Smart Water Technologies - Revision history

Pinfold at 05:45, January 25, 2023

2023-01-25T05:45:46Z

← Older revision		Revision as of 05:45, January 25, 2023
Line 20:		Line 20:
	\|impacts=Not available at this time		\|impacts=Not available at this time
	\|demonstration=Internet of H2O hackathon		\|demonstration=Internet of H2O hackathon
			\|chapter=Smart Water
	\|supercluster=Utility		\|supercluster=Utility
	\|year=2018		\|year=2018

Pinfold at 09:13, March 19, 2022

2022-03-19T09:13:31Z

← Older revision		Revision as of 09:13, March 19, 2022
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	\|leader=Sudhir Kshirsagar		\|leader=Sudhir Kshirsagar
	\|imagecaption=The Cleveland Water Alliance (CWA)		\|imagecaption=The Cleveland Water Alliance (CWA)
	\|municipalities=Cleveland OH~~<!-- The Cleveland Water Alliance -->~~		\|municipalities=Cleveland OH
	\|status=Launched		\|status=Launched
	\|website=http://hydrotrek.com		\|website=http://hydrotrek.com

Pinfold at 08:09, March 19, 2022

2022-03-19T08:09:31Z

← Older revision		Revision as of 08:09, March 19, 2022
Line 1:		Line 1:
	{{ActionCluster		{{ActionCluster
	\| ~~title~~ = ~~Smart Replicable Solutions to Water~~-~~Energy Nexus Challenges~~		\|image=cwa-logo.png
	\| team = Global Quality Corp.		\|team=Global Quality Corp.
	\| leader = Sudhir Kshirsagar		\|leader=Sudhir Kshirsagar
	~~\| image = cwa-logo.png~~		\|imagecaption=The Cleveland Water Alliance (CWA)
	\| imagecaption = The Cleveland Water Alliance (CWA)		\|municipalities=Cleveland OH<!-- The Cleveland Water Alliance -->
	\| municipalities = Cleveland OH		\|status=Launched
	<!-- The Cleveland Water Alliance -->		\|website=http://hydrotrek.com
	\| status = Launched		\|download=SolutionstoWater-EnergyNexusChallenges.pdf
	\| website = http://hydrotrek.com		\|description=The goal of this action cluster is to provide innovative solutions for managing drinking water, wastewater, stormwater and source water resources efficiently and effectively.
	\| download = ~~[https://drive~~.~~google.com/open?id=1VzH0bhhXGPOuespPBQzEJ8kWY4kNm3jj Tech Jam Presentation]~~
	\| description =
	The goal of this action cluster is to provide innovative solutions for managing drinking water, wastewater, stormwater and source water resources efficiently and effectively.
	The smart decisions that balance energy usage with desired water quality and quantity will be supported through the development of cloud-based analytics that is driven with the “Big Data” from distributed array of environmental sensors. These “Internet of Things (IOT)” environmental sensors will be used to both monitor and control the environment. The new data will be supplemented with the data from the existing infrastructure such as SCADA historian databases and meter data. Additional data needs will be examined carefully to reduce their impact on operations. For example, water meter data is usually collected on a daily basis to prolong the battery life whereas the same data may be needed at five-minute intervals to generate an accurate demand picture. Innovative approaches that provide additional data through low-cost sensing and citizen participation will be explored.		The smart decisions that balance energy usage with desired water quality and quantity will be supported through the development of cloud-based analytics that is driven with the “Big Data” from distributed array of environmental sensors. These “Internet of Things (IOT)” environmental sensors will be used to both monitor and control the environment. The new data will be supplemented with the data from the existing infrastructure such as SCADA historian databases and meter data. Additional data needs will be examined carefully to reduce their impact on operations. For example, water meter data is usually collected on a daily basis to prolong the battery life whereas the same data may be needed at five-minute intervals to generate an accurate demand picture. Innovative approaches that provide additional data through low-cost sensing and citizen participation will be explored.
	\| challenges =		\|challenges=Integrate "Frugal Innovation."
	Integrate "Frugal Innovation."		\|solutions=The smart decisions that balance energy usage with desired water quality and quantity will be supported through the development of cloud-based analytics that is driven with the “Big Data” from distributed array of environmental sensors.
	\| solutions =		\|requirements=Innovative approaches that provide additional data through low-cost sensing and citizen participation will be explored.
	The smart decisions that balance energy usage with desired water quality and quantity will be supported through the development of cloud-based analytics that is driven with the “Big Data” from distributed array of environmental sensors.		\|kpi=Under development
	\| requirements=		\|measurement=Ongoing
	Innovative approaches that provide additional data through low-cost sensing and citizen participation will be explored.		\|standards=The lack of standards for data exchange of environmental data is a major issue. There is a significant body of work mainly related to the XML-based exchange of source water data, and the US EPA is relying on Environmental Sampling, Analysis and Results Data Standard (ESAR) and Water Quality Exchange (WQX). The Standard Energy Efficiency Data (SEED) Platform is used by DOE. However, there are no standards for the “Smart City Sensor Data.” Existing data exchange formats are mainly driven by the capabilities of the underlying transmission protocols. The commercial web services have adopted “REST with JSON payload” as their standard, and the environmental web services will need to be compatible with these commercial services so that all data, whether public or commercial, can be easily consumed. This project will develop web services that support “REST with JSON” as their public end-points. It will also develop draft standards for data packet definitions for the JSON datasets. This will be a critical piece of this work because JSON format can be interpreted in a variety of ways, and different interpretations can result in incompatibilities. The REST/JSON API will be defined to promote integration with the existing standards.
