An Approach for Applying Artificial Intelligence (AI) with Internet of Nano Things (IoNT) to Smart Metering in the Utility Industry
Advisor Information
Dr. Deepak Khazanchi
Presentation Type
Oral Presentation
Start Date
26-3-2021 12:00 AM
End Date
26-3-2021 12:00 AM
Abstract
Advanced metering infrastructure (AMI) in the utility industry is a collaborative arrangement of smart meters, communications networks, and data management systems that facilitates shared interaction between customers and associated utilities, and collection of periodic data. AMI has an application in the smart home, power grids, and forest monitoring. The data gathered by advanced metering infrastructure (AMI) is used to determine per-day-power usage, grid outage recovery, improve energy efficiency, and utility service. Most industrial utility providers and services failed to deliver the time-of-use pricing, automated demand response, and true-cost of the energy, as per the American Council for Energy-Efficient Economy (ACEEE) annual report. The reasons for failure are primarily due to challenges in data collection that resulted in economic loss for customers. This also led companies to not deploy AMI anymore. Prior studies approached these communication and data challenges by using IoT (internet of things), artificial intelligence, and distributed storage techniques that use large computing and energy resources. However, this problem can be approached at the physical level rather than the system management level by using the Internet of Nano Things(IoNT) as a miniaturized replacement for traditional IoT sensors. IoNT sensors when deployed will consume less power, have the ability to cover larger areas for communication, and could be placed in otherwise unreachable locations. An AI/ML design approach is proposed integrating IoNT. The AI/ML approaches on data can be utilized to develop cost-beneficial energy delivery by avoiding data integrity challenges and potentially improve safety measures in case of natural accidents like power outages or weather challenges.
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An Approach for Applying Artificial Intelligence (AI) with Internet of Nano Things (IoNT) to Smart Metering in the Utility Industry
Advanced metering infrastructure (AMI) in the utility industry is a collaborative arrangement of smart meters, communications networks, and data management systems that facilitates shared interaction between customers and associated utilities, and collection of periodic data. AMI has an application in the smart home, power grids, and forest monitoring. The data gathered by advanced metering infrastructure (AMI) is used to determine per-day-power usage, grid outage recovery, improve energy efficiency, and utility service. Most industrial utility providers and services failed to deliver the time-of-use pricing, automated demand response, and true-cost of the energy, as per the American Council for Energy-Efficient Economy (ACEEE) annual report. The reasons for failure are primarily due to challenges in data collection that resulted in economic loss for customers. This also led companies to not deploy AMI anymore. Prior studies approached these communication and data challenges by using IoT (internet of things), artificial intelligence, and distributed storage techniques that use large computing and energy resources. However, this problem can be approached at the physical level rather than the system management level by using the Internet of Nano Things(IoNT) as a miniaturized replacement for traditional IoT sensors. IoNT sensors when deployed will consume less power, have the ability to cover larger areas for communication, and could be placed in otherwise unreachable locations. An AI/ML design approach is proposed integrating IoNT. The AI/ML approaches on data can be utilized to develop cost-beneficial energy delivery by avoiding data integrity challenges and potentially improve safety measures in case of natural accidents like power outages or weather challenges.