Video Analytics for Orlando Public Safety - Revision history

Pinfold at 06:32, January 25, 2023

2023-01-25T06:32:11Z

← Older revision		Revision as of 06:32, January 25, 2023
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	* Community acceptance to be replicated across the United States to engage the community to tie in medical resources.		* Community acceptance to be replicated across the United States to engage the community to tie in medical resources.
	\|demonstration=Real-time working application tied into city dispatch systems at city-wide scale, supporting over 50% of the city. Demonstration will include a simulated emergency event and the measurement of response time with and without the proposed solution.		\|demonstration=Real-time working application tied into city dispatch systems at city-wide scale, supporting over 50% of the city. Demonstration will include a simulated emergency event and the measurement of response time with and without the proposed solution.
			\|chapter=Emergency Support Functions
	\|supercluster=Public Safety		\|supercluster=Public Safety
	\|year=2017		\|year=2017
	\|title=Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness		\|title=Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness
	}}		}}

Pinfold at 00:29, April 21, 2022

2022-04-21T00:29:41Z

← Older revision		Revision as of 00:29, April 21, 2022
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	{{ActionCluster		{{ActionCluster
	\| ~~title~~ = ~~Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness~~		\|image=IRISroom2.jpg
	\| team = Harris ~~Corporation~~, University of Central Florida College of Engineering, Amazon		\|team=Harris, University of Central Florida College of Engineering, Amazon
	\| leader = Charles Ramdatt, Sheldon Drobot		\|leader=Charles Ramdatt, Sheldon Drobot
	~~\| image = IRISroom2.jpg~~		\|imagecaption=Orlando Public Safety
	\| imagecaption = Orlando Public Safety		\|municipalities=Orlando FL<!-- ; Lynx Public Transit; Central Florida Expressway Authority; Florida Department of Transportation District V -->
	\| municipalities = Orlando FL		\|status=Ready for Public Announcement
	<!-- ; Lynx Public Transit; Central Florida Expressway Authority; Florida Department of Transportation District V -->		\|description=The project will create connected, city-wide mobile resources and systems to help improve the responses to a variety of challenges within the City of Orlando. Orlando is central city of 275,000 people, in an urban area of 2.4 million citizens, but with 68+ million visitors per year and the largest rental car market in the world. Thus, Orlando has some unique challenges with public safety and traffic. This project will meet the needs of several city departments and external agencies by ensuring cross-cutting and robust situational awareness for a variety of scenarios. It will allow for optimized deployments and expedited responses from police, fire fighters, emergency medical services, public works staff, transportation staff, special event managers, and external agencies which are obligated to provide mutual aid.
	\| status = Ready for Public Announcement		\|challenges=Various city and external agency managers need tools to vastly improve situational awareness for several challenges in different scenarios, each of which requires quick response and seamless collaboration.
	~~\| website =~~		\|solutions=* Quick understanding of the scale and nature of challenges will allow the deployment of the appropriate resources and allow for the understanding of the mitigating measures that are to be employed.
	~~\| download =~~

	\| description =
	The project will create connected, city-wide mobile resources and systems to help improve the responses to a variety of challenges within the City of Orlando. Orlando is central city of 275,000 people, in an urban area of 2.4 million citizens, but with 68+ million visitors per year and the largest rental car market in the world. Thus, Orlando has some unique challenges with public safety and traffic. This project will meet the needs of several city departments and external agencies by ensuring cross-cutting and robust situational awareness for a variety of scenarios. It will allow for optimized deployments and expedited responses from police, fire fighters, emergency medical services, public works staff, transportation staff, special event managers, and external agencies which are obligated to provide mutual aid.

	\| challenges =
	Various city and external agency managers need tools to vastly improve situational awareness for several challenges in different scenarios, each of which requires quick response and seamless collaboration.

