TECHNOLOGY AREA(S): Information Systems, Sensors

ACQUISITION PROGRAM: Maritime Tactical Command and Control, Distributed Common Ground Station � Navy (PMW 150 and 120)

OBJECTIVE: Objective is to develop and test Internet of Things (IoT) concepts in relevant environments.� The performer will prototype an agent-based framework populated by smart objects and Artificial Intelligence (AI)-controlled force units; and demonstrate its effectiveness and efficiency.

DESCRIPTION: The goal of the topic is to prototype an agent-based framework populated by agent-controlled units and smart objects including sensors and logistics assets.� As part of development, the performer will evaluate an implementation of the above with a military simulation (e.g., JSAF, VBS3, etc.) of their choice.� Progress will be tracked by computing the ratio of a set of measures of performance (simulation outcomes) divided by the number of bits sent in-between and between objects (sensors, weapons, and logistics support assets) and units (individual warfighters and/or platforms to three at-sea platforms or three land-based companies).� The offeror should utilize multiple scenarios to prove the utility of their Phase I research.� All messages count, including object/unit discovery.� Assumptions made concerning the abilities of smart sensors need to be justified in literature (e.g., a small Unmanned Aircraft Systems (UAS) should not be allowed to send specific target confirmation messages from 10 miles away).� During Phase II, the offeror will work towards demonstrating with real things during an operational exercise.� Phase III will focus on transitioning the validated architecture and whatever part of the agent-based framework populated by smart objects is not currently fielded.� Transition should be accomplished through redesign of existing platform and sensor systems, for example, to make them intelligent, enabled by the use of efficient communication protocols.

Intelligent things are made possible by technology advances in four areas: 1) inexpensive sensors and actuators, 2) growth in wireless networks and addresses (IPv6), 3) gains in computing power and storage, and 4) advanced analytic methods including machine learning.� IoT devices are used for commercial applications such as home security, healthcare devices, factory production, tracking cargo, autonomous vehicles, electrical grids, etc.� Problems remain in standardization, security, and privacy [1].� Understanding how to move the technology to a military setting where bandwidth is more challenged requires development.� The topic will focus on information technology to support operations in tactical settings by increasing the numbers of smart things that are capable of knowing how, when and why to communicate with other things.

Future smart platforms and sensors will be networked, exchange data as needed, and act as an integrated system.� Operators will be removed from being �in the loop� and reside �on the loop� where they oversee and manage systems.� The system itself will be able to control operating parameters to provide self-awareness, self-prediction, self-comparison, self-reconfiguration, and self-maintenance [2].� New methods are required for measuring effectiveness of these agile systems in defense and public safety domains.� Military applications include personnel sensing, situational awareness, targeting, autonomous systems, logistics, and facilities management [3].

Proposers should develop an IoT system as a cloud system with central and edge computing or as a deployable system with Wireless Sensor Network [5, 6].� Innovative science and technology (S&T) should advance the state-of-the-art in the following areas: 1) Data-driven applications or embedded automation and intelligent adaptive systems, 2) Data handling by intelligent things with adaptive workflows for mission tasking needs, 3) Operator means to selectively oversee and delegate control of system components, and 4) Methods to evaluate system effectiveness and resiliency.

Work produced in Phase II may become classified.� Note: The prospective contractor(s) must be U.S. Owned and Operated with no Foreign Influence as defined by DOD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been be implemented and approved by the Defense Security Service (DSS).� The selected contractor and/or subcontractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances, in order to perform on advanced phases of this contract as set forth by DSS and ONR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement.� The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advance phases of this contract.

PHASE I: Study possible simulations using multiple scenarios with differing measures of effectiveness, instrumented in a way that measures communication volume between things.� Document smart capabilities given to sensors, platforms, and weapons plus the logic used by things to decide why/when/how to communicate.� Identify metrics to validate performance of analytic processes with the goal of reducing technical risk associated with building a working prototype, should work progress.� Performers should produce Phase II plans with a technology roadmap and milestones.

PHASE II: Develop a prototype and perform a field demonstration of the prototype, which may take place in concert with an operational experiment.� In Phase II, the small business may be given access by the Government to subject matter expertise to help validate information sharing logic.� The offeror should assume that the prototype system will need to run as an application in cloud architecture or World Server Network (WSN) of a large number of nodes and have matured a design for a responsive human computer interface.� Phase II deliverables will include a working prototype of the system, software documentation including a user�s manual, and a demonstration.

It is probable that the work under this effort will be classified under Phase II (see Description section for details).

PHASE III DUAL USE APPLICATIONS: Phase III will focus on transitioning the validated architecture and whatever part of the agent-based framework populated by smart objects is not currently fielded.� The final system design must be capable of deployment.� The system should be adapted to transition as part to a larger system or as standalone commercial product.� Commercial interest should be great as the ever-connected world remains power- and bandwidth-constrained.� The Phase III system should have an intuitive human computer interface, providing operator engagement but not overload.� The software and hardware should be modified and documented in accordance with guidelines provided by market plan or transition customer.

REFERENCES:

1. Abdulrahman, Y. A. et al. �Internet of Things: Issues and Challenges.� Procedia CIRP 2016, 16:3�8. https://scholar.google.com/scholar?q=Internet+of+Things%3A+Issues+and+Challenges+Abdulrahman+procedia&btnG=&hl=en&as_sdt=0%2C47&as_vis=1

2. Lee, J, Kao, H-A, and Yang, S. �Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment.� J. Theoretical and Applied Info Tech, 2014, V94, No1 E-ISSN 1817-3195. http://www.sciencedirect.com/science/article/pii/S2212827114000857

3. Fraga-Lamas, P., et al.� �A Review on Internet of Things for Defense and Public Safety.� Sensors 2016, 16, 1644; doi: 10.3390/s16101644. http://www.mdpi.com/1424-8220/16/10/1644/htm

4. Palmer, D., et al. �Defense Systems and IoT: Security Issues in an Era of Distributed Command and Control.� GLSVLSI 2016 Proceedings of the 26th edition on Great Lakes Symposium on VLSI. http://dl.acm.org/citation.cfm?id=2903038

5. �The Cisco Edge Analytics Fabric System.� Cisco whitepaper (2016). http://www.cisco.com/c/dam/en/us/products/collateral/analytics-automation-software/edge-analytics-fabric/eaf-whitepaper.pdf

6. Oteafy, S. M. A. and Hassanein, H. S. �Resilient IoT Architectures Over Dynamic Sensor Networks with Adaptive Components.� IEEE Internet of Things J., 2017, 4, 2 doi: 10.1109/JIOT.2016.2621998. http://ieeexplore.ieee.org/document/7707340/

KEYWORDS: Internet of Things; Cloud Computing; Data Science, Embedded Processing; Communication Protocols; Artificial Intelligence