	\| kpi =		\|cybersecurity=The IoT solutions leverage the LoRaWAN protocol for the node to gateway transmissions, and use technologies based on the AWS IoT client and Azure IoT client to manage the gateways from a cloud-based orchestrator. This approach allows Software Defined Networking (SDN) while providing cybersecure communications. The node locations and related metadata are stored in secure cloud-based storage to protect privacy.
	Under development
	\| measurement =
	Ongoing
	\| standards =
	The lack of standards for data exchange of environmental data is a major issue. There is a significant body of work mainly related to the XML-based exchange of source water data, and the US EPA is relying on Environmental Sampling, Analysis and Results Data Standard (ESAR) and Water Quality Exchange (WQX). The Standard Energy Efficiency Data (SEED) Platform is used by DOE. However, there are no standards for the “Smart City Sensor Data.” Existing data exchange formats are mainly driven by the capabilities of the underlying transmission protocols. The commercial web services have adopted “REST with JSON payload” as their standard, and the environmental web services will need to be compatible with these commercial services so that all data, whether public or commercial, can be easily consumed. This project will develop web services that support “REST with JSON” as their public end-points. It will also develop draft standards for data packet definitions for the JSON datasets. This will be a critical piece of this work because JSON format can be interpreted in a variety of ways, and different interpretations can result in incompatibilities. The REST/JSON API will be defined to promote integration with the existing standards.
	~~\| replicability =~~
	The key to replicability of the project achievements will be ensured through the development of a solid workflow that can be re-executed with minimal interactions with original stakeholders. Such a workflow will require the development of plug and play software and hardware to the extent feasible. The scalability of the solutions will be achieved through the deployment of distributed sensors, edge computing gateways and robust cloud backbones. A collaborative cloud-based platform to share learnings will support sustainability of the solutions.
	\| cybersecurity =
	The IoT solutions leverage the LoRaWAN protocol for the node to gateway transmissions, and use technologies based on the AWS IoT client and Azure IoT client to manage the gateways from a cloud-based orchestrator. This approach allows Software Defined Networking (SDN) while providing cybersecure communications. The node locations and related metadata are stored in secure cloud-based storage to protect privacy.
	The LoRaWAN protocol includes advanced security mechanisms that have to be selected and implemented carefully. We created a Class A device in our implementation and used recommended OTAA (Over the Air Activation) method for authentication. We ran the LoRa Network server on the field gateway and send data forward using MQTT to the Azure IoT hub using security tokens to authenticate devices and services to avoid sending keys on the network. Additionally, security tokens were limited in time validity and scope. Our AWS-based orchestrator that manages specific field gateways uses the AWS X.509 based IoT client, and does not involve the opening of new ports into the firewall. So it substantially improves security while providing advanced device management features. In a nutshell, many millions of devices are communicating today with the architecture of LoRaWAN+ (Azure and/or AWS) but the architecture has to be carefully provisioned to provide the necessary security for the use cases. We demonstrated a cyber-secure and privacy protection architecture for our use cases using LoRaWAN, Azure and AWS.		The LoRaWAN protocol includes advanced security mechanisms that have to be selected and implemented carefully. We created a Class A device in our implementation and used recommended OTAA (Over the Air Activation) method for authentication. We ran the LoRa Network server on the field gateway and send data forward using MQTT to the Azure IoT hub using security tokens to authenticate devices and services to avoid sending keys on the network. Additionally, security tokens were limited in time validity and scope. Our AWS-based orchestrator that manages specific field gateways uses the AWS X.509 based IoT client, and does not involve the opening of new ports into the firewall. So it substantially improves security while providing advanced device management features. In a nutshell, many millions of devices are communicating today with the architecture of LoRaWAN+ (Azure and/or AWS) but the architecture has to be carefully provisioned to provide the necessary security for the use cases. We demonstrated a cyber-secure and privacy protection architecture for our use cases using LoRaWAN, Azure and AWS.
	\| impacts = Not available at this time		\|impacts=Not available at this time
	\| demonstration = Internet of H2O hackathon		\|demonstration=Internet of H2O hackathon
	\| supercluster = Utility		\|supercluster=Utility
	\| year = 2018		\|year=2018
			\|title=Smart Replicable Solutions to Water-Energy Nexus Challenges
			\|replicability=The key to replicability of the project achievements will be ensured through the development of a solid workflow that can be re-executed with minimal interactions with original stakeholders. Such a workflow will require the development of plug and play software and hardware to the extent feasible. The scalability of the solutions will be achieved through the deployment of distributed sensors, edge computing gateways and robust cloud backbones. A collaborative cloud-based platform to share learnings will support sustainability of the solutions.
	}}		}}