	\| solutions =
	* Quick understanding of the scale and nature of challenges will allow the deployment of the appropriate resources and allow for the understanding of the mitigating measures that are to be employed.
	* Response times are critical. The project will integrate computer aided dispatch (CAD) and automated vehicle location (AVL) systems, and implement systems in dispatch and training dispatchers to reduce the ambulance response time. The system will be integrated into GIS positioning system to locate individuals in need based on location.		* Response times are critical. The project will integrate computer aided dispatch (CAD) and automated vehicle location (AVL) systems, and implement systems in dispatch and training dispatchers to reduce the ambulance response time. The system will be integrated into GIS positioning system to locate individuals in need based on location.
	* Several different camera systems are currently available. However, they are not integrated and no software based analytics are currently employed to interpret the numerous feeds on an expedited and simultaneous basis.		* Several different camera systems are currently available. However, they are not integrated and no software based analytics are currently employed to interpret the numerous feeds on an expedited and simultaneous basis.
			\|requirements=* Articulate the project vision to gain stakeholder support and buy-in from the community
	\| requirements =
	* Articulate the project vision to gain stakeholder support and buy-in from the community
	* Develop and assemble project team & stakeholder team		* Develop and assemble project team & stakeholder team
	* Review the individual and overlapping challenges faced by the team		* Review the individual and overlapping challenges faced by the team
Line 34:		Line 22:
	* With lessons learned from the pilot, ensure a phased plan for enabling activity centers, major arterial roadway corridors, places of public interest, and then all neighborhoods across the city.		* With lessons learned from the pilot, ensure a phased plan for enabling activity centers, major arterial roadway corridors, places of public interest, and then all neighborhoods across the city.
	* Ensure a program of independent evaluation of performance		* Ensure a program of independent evaluation of performance
			\|kpi=* Minimum 10% average response time of emergency medical teams
	\| kpi =
	* Minimum 10% average response time of emergency medical teams
	* Minimum 25% average time to clear traffic incidents due to non-life threatening events		* Minimum 25% average time to clear traffic incidents due to non-life threatening events
	* Minimum 25% average arrival time for public works crews to commence clearing of impassable roads		* Minimum 25% average arrival time for public works crews to commence clearing of impassable roads
			\|measurement=* Measurement of response time in minutes over 3-6 month period, compared to baseline
	\| measurement =
	* Measurement of response time in minutes over 3-6 month period, compared to baseline
	* Times to documented by 311, 911, Traffic Management Center, and Emergency Operations Center Staff.		* Times to documented by 311, 911, Traffic Management Center, and Emergency Operations Center Staff.
	* Times to be compared to video documentation of incident detection and responder arrival on scene		* Times to be compared to video documentation of incident detection and responder arrival on scene
			\|standards=* Requires interoperable GPS, AVL and CAD interfaces.
	\| standards =
	* Requires interoperable GPS, AVL and CAD interfaces.
	* Establishes standardized procedures for rapid response services.		* Establishes standardized procedures for rapid response services.
	* Establishes standardized methods for AI-based warning services		* Establishes standardized methods for AI-based warning services
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	* Standardized processes are not unique to city or region and can be replicated and scaled up in multiple cities/communities. The solution is planned to be replicated in other cities in the USA, Europe, and Africa.		* Standardized processes are not unique to city or region and can be replicated and scaled up in multiple cities/communities. The solution is planned to be replicated in other cities in the USA, Europe, and Africa.
	* The system will have its own business model to create sustainable revenue stream.		* The system will have its own business model to create sustainable revenue stream.
			\|cybersecurity=TBD
	\| cybersecurity =		\|impacts=* Reduction of existing ambulance response time

	\| impacts =
	* Reduction of existing ambulance response time
	* Improving quality of lives		* Improving quality of lives
	* Community acceptance to be replicated across the United States to engage the community to tie in medical resources.		* Community acceptance to be replicated across the United States to engage the community to tie in medical resources.
			\|demonstration=Real-time working application tied into city dispatch systems at city-wide scale, supporting over 50% of the city. Demonstration will include a simulated emergency event and the measurement of response time with and without the proposed solution.
	\| demonstration =		\|supercluster=Public Safety
	Real-time working application tied into city dispatch systems at city-wide scale, supporting over 50% of the city. Demonstration will include a simulated emergency event and the measurement of response time with and without the proposed solution.		\|year=2017
			\|title=Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness
	\| supercluster = Public Safety
	\| year = 2017

	}}		}}

Pinfold at 20:55, March 13, 2022

2022-03-13T20:55:03Z

← Older revision		Revision as of 20:55, March 13, 2022
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	{{ActionCluster		{{ActionCluster

