Version 1
: Received: 12 February 2024 / Approved: 12 February 2024 / Online: 12 February 2024 (15:38:38 CET)
How to cite:
Tandazo Espinoza, M. G.; Punina Cordova, B. I.; Tandazo Vanegas, R. E. IoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring. Preprints2024, 2024020705. https://doi.org/10.20944/preprints202402.0705.v1
Tandazo Espinoza, M. G.; Punina Cordova, B. I.; Tandazo Vanegas, R. E. IoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring. Preprints 2024, 2024020705. https://doi.org/10.20944/preprints202402.0705.v1
Tandazo Espinoza, M. G.; Punina Cordova, B. I.; Tandazo Vanegas, R. E. IoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring. Preprints2024, 2024020705. https://doi.org/10.20944/preprints202402.0705.v1
APA Style
Tandazo Espinoza, M. G., Punina Cordova, B. I., & Tandazo Vanegas, R. E. (2024). IoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring. Preprints. https://doi.org/10.20944/preprints202402.0705.v1
Chicago/Turabian Style
Tandazo Espinoza, M. G., Byron Ivan Punina Cordova and Ronald Eduardo Tandazo Vanegas. 2024 "IoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring" Preprints. https://doi.org/10.20944/preprints202402.0705.v1
Abstract
Gas leakage can occur for various reasons, including a gas leak in the distribution line, damaged regulators, service connection failures, fluctuations in inlet gas pressure, and other factors leading to millions in losses to the state. The objective is to develop a general and intelligent model for tracking and monitoring LPG distribution based on the Internet of Things and Business Intelligence technology. Devices such as sensors and actuators reduce risks and prevent accidents. IoT can also access automatic control of machines and infrastructure, and sensors’ data helps make intelligent decisions. The quantitative approach is used in the systematic review methodology based on the PRISMA statement; the architecture design is based on analytical research that studies the feasibility of a measure through empirical evidence; and the architecture description uses a qualitative approach. The Y.4908 Standard evaluates an IoT network’s interoperability, usability, and security. A targeted group of thirty IT professionals was surveyed to assess the Business Intelligence model. Forty scientific papers were selected for analysis. A model with IoT components and a four-level business intelligence system was found. At the overall average level, 49% strongly agree, 38% agree, 12% neither agree nor disagree, and 1% disagree. In other words, the model has an overall average approval rating of 87%.
Keywords
Internet of Things; IoT; LPG; sensing approach; Business Intelligence; Liquefied Petroleum Gas
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
