In 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.
- 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
- 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
- A. M. Andrushko, “Leveraging smart measurement technologies for enhanced food and beverage servicing: a case study of the KYPS system” // COLLECTIVE MONOGRAPH “CAD IN MACHINERY DESIGN IMPLEMENTATION AND EDUCATIONAL ISSUES. XXXI INTERNATIONAL CONFERENCE”, Publishing House of Bialystok University of Technology, Białystok, Poland, 2024, 161-171. DOI: 10.24427/978-83-68077-19-3
- 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
- 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
- [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].
- 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
- 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.
- 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.
- H. V. Ravinder, “Forecasting With Exponential Smoothing – What’s The Right Smoothing Constant?”, Review of Business Information Systems, 17 (3), 2013, 117-126.
- 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
- 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