	\| title = Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness		\| title = Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness

	\| team = Harris Corporation, University of Central Florida College of Engineering, Amazon		\| team = Harris Corporation, University of Central Florida College of Engineering, Amazon
			\| leader = Charles Ramdatt, Sheldon Drobot
	\| leader = Charles Ramdatt, ~~Director of Smart Cities & Special Projects, City of Orlando Florida~~
	~~\| email = Charles.ramdatt@cityoforlando.net~~
	~~<!-- [mailto:SDROBOT@harris.com~~ Sheldon Drobot~~]-->~~
	\| image = IRISroom2.jpg		\| image = IRISroom2.jpg
	\| imagecaption = Orlando Public Safety		\| imagecaption = Orlando Public Safety

Pinfold at 01:35, February 13, 2022

2022-02-13T01:35:41Z

← Older revision		Revision as of 01:35, February 13, 2022
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	\| title = Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness		\| title = Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness

	\| team = Harris Corporation, University of Central Florida College of Engineering, Amazon ~~Web Services~~		\| team = Harris Corporation, University of Central Florida College of Engineering, Amazon

	\| leader = Charles Ramdatt, Director of Smart Cities & Special Projects, City of Orlando Florida		\| leader = Charles Ramdatt, Director of Smart Cities & Special Projects, City of Orlando Florida

Pinfold at 06:28, January 11, 2022

2022-01-11T06:28:19Z

← Older revision		Revision as of 06:28, January 11, 2022
Line 5:		Line 5:
	\| team = Harris Corporation, University of Central Florida College of Engineering, Amazon Web Services		\| team = Harris Corporation, University of Central Florida College of Engineering, Amazon Web Services

	\| leader = Charles Ramdatt, Director of Smart Cities & Special Projects, City of Orlando, Florida		\| leader = Charles Ramdatt, Director of Smart Cities & Special Projects, City of Orlando Florida
	\| email = Charles.ramdatt@cityoforlando.net		\| email = Charles.ramdatt@cityoforlando.net
	<!-- [mailto:SDROBOT@harris.com Sheldon Drobot]-->		<!-- [mailto:SDROBOT@harris.com Sheldon Drobot]-->

Pinfold at 06:28, January 11, 2022

2022-01-11T06:28:01Z

← Older revision		Revision as of 06:28, January 11, 2022
Line 10:		Line 10:
	\| image = IRISroom2.jpg		\| image = IRISroom2.jpg
	\| imagecaption = Orlando Public Safety		\| imagecaption = Orlando Public Safety
	\| municipalities = Orlando, FL		\| municipalities = Orlando FL
	<!-- ; Lynx Public Transit; Central Florida Expressway Authority; Florida Department of Transportation District V -->		<!-- ; Lynx Public Transit; Central Florida Expressway Authority; Florida Department of Transportation District V -->
	\| status = Ready for Public Announcement		\| status = Ready for Public Announcement

Pinfold at 06:27, January 11, 2022

2022-01-11T06:27:43Z

← Older revision		Revision as of 06:27, January 11, 2022
Line 3:		Line 3:
	\| title = Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness		\| title = Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness

	\| team = Harris Corporation; University of Central Florida College of Engineering~~; ;~~ Amazon Web Services		\| team = Harris Corporation, University of Central Florida College of Engineering, Amazon Web Services

	\| leader = Charles Ramdatt, Director of Smart Cities & Special Projects, City of Orlando, Florida		\| leader = Charles Ramdatt, Director of Smart Cities & Special Projects, City of Orlando, Florida

Pinfold at 03:24, November 12, 2021

2021-11-12T03:24:29Z

← Older revision		Revision as of 03:24, November 12, 2021
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	\| email = Charles.ramdatt@cityoforlando.net		\| email = Charles.ramdatt@cityoforlando.net
	<!-- [mailto:SDROBOT@harris.com Sheldon Drobot]-->		<!-- [mailto:SDROBOT@harris.com Sheldon Drobot]-->
	\| image =		\| image = IRISroom2.jpg
	\| imagecaption =		\| imagecaption = Orlando Public Safety
	\| municipalities = Orlando, FL		\| municipalities = Orlando, FL
	<!-- ; Lynx Public Transit; Central Florida Expressway Authority; Florida Department of Transportation District V -->		<!-- ; Lynx Public Transit; Central Florida Expressway Authority; Florida Department of Transportation District V -->

