Underground Infrastructure Sensing and Mapping - Revision history

Pinfold at 06:18, January 25, 2023

2023-01-25T06:18:19Z

← Older revision		Revision as of 06:18, January 25, 2023
Line 10:		Line 10:
	* Information processing challenges to convert sensor data into database of subsurface mapping and condition.		* Information processing challenges to convert sensor data into database of subsurface mapping and condition.
	* Communication, management and interoperability – multiple utilities, some span neighboring municipalities: water, sewer (sanitary and stormwater), electric, gas, and telecommunications ; have different features, protocols and management issues.		* Communication, management and interoperability – multiple utilities, some span neighboring municipalities: water, sewer (sanitary and stormwater), electric, gas, and telecommunications ; have different features, protocols and management issues.
			\|solutions=Digital Twin
	\|requirements=# Develop map of underground utilities using ground penetrating radar, pipe robot telemetry, new construction observations and historical records; using combination of constructive, pattern recognition and data fusion methods.		\|requirements=# Develop map of underground utilities using ground penetrating radar, pipe robot telemetry, new construction observations and historical records; using combination of constructive, pattern recognition and data fusion methods.
	# Place condition and operation sensors into underground infrastructure at key locations.		# Place condition and operation sensors into underground infrastructure at key locations.
Line 38:		Line 39:
	# System performance assessment.		# System performance assessment.
	# Study of scalability.		# Study of scalability.
			\|chapter=Digital Twins
	\|supercluster=Utility		\|supercluster=Utility
	\|year=2016, 2017		\|year=2016, 2017

Pinfold at 06:43, May 17, 2022

2022-05-17T06:43:29Z

← Older revision		Revision as of 06:43, May 17, 2022
Line 1:		Line 1:
	{{ActionCluster		{{ActionCluster
	\|image=Mapping Underground Infrastructure.jpeg		\|image=Mapping Underground Infrastructure.jpeg
	\|team=BTV Ignite, Kardinal Microsystems, University of Vermont~~; City of Winooski, VT~~		\|team=BTV Ignite, Kardinal Microsystems, University of Vermont
	\|leader=Dryver Huston, Tian Xia		\|leader=Dryver Huston, Tian Xia
	\|imagecaption=Mapping Underground Infrastructure		\|imagecaption=Mapping Underground Infrastructure

Pinfold at 06:43, May 17, 2022

2022-05-17T06:43:02Z

← Older revision		Revision as of 06:43, May 17, 2022
Line 5:		Line 5:
	\|imagecaption=Mapping Underground Infrastructure		\|imagecaption=Mapping Underground Infrastructure
	\|municipalities=Winooski VT		\|municipalities=Winooski VT
			\|status=Development
	\|description=Use sensing and information technology to determine the state of infrastructure and provide it in an appropriate, timely and secure format for the managers, planners and users. Information processing techniques convert the data in information-laden databases for use in analytics, graphical presentations, metering and planning.		\|description=Use sensing and information technology to determine the state of infrastructure and provide it in an appropriate, timely and secure format for the managers, planners and users. Information processing techniques convert the data in information-laden databases for use in analytics, graphical presentations, metering and planning.
	\|challenges=* Technical challenges for sensor selection, design, operation and use. Subsurface congestion and unknown features are complications.		\|challenges=* Technical challenges for sensor selection, design, operation and use. Subsurface congestion and unknown features are complications.

Pinfold at 06:42, May 17, 2022

2022-05-17T06:42:16Z

← Older revision		Revision as of 06:42, May 17, 2022
Line 2:		Line 2:
	\|image=Mapping Underground Infrastructure.jpeg		\|image=Mapping Underground Infrastructure.jpeg
	\|team=BTV Ignite, Kardinal Microsystems, University of Vermont; City of Winooski, VT		\|team=BTV Ignite, Kardinal Microsystems, University of Vermont; City of Winooski, VT
	\|leader=Dryver Huston		\|leader=Dryver Huston, Tian Xia
	\|imagecaption=Mapping Underground Infrastructure		\|imagecaption=Mapping Underground Infrastructure
	\|municipalities=Winooski VT		\|municipalities=Winooski VT

