N152-122       TITLE:  In-Transit Visibility Module for Lifts of Opportunity Program (LOOP) & Transportation Exploitation Tool (TET) 

TECHNOLOGY AREAS:  Information Systems

ACQUISITION PROGRAM:  NAVSUP Transportation Exploitation Tool is local prototype seeking to become a program of record.

OBJECTIVE:  Develop and demonstrate an In-Transit Visibility (ITV) module that will enhance Lifts of Opportunity (LOOP) planners' ability to accurately and in near-real-time monitor the transportation of critical end items, predict time of arrival and potential hazards to the mission, and provide decision support tools including mission performance metrics and automatically generated alerts if human intervention is required.

DESCRIPTION:  The United States Transportation Command (USTRANSCOM) plans and executes worldwide movement of cargo and people at sea, on land, and in the air, launching an average of 1,700 movements a day. Navy Fleet/Force transportation requests within USTRANSCOM are routed to specialists who focus on satisfying requirements using a mode of transportation with minimal coordination between them and their counterparts. To avoid the high cost for dedicated USTRANSCOM Special Assignment Airlift Mission (SAAM) or contracted commercial flights, the Navy developed and implemented a Transportation Exploitation Tool (TET) prototype. TET helps planners find cargo capacity on SAAMs or other conveyances that can support mission requirements resulting in significant cost avoidance for the urgent movement of cargo worldwide. Once a mission is booked, transportation planners and fleet forces require the ability to accurately track urgently needed cargo as it moves from its origin to its destination and through all transportation nodes, and then allow planners to close out the mission. The ITV of critical supplies throughout the movement will have several important benefits: 1) allows team to plan for material handling, and other special equipment and personnel needed to load the cargo at transportation nodes, 2) provides early identification of problems or delays during the mission that may necessitate re-planning, and 3) increased visibility helps ensure critical items are not needlessly re-ordered. Current state of the art for large scale DoD ITV systems use radio frequency identification (RFID) tags and a network of read/write stations (to include satellites). Systems like the Army's Joint-Automatic Identification Technology (J-AIT) have over 1,900 stations alone. These types of systems are costly and manpower intensive. The limitations the Navy has for manpower and funding requires an innovative solution for an ITV capability using data that is already available. The focus of the ITV module is threefold. First is development of software tools (Intelligent Agents (IAs) and semantic services) that can take disparate sources of data (real-time feeds, near-real-time feeds, manual entry, and historical references) and fuse them to accurately infer location data of transported items with high confidence. Second is development of additional decision support tools to aid planners. This includes automatic generation of alerts and tracking of mission performance metrics. Third and final is development of predictive models that will use the same data sources to anticipate arrival times of logistical items. The capability to predict arrival times (updated as the current location changes) of goods in finer granularity than current methodologies is necessary to facilitate planning. Using machine learning methodologies, the predictive models should be able to learn from previously executed missions to identify trends that support successful mission planning and execution. Challenges include development of a robust IA that can digest large quantities of data and mine pertinent information (specified and inferred) on specific items. Data may need to be semantically connected (for example, connection of the cargo ID to a strategic mission with its flight schedule and inflight tracking data) in order to derive relevant mission data (location, time to arrival, and probability of success for completing the next mission leg). The software tools need to be accurate, reliable, and able to run efficiently on handheld operating systems compatible with the Ozone Widget Framework (OWF). The existing TET system runs as a web service on the NIPRNET/SIPRNET (the Department of Navy's unclassified and classified internal computer networks). For this effort, the ITV module will initially attain static or live data feeds from existing TET services through an existing systems integration laboratory (SIL) environment (the government will ensure access to the SIL for the awarded companies) at The Pennsylvania State University (PSU) Applied Research Laboratory (ARL), independent of Department of Defense (DoD) networks but funded by the government. The SIL environment with virtual machines will allow experimentation and integration without the need for operational security and information assurance certification until the system is actually deployed. Message communications between TET and the ITV service is required; for example an alert of a missed transportation connection would be pushed back to TET to initiate dynamic re-planning of the mission. Examples of communication channels that need to interface with TET/ITV: Marine Corps' Tactical Service Oriented Architecture (TSOA), Naval Tactical Cloud (NTC). Examples of incoming data feeds provided via the SIL: IDE/GTN

Convergence (IGC), Global Decision Support System (GDSS), Federal Aviation Administration (FAA),

National ITV Server, Global Air Transportation Execution System (GATES), Weather, Coast Guard Automated Information System (AIS) or equivalent. Real time feeds will ultimately be pursued with support from the government. 