Pinfold: 1 revision imported

2021-10-31T20:45:44Z

1 revision imported

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

en>Ocadmin at 06:07, March 23, 2020

2020-03-23T06:07:12Z

New page

{{ActionCluster

| title = Video Analytics for Orlando Special Events, Public Safety, Emergency Management and Traffic Situational Awareness

| team = Harris Corporation; University of Central Florida College of Engineering; ; Amazon Web Services

| leader = Charles Ramdatt, Director of Smart Cities & Special Projects, City of Orlando, Florida
| email = Charles.ramdatt@cityoforlando.net

| image =
| imagecaption =
| municipalities = Orlando, FL

| status = Ready for Public Announcement
| website =
| download =

| description =
The project will create connected, city-wide mobile resources and systems to help improve the responses to a variety of challenges within the City of Orlando. Orlando is central city of 275,000 people, in an urban area of 2.4 million citizens, but with 68+ million visitors per year and the largest rental car market in the world. Thus, Orlando has some unique challenges with public safety and traffic. This project will meet the needs of several city departments and external agencies by ensuring cross-cutting and robust situational awareness for a variety of scenarios. It will allow for optimized deployments and expedited responses from police, fire fighters, emergency medical services, public works staff, transportation staff, special event managers, and external agencies which are obligated to provide mutual aid.

| challenges =
Various city and external agency managers need tools to vastly improve situational awareness for several challenges in different scenarios, each of which requires quick response and seamless collaboration.

| solutions =
* Quick understanding of the scale and nature of challenges will allow the deployment of the appropriate resources and allow for the understanding of the mitigating measures that are to be employed.
* Response times are critical. The project will integrate computer aided dispatch (CAD) and automated vehicle location (AVL) systems, and implement systems in dispatch and training dispatchers to reduce the ambulance response time. The system will be integrated into GIS positioning system to locate individuals in need based on location.
* Several different camera systems are currently available. However, they are not integrated and no software based analytics are currently employed to interpret the numerous feeds on an expedited and simultaneous basis.

| requirements =
* Articulate the project vision to gain stakeholder support and buy-in from the community
* Develop and assemble project team & stakeholder team
* Review the individual and overlapping challenges faced by the team
* Inventory existing/available resources such as camera and communications systems
* Create scope and requirements, project plan
* Develop system architecture
* Create application development team, develop mobile application
* Downtown Orlando is selected as the pilot area because of the convergence of needs and the pre-existing camera networks in that area
* Run pilot to overlap with the hurricane season and the ramping up of high #s of special events in the Fall
* With lessons learned from the pilot, ensure a phased plan for enabling activity centers, major arterial roadway corridors, places of public interest, and then all neighborhoods across the city.
* Ensure a program of independent evaluation of performance

| kpi =
* Minimum 10% average response time of emergency medical teams
* Minimum 25% average time to clear traffic incidents due to non-life threatening events
* Minimum 25% average arrival time for public works crews to commence clearing of impassable roads

| measurement =
* Measurement of response time in minutes over 3-6 month period, compared to baseline
* Times to documented by 311, 911, Traffic Management Center, and Emergency Operations Center Staff.
* Times to be compared to video documentation of incident detection and responder arrival on scene

| standards =
* Requires interoperable GPS, AVL and CAD interfaces.
* Establishes standardized procedures for rapid response services.
* Establishes standardized methods for AI-based warning services
* Builds upon existing standards in weather and public safety
* Standardized processes are not unique to city or region and can be replicated and scaled up in multiple cities/communities. The solution is planned to be replicated in other cities in the USA, Europe, and Africa.
* The system will have its own business model to create sustainable revenue stream.

| cybersecurity =

| impacts =
* Reduction of existing ambulance response time
* Improving quality of lives
* Community acceptance to be replicated across the United States to engage the community to tie in medical resources.

| demonstration =
Real-time working application tied into city dispatch systems at city-wide scale, supporting over 50% of the city. Demonstration will include a simulated emergency event and the measurement of response time with and without the proposed solution.

| supercluster = Public Safety
| year = 2017

}}