A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers
Currently, efficiency in the supply domain and the ability to make quick and accurate decisions and to assess risk properly play a crucial role. The role of a decision support system (DSS) is to support the decision-making process in the enterprise, and for this, it is yet not enough to have up-to-d...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/8/3474 |
| _version_ | 1797537850737033216 |
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| author | Michał Kozielski Joanna Henzel Łukasz Wróbel Zbigniew Łaskarzewski Marek Sikora |
| author_facet | Michał Kozielski Joanna Henzel Łukasz Wróbel Zbigniew Łaskarzewski Marek Sikora |
| author_sort | Michał Kozielski |
| collection | DOAJ |
| description | Currently, efficiency in the supply domain and the ability to make quick and accurate decisions and to assess risk properly play a crucial role. The role of a decision support system (DSS) is to support the decision-making process in the enterprise, and for this, it is yet not enough to have up-to-date data; reliable predictions are necessary. Each application area has its own specificity, and so far, no dedicated DSS for liquefied petroleum gas (LPG) supply has been presented. This study presents a decision support system dedicated to support the LPG supply process from the perspective of gas demand analysis. This perspective includes a short- and medium-term gas demand prediction, as well as the definition and monitoring of key performance indicators. The analysis performed within the system is based exclusively on the collected sensory data; no data from any external enterprise resource planning (ERP) systems are used. Examples of forecasts and KPIs presented in the study show what kind of analysis can be implemented in the proposed system and prove its usefulness. This study, showing the overall workflow and the results for the use cases, which outperform the typical trivial approaches, could be a valuable direction for future works in the field of LPG and other fuel supply. |
| first_indexed | 2024-03-10T12:22:08Z |
| format | Article |
| id | doaj.art-5cb5aab9536a4dfcbbbc5b46ec594856 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T12:22:08Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-5cb5aab9536a4dfcbbbc5b46ec5948562023-11-21T15:20:34ZengMDPI AGApplied Sciences2076-34172021-04-01118347410.3390/app11083474A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas SuppliersMichał Kozielski0Joanna Henzel1Łukasz Wróbel2Zbigniew Łaskarzewski3Marek Sikora4Department of Computer Networks and Systems, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandDepartment of Computer Networks and Systems, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandDepartment of Computer Networks and Systems, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandAIUT Ltd., Wyczółkowskiego 113, 44-109 Gliwice, PolandDepartment of Computer Networks and Systems, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandCurrently, efficiency in the supply domain and the ability to make quick and accurate decisions and to assess risk properly play a crucial role. The role of a decision support system (DSS) is to support the decision-making process in the enterprise, and for this, it is yet not enough to have up-to-date data; reliable predictions are necessary. Each application area has its own specificity, and so far, no dedicated DSS for liquefied petroleum gas (LPG) supply has been presented. This study presents a decision support system dedicated to support the LPG supply process from the perspective of gas demand analysis. This perspective includes a short- and medium-term gas demand prediction, as well as the definition and monitoring of key performance indicators. The analysis performed within the system is based exclusively on the collected sensory data; no data from any external enterprise resource planning (ERP) systems are used. Examples of forecasts and KPIs presented in the study show what kind of analysis can be implemented in the proposed system and prove its usefulness. This study, showing the overall workflow and the results for the use cases, which outperform the typical trivial approaches, could be a valuable direction for future works in the field of LPG and other fuel supply.https://www.mdpi.com/2076-3417/11/8/3474decision-makingdecision support systemgas industrypredictive modelsboosting |
| spellingShingle | Michał Kozielski Joanna Henzel Łukasz Wróbel Zbigniew Łaskarzewski Marek Sikora A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers Applied Sciences decision-making decision support system gas industry predictive models boosting |
| title | A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers |
| title_full | A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers |
| title_fullStr | A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers |
| title_full_unstemmed | A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers |
| title_short | A Sensor Data-Driven Decision Support System for Liquefied Petroleum Gas Suppliers |
| title_sort | sensor data driven decision support system for liquefied petroleum gas suppliers |
| topic | decision-making decision support system gas industry predictive models boosting |
| url | https://www.mdpi.com/2076-3417/11/8/3474 |
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