Vineyard Digital Twin: construction and characterization via UAV images - DIWINE Proof of Concept

被引:9
作者
Edemetti, Francesco [1 ]
Maiale, Angela [2 ]
Carlini, Camillo [2 ]
D'Auria, Olga [2 ]
Llorca, Jaime [3 ,4 ]
Tulino, Antonia Maria [3 ,4 ]
机构
[1] Noovle SpA Soc Benefit, Data Ctr, Colocat & Operat Infrastruct Serv, Milan, Italy
[2] TIM SpA, Technol & Innovat Dept, Milan, Italy
[3] NYU, New York, NY USA
[4] Univ Naples Federico II, Informat & Commun Technol Dept, Naples, Italy
来源
2022 IEEE 23RD INTERNATIONAL SYMPOSIUM ON A WORLD OF WIRELESS, MOBILE AND MULTIMEDIA NETWORKS (WOWMOM 2022) | 2022年
关键词
Unmanned Aerial Vehicles; Machine Learning; 5G NR; Digital Twin;
D O I
10.1109/WoWMoM54355.2022.00094
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The DIWINE project aims to play a salient role in the Smart and Sustainable Agriculture industry by enabling creation of a Digital Twin platform for a vineyard. It is conceived as a disruptive solution based on the use of: Unmanned Aerial Vehicles (UAVs), 5G, edge/cloud computing, Machine Learning (ML) and Artificial Intelligence (AI). The platform leverages key 5G technologies such as 5G New Radio (NR) and Multi Access Edge computing (MEC) to remotely control the UAVs and to transfer captured high-resolution images to the cloud. Moreover, the computational power of MEC and central cloud computing enables the use of ML and AI algorithms to process captured data and transform it into a highly accurate Digital Twin. The winemaker has an immediate and flexible access to the Digital Twin platform and is also able to integrate existing technologies, such as IoT sensors and weather forecasts. DIWINE allows: an efficient management of the vineyard, accurately differentiating the final product, simulating different possible scenarios, and optimizing the farm's consumption, supporting the winemaker to minimize missed harvests risk, and optimizing profitability.
引用
收藏
页码:601 / 606
页数:6
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