D6.1 Design of the monitoring system and KPI definition

This deliverable presents the key performance indicators (KPI) that will be used to quantify the performance of the MiniStor system. The KPIs have been selected based on a literature review, a survey among project partners as well as indicators initially defined in the grant agreement. For each KPI, the required input (measurement) values are determined, and a calculation procedure is defined. Many of these KPIs will be measured through a monitoring system also specified in this document. This report also presents the monitoring system architecture, the selected hardware and the data flow process to collect the variables in order to aggregate, transmit and store them in a cloud-based IoT platform for data visualisation and analysis in compliance with relevant data safety measures. As each demonstration site has its site-specific features, the monitoring systems were adjusted to the requirements of each site. The respective adjustments have been described as well.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-13
DOI
https://doi.org/10.5281/zenodo.16964115
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

D6.1 Design of the monitoring system and KPI definition

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

D6.1 Design of the monitoring system and KPI definition

article en

Abstract

This deliverable presents the key performance indicators (KPI) that will be used to quantify the performance of the MiniStor system. The KPIs have been selected based on a literature review, a survey among project partners as well as indicators initially defined in the grant agreement. For each KPI, the required input (measurement) values are determined, and a calculation procedure is defined. Many of these KPIs will be measured through a monitoring system also specified in this document. This report also presents the monitoring system architecture, the selected hardware and the data flow process to collect the variables in order to aggregate, transmit and store them in a cloud-based IoT platform for data visualisation and analysis in compliance with relevant data safety measures. As each demonstration site has its site-specific features, the monitoring systems were adjusted to the requirements of each site. The respective adjustments have been described as well.

Zenodo (CERN European Organization for Nuclear Research)
College of Wooster (US), Democritus University of Thrace (GR), Cooperative Institute for Research in Environmental Sciences (US), IDEO (United States) (US), Universidade de Santiago de Compostela (ES), NOAA Atlantic Oceanographic and Meteorological Laboratories (US), Endo Pharmaceuticals (United States) (US), R2M Solution (Italy) (IT), Centre for Research and Technology Hellas (GR), Energy International (United States) (US), Woosuk University (KR), Lucerne University of Applied Sciences and Arts (CH), Woosong University (KR)
Partnerships for the goals
Openalex Percentile: Top 51%
Geochemistry and Geologic Mapping
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D6.1 Design of the monitoring system and KPI definition · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS