RP-SMARF: A Cloud-Based Platform for Research Collaboration on Smart Facilities Management

1. TEMPLATEDESIGN© 2008
www.PosterPresentations.com
[1] Bridge monitoring using wireless smart sensors, http://spie.org/x84931.xml, Accessed, 04 2015
[2] The COMPACS® computer monitoring system for machinery health control and accidents prevention
http://www.dynamicsru.com/products/compacs-m/ , Accessed, 04 2015
[3] UNLV’s Environmentally Friendly Science and Engineering Building is Monitored for Earthquake Shaking,
http://earthquake.usgs.gov/monitoring/buildings/unlv.php , Accessed, 04 2015
[4] A McGregor, D. Bennett, S. Majumdar, B. Nandy, J.O. Melendez, M. St-Hilaire, D. Lau and J. Liu; “A
Cloud-Based Platform for Supporting Research Collaboration”, in proc. of 8th IEEE International Conference
on Cloud Computing, New York City, 06 2015
[5] D. Lau, J. Liu, S. Majumdar, B. Nandy, M. St-Hilaire and C.S. Yang, "A Cloud-Based Approach for Smart
Facilities Management", in proc. of 3rd Annual Conference on Prognostics and Health Management (IEEE
PHM 2013), pp. 1-8, Gaithersburg, Maryland, 06 2013.
RP-SMARF: A Cloud-Based Platform for Research Collaboration on Smart
Facilities Management
Smart Facilities Management allow sensor-based
devices/structures to be continuously monitored
and managed
The Research Platform for Smart Facilities
Management (RP-SMARF) is a cloud-based
platform to improve collaboration between
researchers of smart facilities management
techniques
RP-SMARF offers communities of researchers and
industry practitioners:
Access to cutting edge software tools created by
researchers
Access to geographically dispersed computing and
storage resources, data sets and tools
Greatly simplified tool maintenance and support for
the software creators, along with intellectual property
(IP) protection
Fine grained access controls to ensure only the
appropriate users have access to sensitive data and
technology
Introduction 1 Problems in Smart Facilities Management 4
Managing a Smart Facility 3
End-User Interface 7
Conclusions 9
Initial Domains 2
Smart facilities management can be applied in
various domains such as:
Smart Bridges
Smart Machines
Smart Buildings
The research domains use sensors for capturing
metrics
These metrics aid in making informed decisions
about the structural health of the facility, as well as the
maintenance and management of the infrastructure
3
3
6
Sample Use Cases 8
Acknowledgement
10
A. McGregor†, D. Bennett‡, S. Majumdar*, B. Nandy§, J.O. Melendezǂ, M. St-Hilaireǂ, D. Lauǂ, J. Liuǂ,
A. Biswasǂ, N. Limǂ, A. Tehranianǂ, K. Zhuangǂ , L. Davidsonǂ
ǂ†*Carleton University, Ottawa, Canada
‡§Solana Networks, Ottawa, Canada
email: †andrewmcgregor@sce.carleton.ca, §bnandy@solananetworks.com, *majumdar@sce.carleton.ca
Smart
Bridge
Smart
Machine
Smart Building
Data may be analyzed in real-time using:
 Streaming data in real-time
 Interactive GUI
 Real-time analytics
Historical data may be processed to analyze
specific circumstances or to determine the effects of
operating the facility over time
 Metadata based search
 Bulk data transfer and analytics
 Analysis tools for historical data
Monitor Analyze Decide
Real-time Historic
Metadata
Extraction
Search
The RP-SMARF architecture is based on a “control
server” that maintains a database of accessible
resources and permissions
The RP-SMARF remote agent provides two
services:
A job running service allows the control server to
interact with the remote agent to start and stop jobs
 A file system service on the remote agent is used by
the control server to allow end-user interaction with
the files accessible via the remote agent
The Guacamole Server provides a web server
which allows interactive GUI-based access to tools
which have a GUI
Browser
Control Server
Domain-
Specific VMs
Public Cloud
Institution X
Remote
Agent
Guacamole
Server
Firewall
Domain-
Specific
Computer
Domain-
Specific
File
Server
Institution Y
Remote
Agent
Guacamole
Server
Domain-
Specific
File
Server
Firewall
Remote
Agent
SFTP
SFTPSSH
VNC/RDP
HTTP
HTTP
SSH
ICE
Domains are becoming data-driven: data needs to
be shared, searched and analyzed
Software is becoming easier to create but remains
hard to manage, distribute and support on remote
systems
Managing IP of the tool is hard: control may be lost
once a tool is distributed
Key Features of RP-SMARF 5
Simplified Tool Usage: Accessing a GUI to use any
tool with any dataset
Multi-Tenancy: Access to multiple research
communities with fine-grained access control
Unification of heterogeneous resources:
Virtual machines on a public cloud
Dedicated computers
Databases and file servers
Software tools
Automatic data movement: copy data to allow tools
to have access
Tool and dataset discovery
Metadata searching: Allowing effective searching of
dataset
Processing real-time data streams
Ability to easily add and remove resources from the
platform
RP-SMARF Architecture 6
Within each site
that is providing
resources, there is
a “remote agent”
that provides
access to storage
and computing
resources behind
the firewall
Instrumented Bridge:
Collaboration between a bridge operator that collects
bridge data and a remote researcher who uses a
tool running at Carleton University to analyze the
data
Data transfer and invocation of processing tool are
done through RP-SMARF
Smart Machinery:
Analysis of bearing data for Auxiliary Power Units
 Data is transferred by using the facilities provided
by RP-SMARF to the Carleton server hosting the
tool
Discover
Run Tool
View output
Modern, browser-based GUI with REST API
Common UI to access all tools and datasets
RP-SMARF unifies heterogeneous geographically
dispersed resources
RP-SMARF provides a bridge between the software
written by researchers and the outside world
RP-SMARF makes it practical for a single
researcher to make their software and datasets
available to other collaborators without needing
expertise in areas outside their domain
We are grateful to CANARIE for providing the financial
support for this project
Bearing Fault Analysis Output
Bridge Vibration
Animation
11
References 10
Access to data within an
institution is performed via
SFTP or via the native file
system of the remote agent
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