Naval Internet of Things (IoT) Effectiveness and Efficiency
Navy STTR 2018.A - Topic N18A-T027 ONR - Mr. Steve Sullivan - steven.sullivan@navy.mil Opens: January 8, 2018 - Closes: February 7, 2018 (8:00 PM ET)
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. 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. 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
|