Pinfold at 06:34, May 17, 2022

2022-05-17T06:34:39Z

← Older revision		Revision as of 06:34, May 17, 2022
Line 1:		Line 1:
	{{ActionCluster		{{ActionCluster
			\|image=Mapping Underground Infrastructure.jpeg
	\| ~~title~~ = Underground Infrastructure ~~Sensing and Mapping for Smart Maintenance, Sustainability, Usage and Resilience~~		\|team=BTV Ignite, Kardinal Microsystems, University of Vermont; City of Winooski, VT
	\| team = BTV Ignite, Kardinal Microsystems, University of Vermont; City of Winooski, VT		\|leader=Dryver Huston
			\|imagecaption=Mapping Underground Infrastructure
	\| leader = Dryver Huston		\|municipalities=Winooski VT
	~~\| email = dryver.huston@uvm.edu~~		\|description=Use sensing and information technology to determine the state of infrastructure and provide it in an appropriate, timely and secure format for the managers, planners and users. Information processing techniques convert the data in information-laden databases for use in analytics, graphical presentations, metering and planning.
	~~<!-- [mailto:txia@uvm.edu Tian Xia]-->~~		\|challenges=* Technical challenges for sensor selection, design, operation and use. Subsurface congestion and unknown features are complications.

	~~\| image = Mapping Underground Infrastructure.jpeg~~
	\| imagecaption = Mapping Underground Infrastructure
	\| municipalities = Winooski, VT
	~~\| status =~~
	~~\| website =~~
	~~\| download =~~

	\| description =
	Use sensing and information technology to determine the state of infrastructure and provide it in an appropriate, timely and secure format for the managers, planners and users. Information processing techniques convert the data in information-laden databases for use in analytics, graphical presentations, metering and planning.


	\| challenges =
	* Technical challenges for sensor selection, design, operation and use. Subsurface congestion and unknown features are complications.
	* Information processing challenges to convert sensor data into database of subsurface mapping and condition.		* Information processing challenges to convert sensor data into database of subsurface mapping and condition.
	* Communication, management and interoperability – multiple utilities, some span neighboring municipalities: water, sewer (sanitary and stormwater), electric, gas, and telecommunications ; have different features, protocols and management issues.		* Communication, management and interoperability – multiple utilities, some span neighboring municipalities: water, sewer (sanitary and stormwater), electric, gas, and telecommunications ; have different features, protocols and management issues.
			\|requirements=# Develop map of underground utilities using ground penetrating radar, pipe robot telemetry, new construction observations and historical records; using combination of constructive, pattern recognition and data fusion methods.

	~~\| solutions =~~

	\| requirements =
	# Develop map of underground utilities using ground penetrating radar, pipe robot telemetry, new construction observations and historical records; using combination of constructive, pattern recognition and data fusion methods.
	# Place condition and operation sensors into underground infrastructure at key locations.		# Place condition and operation sensors into underground infrastructure at key locations.
	# Use fiber optic high-speed telecommunications network to transmit data.		# Use fiber optic high-speed telecommunications network to transmit data.
	# Create Underground Infrastructure Information Model database for use in infrastructure management and planning.		# Create Underground Infrastructure Information Model database for use in infrastructure management and planning.
	# Integrate cybersecurity measures into design decisions.		# Integrate cybersecurity measures into design decisions.
			\|kpi=* Emergency repair reduction of 20%
	\| kpi =
	* Emergency repair reduction of 20%
	* Service outage reduction of 20%		* Service outage reduction of 20%
	* Inappropriate sanitary and storm water sewage discharge reduction of 20%		* Inappropriate sanitary and storm water sewage discharge reduction of 20%
			\|measurement=Billing records, service records, and sewer sensing
			\|standards=* The sensing systems, data streams, and databases can all easily conform to existing and emerging standards.

	\| measurement =
	Billing records, service records, and sewer sensing


	\| standards =
	* The sensing systems, data streams, and databases can all easily conform to existing and emerging standards.
	* The initial deployment is in a small city that is big enough to capture many of the pertinent issues, yet small enough to allow degrees of freedom for easy deployment. Conceptual and technical development then easily scales to bigger cities.		* The initial deployment is in a small city that is big enough to capture many of the pertinent issues, yet small enough to allow degrees of freedom for easy deployment. Conceptual and technical development then easily scales to bigger cities.
			\|cybersecurity=TBD
	\| cybersecurity =		\|impacts=# Overall more efficient and resilient subsurface infrastructure

	\| impacts =
	# Overall more efficient and resilient subsurface infrastructure
	# Reduced service outages and emergency repairs		# Reduced service outages and emergency repairs
	# Better planning tools		# Better planning tools
	# Reduced environmental impacts – energy use, and stormwater and sewage discharge.		# Reduced environmental impacts – energy use, and stormwater and sewage discharge.
	# Quicker construction cycles.		# Quicker construction cycles.
			\|demonstration=* Phase I Pilot/Demonstration:
	\| demonstration =