PHASE I:  Define and develop a concept and software architecture for an ITV module that can infer location of a logistical item using available real time feeds, near-real time feeds, and historical data. The ITV module architecture shall support communication with NAVSUP's Transportation Exploitation Tool (TET) to receive mission details, data feeds, and to transmit alerts or other messages back to TET. The performer will define decision support tools to capture critical metrics of current/historical mission performance. These tools require automatically generated alerts for situations that may hinder mission success and that prompt actions from planners. In addition, develop predictive models that provide real/near-real time updates of arrival times for logistical items. The performer will also define an open source widget based approach to enable mobile/handheld devices to interact with the ITV module. At the conclusion of Phase I, the performer should provide a viable path forward for the implementation of the concept ensuring coupling of communication with the TET tool. The small business shall deliver architecture views, describe the software's major functions, describe the user interface, outline data messaging functions, and describe the proposed software development process, schedule, risk, and cost.

PHASE II:  Develop and demonstrate a handheld ITV prototype based on Phase I efforts in a SIL environment. The software shall demonstrate all major functionality to include ITV and prediction of arrival of TET missions in execution, implementation of decision support tools (i.e. real-time alerts) , and collection of key performance metrics for use in future analytic models. This includes validating ability of the ITV module to locate an object for a lift of opportunity mission in execution with high confidence to accurately predict arrival times within a low margin of error, using only the data feeds provided to the performer through ONR and PSU ARL. The ability of the module to mine, digest, and derive object location, in the finest granularity possible, in a timely manner (within a few minutes) is necessary to ensure an appropriate planning capability. Alerts and other desired analytical and decision support aspects will also be demonstrated. Phase II will include a government evaluation by transportation planners at NAVSUP in Norfolk.

PHASE III:  Phase III will focus on the seamless integration of the ITV module with the TET in a cross domain NIPRNET/SIPRNET environment by transportation planners in Norfolk, VA. This includes refining and implementing enhancements to existing software functions and addition of functions that support transportation planning and ITV. The performer will work closely with NAVSUP and the program of record for the TET application to ensure that both TET and ITV components will work in an efficient and effective manner in a relevant environment during planning missions. This effort includes software verification and validation functions and completion of information assurance tasks necessary for deployment on NIPRNET/SIPRNET.

REFERENCES:  

1.   Transportation Expolitation Tool (TET). (n.d.). Retrieved December 9, 2014, from

http://www.onr.navy.mil/Media-Center/Press-Releases/2013/Transportation-Exploitation-Tool-LogisticsSoftware.aspx

2.   TSOA. (n.d.). Retrieved December 9, 2014, from

http://www.marines.mil/News/MarinesTV.aspx?videoid=195016

3.   OZONE Platform. (n.d.). Retrieved December 9, 2014, from http://www.ozoneplatform.org/

4.   IDE/GTN Convergence (IGC). (n.d.). Retrieved December 9, 2014, from http://www.dla.mil/informationoperations/pages/IGC.aspx

5.   Lifts of Opportunity (LOOP) Retrieved from

http://interactiondc.com/navsup/ourteam/navsupgls/prod_serv/transportation/Opportune%20Lift%20(OPLI FT)%20and%20Lifts%20of%20Opportunity%20Transportation%20Exploitation%20Tool.pdf

KEYWORDS:  In-Transit Visibility, Transportation Management Systems, Intelligent Agent, Predictive Models, Logistics, Demand Forecasting, Semantic, Decision Support

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