Pinfold at 10:47, March 13, 2022

2022-03-13T10:47:15Z

← Older revision		Revision as of 10:47, March 13, 2022
Line 2:		Line 2:
	\| title = Smart Replicable Solutions to Water-Energy Nexus Challenges		\| title = Smart Replicable Solutions to Water-Energy Nexus Challenges
	\| team = Global Quality Corp.		\| team = Global Quality Corp.
	\| leader = ~~Dr.~~ Sudhir Kshirsagar~~, Global Quality Corp.~~		\| leader = Sudhir Kshirsagar
	\| image = cwa-logo.png		\| image = cwa-logo.png
	\| imagecaption = The Cleveland Water Alliance (CWA)		\| imagecaption = The Cleveland Water Alliance (CWA)

Pinfold: 1 revision imported

2021-10-31T20:45:29Z

1 revision imported

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

en>Ocadmin at 05:51, March 23, 2020

2020-03-23T05:51:33Z

New page

{{ActionCluster
| title = Smart Replicable Solutions to Water-Energy Nexus Challenges
| team = Global Quality Corp.
| leader = Dr. Sudhir Kshirsagar, Global Quality Corp.
| image = cwa-logo.png
| imagecaption = The Cleveland Water Alliance (CWA)
| municipalities = Cleveland OH

