Leveraging IoT data for accurate temperature forecasting in the food and beverage industry

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dc.citation.epage16
dc.citation.issue3
dc.citation.journalTitleКомп’ютерні системи проектування. Теорія і практика
dc.citation.spage9
dc.contributor.affiliationНаціональний університет “Львівська політехніка”
dc.contributor.affiliationНаціональний університет “Львівська політехніка”
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorАндрушко, Андрій
dc.contributor.authorТом’юк, Василь
dc.contributor.authorAndrushko, Andriy
dc.contributor.authorTomiuk, Vasyl
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-12-16T08:40:58Z
dc.description.abstractУ секторі громадського харчуваня підтримка оптимальних температурних умов має вирішальне значення для забезпечення якості та безпеки продукції. Поява Інтернету речей (IoT) дала змогу здійснювати моніторинг температури в режимі реального часу за допомогою сенсорних мереж, надаючи велику кількість даних, які можна використовувати для прогнозної аналітики. У цьому дослідженні запропоновано метод аналізу даних ІоТ та прогнозування температури на основі цих даних. Метод спеціально адаптовано до специфіки операційної динаміки сектору громадського харчуваня. Використовуючи експоненційне згладжування у поєднанні із елементами машинного навчання, автори створили алгоритм, здатний надавати точні прогнози температури для підтримки проактивного прийняття рішень.
dc.description.abstractIn the food and beverage industry, maintaining optimal temperature conditions is crucial for ensuring product quality and safety. The advent of the Internet of Things (IoT) has enabled real-time temperature monitoring through sensor networks, providing a wealth of data that can be harnessed for predictive analytics. This study presents a robust method for analyzing and forecasting IoT temperature data, specifically tailored to the operational dynamics of the food and beverage sector. By leveraging exponential smoothing techniques and a learning approach, we aim to present an algorithm capable of delivering accurate temperature forecasts to support proactive decision-making.
dc.format.extent9-16
dc.format.pages8
dc.identifier.citationAndrushko A. Leveraging IoT data for accurate temperature forecasting in the food and beverage industry / Andriy Andrushko, Vasyl Tomiuk // Computer Systems of Design. Theory and Practice. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 6. — No 3. — P. 9–16.
dc.identifier.citation2015Andrushko A., Tomiuk V. Leveraging IoT data for accurate temperature forecasting in the food and beverage industry // Computer Systems of Design. Theory and Practice, Lviv. 2024. Vol 6. No 3. P. 9–16.
dc.identifier.citationenAPAAndrushko, A., & Tomiuk, V. (2024). Leveraging IoT data for accurate temperature forecasting in the food and beverage industry. Computer Systems of Design. Theory and Practice, 6(3), 9-16. Lviv Politechnic Publishing House..
dc.identifier.citationenCHICAGOAndrushko A., Tomiuk V. (2024) Leveraging IoT data for accurate temperature forecasting in the food and beverage industry. Computer Systems of Design. Theory and Practice (Lviv), vol. 6, no 3, pp. 9-16.
dc.identifier.doihttps://doi.org/10.23939/cds2024.03.009
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/124092
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofКомп’ютерні системи проектування. Теорія і практика, 3 (6), 2024
dc.relation.ispartofComputer Systems of Design. Theory and Practice, 3 (6), 2024
dc.relation.references[1] F. Liu, C. W. Tan, E. T. K. Lim, & B. Choi, ―Traversing knowledge networks: an algorithmic historiography of extant literature on the Internet of Things (IoT)‖, Journal of Management Analytics, 4(1), 2016, 3–34. https://doi.org/10.1080/23270012.2016.1214540
dc.relation.references[2] E. Ahmed, I. Yaqoob, I. A. T. Hashem, I. Khan, A. I. A. Ahmed, M. Imran, A. V. Vasilakos, ―The role of big data analytics in Internet of Things‖, Computer Networks, 129(2), 2019, 459–471, ISSN 1389–1286.https://doi.org/10.1016/j.comnet.2017.06.013
dc.relation.references[3] A. M. Andrushko, ―Leveraging smart measurement technologies for enhanced food and beverage servicing: a case study of the KYPS system‖ // CAD in machinery design implementation and educational issues.XXXI international conference: collective monograph, Publishing House of Bialystok University of Technology, Białystok, Poland, 2024, 161–171. DOI: 10.24427/978-83-68077-19-3
dc.relation.references[4] P. Kansakar, F. Munir & N. Shabani, ―Technology in the Hospitality Industry: Prospects and Challenges‖, IEEE Consumer Electronics Magazine, 8(3), 2019, 60–65. DOI: 10.1109/MCE.2019.2892245
dc.relation.references[5] Y. Bouzembrak, M. Klüche, A. Gavai & Hans J. P. Marvin, ―Internet of Things in food safety: Literature review and a bibliometric analysis‖, Trends in Food Science & Technology, 94, 2019, 54–64. ISSN 0924-2244. https://doi.org/10.1016/j.tifs.2019.11.002
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dc.relation.references[7] Y. Sasaki, ―A Survey on IoT Big Data Analytic Systems: Current and Future‖, IEEE Internet of Things Journal, 9(2), 2022, 1024–1036. DOI: 10.1109/JIOT.2021.3131724
dc.relation.references[8] E. Ostertagova & O. Ostertag, ―The Simple Exponential Smoothing Model‖ // Modelling of mechanical and mechatronic systems 2011, The 4th International conference, Faculty of Mechanical engineering, Technical university of Košice, September 20–22, 2011, Herľany, Slovak Republic, 380–384.