	* Phase I Pilot/Demonstration:
	GPR measurement and integration of historical records to construct UIIM database for one or two city blocks		GPR measurement and integration of historical records to construct UIIM database for one or two city blocks

Line 71:		Line 37:
	# System performance assessment.		# System performance assessment.
	# Study of scalability.		# Study of scalability.
			\|supercluster=Utility
			\|year=2016, 2017
			\|title=Underground Infrastructure Sensing and Mapping for Smart Maintenance, Sustainability, Usage and Resilience
	\| supercluster = Utility		\|email=dryver.huston@uvm.edu
	\| year = 2017		<!-- [mailto:txia@uvm.edu Tian Xia]-->

	}}		}}

	~~[[Category:Year_2016]]~~

Pinfold at 07:30, November 12, 2021

2021-11-12T07:30:59Z

← Older revision		Revision as of 07:30, November 12, 2021
Line 8:		Line 8:
	<!-- [mailto:txia@uvm.edu Tian Xia]-->		<!-- [mailto:txia@uvm.edu Tian Xia]-->

	\| image =		\| image = Mapping Underground Infrastructure.jpeg
	\| imagecaption =		\| imagecaption = Mapping Underground Infrastructure
	\| municipalities = Winooski, VT		\| municipalities = Winooski, VT
	\| status =		\| status =

Pinfold: 1 revision imported

2021-10-31T20:45:41Z

1 revision imported

← Older revision		Revision as of 20:45, October 31, 2021
(No difference)

en>Ocadmin at 05:18, March 11, 2020

2020-03-11T05:18:20Z

New page

{{ActionCluster

| title = Underground Infrastructure Sensing and Mapping for Smart Maintenance, Sustainability, Usage and Resilience
| team = BTV Ignite, Kardinal Microsystems, University of Vermont; City of Winooski, VT

| leader = Dryver Huston
| email = dryver.huston@uvm.edu


| image =
| imagecaption =
| municipalities = Winooski, VT
| status =
| website =
| download =

| description =
Use sensing and information technology to determine the state of infrastructure and provide it in an appropriate, timely and secure format for the managers, planners and users. Information processing techniques convert the data in information-laden databases for use in analytics, graphical presentations, metering and planning.

| challenges =
* Technical challenges for sensor selection, design, operation and use. Subsurface congestion and unknown features are complications.
* Information processing challenges to convert sensor data into database of subsurface mapping and condition.
* Communication, management and interoperability – multiple utilities, some span neighboring municipalities: water, sewer (sanitary and stormwater), electric, gas, and telecommunications ; have different features, protocols and management issues.

| solutions =

| requirements =
# Develop map of underground utilities using ground penetrating radar, pipe robot telemetry, new construction observations and historical records; using combination of constructive, pattern recognition and data fusion methods.
# Place condition and operation sensors into underground infrastructure at key locations.
# Use fiber optic high-speed telecommunications network to transmit data.
# Create Underground Infrastructure Information Model database for use in infrastructure management and planning.
# Integrate cybersecurity measures into design decisions.

| kpi =
* Emergency repair reduction of 20%
* Service outage reduction of 20%
* Inappropriate sanitary and storm water sewage discharge reduction of 20%

| measurement =
Billing records, service records, and sewer sensing

| standards =
* The sensing systems, data streams, and databases can all easily conform to existing and emerging standards.
* The initial deployment is in a small city that is big enough to capture many of the pertinent issues, yet small enough to allow degrees of freedom for easy deployment. Conceptual and technical development then easily scales to bigger cities.

| cybersecurity =

| impacts =
# Overall more efficient and resilient subsurface infrastructure
# Reduced service outages and emergency repairs
# Better planning tools
# Reduced environmental impacts – energy use, and stormwater and sewage discharge.
# Quicker construction cycles.

| demonstration =

* Phase I Pilot/Demonstration:
GPR measurement and integration of historical records to construct UIIM database for one or two city blocks

* Phase II Deployment:
# Selection of best deployment sites.
# Construct database using tomographic GPR, construction and historic records.
# Integration of sensors into telecommunications (fiber optic) system.
# Database usage and demonstration, including mobile apps.
# Cybersecurity integration.
# System performance assessment.
# Study of scalability.

| supercluster = Utility
| year = 2017

}}

[[Category:Year_2016]]