| status = Launched
| website = http://hydrotrek.com
| download = [https://drive.google.com/open?id=1VzH0bhhXGPOuespPBQzEJ8kWY4kNm3jj Tech Jam Presentation]
| description =
The goal of this action cluster is to provide innovative solutions for managing drinking water, wastewater, stormwater and source water resources efficiently and effectively.
The smart decisions that balance energy usage with desired water quality and quantity will be supported through the development of cloud-based analytics that is driven with the “Big Data” from distributed array of environmental sensors. These “Internet of Things (IOT)” environmental sensors will be used to both monitor and control the environment. The new data will be supplemented with the data from the existing infrastructure such as SCADA historian databases and meter data. Additional data needs will be examined carefully to reduce their impact on operations. For example, water meter data is usually collected on a daily basis to prolong the battery life whereas the same data may be needed at five-minute intervals to generate an accurate demand picture. Innovative approaches that provide additional data through low-cost sensing and citizen participation will be explored.
| challenges =
Integrate "Frugal Innovation."
| solutions =
The smart decisions that balance energy usage with desired water quality and quantity will be supported through the development of cloud-based analytics that is driven with the “Big Data” from distributed array of environmental sensors.
| requirements=
Innovative approaches that provide additional data through low-cost sensing and citizen participation will be explored.
| kpi =
Under development
| measurement =
Ongoing
| standards =
The lack of standards for data exchange of environmental data is a major issue. There is a significant body of work mainly related to the XML-based exchange of source water data, and the US EPA is relying on Environmental Sampling, Analysis and Results Data Standard (ESAR) and Water Quality Exchange (WQX). The Standard Energy Efficiency Data (SEED) Platform is used by DOE. However, there are no standards for the “Smart City Sensor Data.” Existing data exchange formats are mainly driven by the capabilities of the underlying transmission protocols. The commercial web services have adopted “REST with JSON payload” as their standard, and the environmental web services will need to be compatible with these commercial services so that all data, whether public or commercial, can be easily consumed. This project will develop web services that support “REST with JSON” as their public end-points. It will also develop draft standards for data packet definitions for the JSON datasets. This will be a critical piece of this work because JSON format can be interpreted in a variety of ways, and different interpretations can result in incompatibilities. The REST/JSON API will be defined to promote integration with the existing standards.
| replicability =
The key to replicability of the project achievements will be ensured through the development of a solid workflow that can be re-executed with minimal interactions with original stakeholders. Such a workflow will require the development of plug and play software and hardware to the extent feasible. The scalability of the solutions will be achieved through the deployment of distributed sensors, edge computing gateways and robust cloud backbones. A collaborative cloud-based platform to share learnings will support sustainability of the solutions.
| cybersecurity =
The IoT solutions leverage the LoRaWAN protocol for the node to gateway transmissions, and use technologies based on the AWS IoT client and Azure IoT client to manage the gateways from a cloud-based orchestrator. This approach allows Software Defined Networking (SDN) while providing cybersecure communications. The node locations and related metadata are stored in secure cloud-based storage to protect privacy.
The LoRaWAN protocol includes advanced security mechanisms that have to be selected and implemented carefully. We created a Class A device in our implementation and used recommended OTAA (Over the Air Activation) method for authentication. We ran the LoRa Network server on the field gateway and send data forward using MQTT to the Azure IoT hub using security tokens to authenticate devices and services to avoid sending keys on the network. Additionally, security tokens were limited in time validity and scope. Our AWS-based orchestrator that manages specific field gateways uses the AWS X.509 based IoT client, and does not involve the opening of new ports into the firewall. So it substantially improves security while providing advanced device management features. In a nutshell, many millions of devices are communicating today with the architecture of LoRaWAN+ (Azure and/or AWS) but the architecture has to be carefully provisioned to provide the necessary security for the use cases. We demonstrated a cyber-secure and privacy protection architecture for our use cases using LoRaWAN, Azure and AWS.
| impacts = Not available at this time
| demonstration = Internet of H2O hackathon
| supercluster = Utility
| year = 2018
}}