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dc.relation.references[10] H. V. Ravinder, ―Forecasting With Exponential Smoothing – What’s The Right Smoothing Constant?‖, Review of Business Information Systems, 17 (3), 2013, 117–126.
dc.relation.references[11] I. Tuncer, ―Customer Experience in the Restaurant Industry: Use of Smart Technologies‖, Handbook of Research on Smart Technology Applications in the Tourism Industry, IGI Global, 2020. DOI: 10.4018/978-1-7998-1989-9.ch012
dc.relation.references[12] R. H. L. Chiang, V. Grover, T. P. Liang, & D. Zhang, ―Special Issue: Strategic Value of Big Data and Business Analytics‖, Journal of Management Information Systems, 35(2), 2018 383–387.https://doi.org/10.1080/07421222.2018.145195
dc.relation.referencesen[1] F. Liu, C. W. Tan, E. T. K. Lim, & B. Choi, ―Traversing knowledge networks: an algorithmic historiography of extant literature on the Internet of Things (IoT)‖, Journal of Management Analytics, 4(1), 2016, 3–34. https://doi.org/10.1080/23270012.2016.1214540
dc.relation.referencesen[2] E. Ahmed, I. Yaqoob, I. A. T. Hashem, I. Khan, A. I. A. Ahmed, M. Imran, A. V. Vasilakos, ―The role of big data analytics in Internet of Things‖, Computer Networks, 129(2), 2019, 459–471, ISSN 1389–1286.https://doi.org/10.1016/j.comnet.2017.06.013
dc.relation.referencesen[3] A. M. Andrushko, ―Leveraging smart measurement technologies for enhanced food and beverage servicing: a case study of the KYPS system‖, CAD in machinery design implementation and educational issues.XXXI international conference: collective monograph, Publishing House of Bialystok University of Technology, Białystok, Poland, 2024, 161–171. DOI: 10.24427/978-83-68077-19-3
dc.relation.referencesen[4] P. Kansakar, F. Munir & N. Shabani, ―Technology in the Hospitality Industry: Prospects and Challenges‖, IEEE Consumer Electronics Magazine, 8(3), 2019, 60–65. DOI: 10.1109/MCE.2019.2892245
dc.relation.referencesen[5] Y. Bouzembrak, M. Klüche, A. Gavai & Hans J. P. Marvin, ―Internet of Things in food safety: Literature review and a bibliometric analysis‖, Trends in Food Science & Technology, 94, 2019, 54–64. ISSN 0924-2244. https://doi.org/10.1016/j.tifs.2019.11.002
dc.relation.referencesen[6] [Electronic resource] M. Diaz, ―How to manage hotel food and beverage services: redefining F&B in the hospitality industry‖, 2019, https://joinposter.com/en/post/hotel-food-and-beverage [Jul 11, 2023].
dc.relation.referencesen[7] Y. Sasaki, ―A Survey on IoT Big Data Analytic Systems: Current and Future‖, IEEE Internet of Things Journal, 9(2), 2022, 1024–1036. DOI: 10.1109/JIOT.2021.3131724
dc.relation.referencesen[8] E. Ostertagova & O. Ostertag, ―The Simple Exponential Smoothing Model‖, Modelling of mechanical and mechatronic systems 2011, The 4th International conference, Faculty of Mechanical engineering, Technical university of Košice, September 20–22, 2011, Herľany, Slovak Republic, 380–384.
dc.relation.referencesen[9] B. Render, R. M. Stair Jr., M. E. Hanna, T. S. Hale, ―Quantitative Analysis for Management‖, 13th Edition, Pearson Education Limited, Edinburgh Gate, Harlow, Essex CM20 2JE, England, 2018.
dc.relation.referencesen[10] H. V. Ravinder, ―Forecasting With Exponential Smoothing – What’s The Right Smoothing Constant?‖, Review of Business Information Systems, 17 (3), 2013, 117–126.
dc.relation.referencesen[11] I. Tuncer, ―Customer Experience in the Restaurant Industry: Use of Smart Technologies‖, Handbook of Research on Smart Technology Applications in the Tourism Industry, IGI Global, 2020. DOI: 10.4018/978-1-7998-1989-9.ch012
dc.relation.referencesen[12] R. H. L. Chiang, V. Grover, T. P. Liang, & D. Zhang, ―Special Issue: Strategic Value of Big Data and Business Analytics‖, Journal of Management Information Systems, 35(2), 2018 383–387.https://doi.org/10.1080/07421222.2018.145195
dc.relation.urihttps://doi.org/10.1080/23270012.2016.1214540
dc.relation.urihttps://doi.org/10.1016/j.comnet.2017.06.013
dc.relation.urihttps://doi.org/10.1016/j.tifs.2019.11.002
dc.relation.urihttps://joinposter.com/en/post/hotel-food-and-beverage
dc.relation.urihttps://doi.org/10.1080/07421222.2018.145195
dc.rights.holder© Національний університет „Львівська політехніка“, 2024
dc.rights.holder© Аndrushko А., Tomiuk V., 2024
dc.subjectIoT
dc.subjectдані
dc.subjectпрогноз температури
dc.subjectсектор громадського харчуваня
dc.subjectекспоненційне згладжування
dc.subjectаналіз часових рядів
dc.subjectсезонність
dc.subjectIoT
dc.subjectdata
dc.subjecttemperature forecasting
dc.subjectfood and beverage industry
dc.subjectexponential smoothing
dc.subjecttime series analysis
dc.subjectseasonality
dc.titleLeveraging IoT data for accurate temperature forecasting in the food and beverage industry
dc.title.alternativeВикористання ІоТ даних для точного прогнозування температури в секторі громадського харчування
dc.typeArticle

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Комп'ютерні системи проектування теорія і практика. – 2024. – Том 6, № 3