Naslov
Smart Agriculture: Machine Learning in Modelling Wine Quality Based on Laboratory or IoT Sensory Analysis

Autori
Oreški, Dijana ; Pihir, Igor ; Kadoić, Nikola

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of 56th Croatian and 16th International symposium on Agriculture / Rozman, Vlatka ; Antunović, Zvonko - Osijek : Fakultet agrobiotehničkih znanosti Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2021, 717-722

Skup
56. hrvatski i 16. međunarodni simpozij agronoma

Mjesto i datum
Vodice, Hrvatska, 05.09.2021. - 10.09.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
smart agriculture, machine learning, wine quality, IoT, modelling

Sažetak
Agriculture is undergoing a Digital Transformation by use of emerging or Industry 4.0 technologies. Emerging technologies like IoT, Big Data, Data Analytics, Drones, and others, are rapidly implemented in so-called “Smart Agriculture”. These technologies boost productivity, improve predictions, manage uncertainty and introduction of innovations, mmaking producers more competitive. This paper deals with testing, the concept of using IoT, Big Data, Data Analytics and Machine Learning to model and predict wine quality. Prediction model is tested on publicly available dataset. Research results based on physicochemical properties of wines shows good results for wine quality prediction. Research is part of EU funded project Center of Competences for Digital Transformation of the Food Industry in Rural Areas.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA