singh OASRTRS -Alan Hanscom:New Hampshire State DOT -Dale Peabody:Maine State DOT -Maureen Kestler:USDA Forest Service -Shawana Johnson: Global Marketing Insights – President -Christopher Rezendes: INEX Advisors LLC -David Silvia:Naval Undersea Warfare Center – Engineer -Sally Schoop:CRREL – Research Engineer 4

5. Project Overview 5 Project Goal move towards scientific, data driven SLR Build upon findings from RITA RS-11-H-UMDA demo project Research and Develop Extensible Architecture - Develop low cost maintainable infrastructure using IOT concepts - Develop wireless sensors (improved deployment, maintenance, etc.) - Develop flexible data collection and communications node - Develop flexible network base station (or link to existing) Improve DSS system operability Research and develop SLR forecasting models - Review present SLR modeling concepts - Develop forecasting model using findings Move towards commercialization of concepts

6. RITA Demo Key Features System monitors roadway surface and subsurface conditions using wired sensors (thermistors, soil moisture, pressure and surface weather) and transfer data in real-time via satellite or cell network Decision support system automates data reduction and produces graphical displays of frost-thaw penetration and subsurface moisture conditions Database and search engine used to retrieve archived historical data as well as current data Assess integrated predictive model(s) to assist decision makers in applying SLRs 6

7. Test sites and Demo Monitoring System Three demonstration sites established - 2 satellite (Warren, NH and Mariaville, ME) - 1 cell transmission (Madison, ME) Satellite system components integrated by Hoskin Scientific Ltd with Upward Innovations, Inc 7

8. Project’s Approach Take lessons learned from current proof of concept system - COTS sensors and communications methods costly and have been prone to failure (moisture issues, linkage issues) - Current systems have numerous sensors (15 cell and 28 satellite linked) with fixed logging intervals - Upgrading firmware to adjust timing on sensors (lower data rates) - Current GUI and database allows visualization of data in graphical forms - Develop more robust visualization techniques Look at simplification of sensor and communications for sites to improve costing and performance 8

9. Proposed Sensing Approach RFID sensors - Proven technology for numerous industries - Consumer goods tracking - Oil and Gas production - Transportation - construction - Application within transportation infrastructure new - Viable technology supporting low cost, wireless sensing and identification for many applications Smart RFID (chosen technology) with enhance communications - Adds Sensing, processing, storage and communications to Tag 9

10. RFID Overview Radio Frequency Identification (RFID) - Tag wirelessly sends bits of data when triggered by a reader - Power source not required for passive tags (battery for active tags) - Superior capabilities to traditional identification methods - Non line of sight - High speed, multiple reads - Can read and write to tags - Unit specific ID Project looks at simplification of present sensor and communications for sites to improve costing and performance FrequencyDistance Example Application LF125khzFew cm Auto- Immobilizer HF13.56Mhz1mBuilding Access UHF900Mhz~7mSupply Chain μwave2.4Ghz10m+Traffic Toll 10

11. Basic RFID Tag Operating principle Near Field (LF, HF): Inductive coupling of tag to magnetic field circulating around the antenna (magnetic flux induces current in tag) Far Field (UHF, microwave): Backscatter (modulated back scatter by changing antenna impedance) N reader S reader Tag Tag Backscatter Inductive Coupling 11

12. Types of Tags Passive - Operational power scavenged from reader radiated power Semi-Passive - Operational power provided by a battery (battery assisted passive: BAP) Active - Operational power provided by battery – transmitter built into tag 12

13. Electronic Product Code Header – Tag version Number EPC Manager – Manufacturer ID Object class – Manufacturers' product ID Serial number – Unit ID 13

14. Smart Sensors Standard IEEE 1451.7 Extension of EPC integrated with TEDS EPC- defines the tag TEDS – defines the metadata for the sensor associated with the tag 14

15. Proposed site Architecture Integrated Tag sensors, reader, solar charger and communications network to DSS backend RFID Sensors (integrated temperature, moisture, pressure, deflection) Readers (mobile or fixed UHF), communications (Wireless IOT)

16. Wireless IOT Network What is it? - Open wireless Machine to Machine standard protocol (HW and SW) with aims : low cost (chip 10yr battery), widespread coverage, reliable, secure, supports large #items, low cost service, broadcast and small burst capabilities from 2.5 Kbps up to 16Mbps) - Uses “white space” spectrum (UHF TV) at low power. Approved by US FCC Covers (spec) interface from base station to backhaul network Can build network by using base station hopping also 16

17. 17 Some early tests Thinmagic Vega UHF Reader with 7.5 dBiC antenna (pc connected) Tags: Confidex Ironside metallic, ALN-9629 square inlay and Avery Dennison AD-824 First test in air approximately 12 ft (all passed) Second test in soil and concrete (construction site) at approximately 6 ft depth, reader at 3 ft above ground (all passed) Indicates strong support for use in proposed system Need to test further with variable angle of incidence, distances, power, multiple sensors, etc.

18. Decision Support System DSS automates data reduction and produces graphical displays of frost-thaw penetration and subsurface moisture conditions at remote sites Database stores and retrieves archived historical/current data -Historic data from 9 former test sites in NH and 3 in Maine -Current data from 2 demonstration test sites in Maine and 1 site in New Hampshire -Current data from 12 RWIS stations in NH (Plymouth State University, NH) 18

19. 19 Present DSS Graphical User Interface (GUI) http://ne-slr.umassd.edu/user/site/download?id=30 19

20. 20 SLR Predictive Model(s) Why used? - State DOTs do not have funds to instrument and monitor all roadways for frost/thaw depths - FWD or other in situ testing and analysis is costly and time consuming - Difficult to obtain subsurface temperature and/or FWD data in real- time - Truckers must be notified of SLR 3 to 5 days ahead of actual posting - Present DSS uses freeze/thaw index approach - Looking at other models for future enhancements

21. 21 Commercialization - States do not have resources to instrument, monitor and maintain all roadways - Let commercialization big data analytics trends take over - Applications will evolve if profit margin seen for using data in novel ways - Road users may be willing to pay for services that improve their operations and profits - IOT may be the avenue

22. 22 Project’s Status - Business Student Research Assistants have been Hired - Two Computer Science – DSS improvements - Four Electrical and Computer Engineering – system architecture, IOT network, data collection node, Sensor node design, implementation and testing - One Civil Engineering – SLR prediction model development Subcontract Frost Associates – Modeling efforts Initial COTS evaluation of sensor and reader components started DSS identified fixes implemented and others ongoing

23. 23 Problems Purchasing issues slowed hardware lab setup Subcontracting problems slowed effort to get Frost Associates involved Late start up date cased issues with getting all student Research Assistants hired for the semester - All in place for summer activities

24. 24 Next Quarter Plans System Architecture - Evaluate passive, battery assisted and active sensor tag technology options - Evaluate sensor tag reader technology options - Evaluate COTS IOT network concepts (base station architectures and performance parameters) - Define proposed integrated reader, processing, and network communication node architecture Initiate redesign of DSS using advisory committee and users feedback Initiate evaluation of forecasting model concepts

25. Benefits to the Transportation User Community Integrating low cost wireless RFID technology into roadways will support expansion of real-time data collection sites Enhance data and tools (visualization/models) provides improved traffic management capabilities for DOT SLR timing Expansion will provide critical quantitative data to eliminate or supplement components of current visual inspection procedures Result in enhanced capabilities in making SLR placement and removal decisions Improve the lifetime of roads under management Data can be made available to public (trucking firms) to better coordinate SLR activities 25

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