Smart Agriculture and Digital Transformation on Case of Intelligent System for Wine Quality Prediction

Oreški, Dijana; Pihir, Igor; Cajzek, K.

doi:10.23919/mipro52101.2021.9596979

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Sarri et al introduce precision agriculture methods, suggesting they can be crucial in enhancing wine farm management [52]. Building on this, Oreški et al highlight the avenue of employing machine learning techniques, especially in predicting wine quality [53]. Furthermore, Vela et al's study underscore the significance of conducting energy audits in wineries [54].…”

Section: Smart Agriculture Applications For Vineyards and Wineries: T...mentioning

confidence: 99%

WiCHORD+: A Scalable, Sustainable, and P2P Chord-Based Ecosystem for Smart Agriculture Applications

Balatsouras,

Karras,

Karras

et al. 2023

Sensors

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In the evolving landscape of Industry 4.0, the convergence of peer-to-peer (P2P) systems, LoRa-enabled wireless sensor networks (WSNs), and distributed hash tables (DHTs) represents a major advancement that enhances sustainability in the modern agriculture framework and its applications. In this study, we propose a P2P Chord-based ecosystem for sustainable and smart agriculture applications, inspired by the inner workings of the Chord protocol. The node-centric approach of WiCHORD+ is a standout feature, streamlining operations in WSNs and leading to more energy-efficient and straightforward system interactions. Instead of traditional key-centric methods, WiCHORD+ is a node-centric protocol that is compatible with the inherent characteristics of WSNs. This unique design integrates seamlessly with distributed hash tables (DHTs), providing an efficient mechanism to locate nodes and ensure robust data retrieval while reducing energy consumption. Additionally, by utilizing the MAC address of each node in data routing, WiCHORD+ offers a more direct and efficient data lookup mechanism, essential for the timely and energy-efficient operation of WSNs. While the increasing dependence of smart agriculture on cloud computing environments for data storage and machine learning techniques for real-time prediction and analytics continues, frameworks like the proposed WiCHORD+ appear promising for future IoT applications due to their compatibility with modern devices and peripherals. Ultimately, the proposed approach aims to effectively incorporate LoRa, WSNs, DHTs, cloud computing, and machine learning, by providing practical solutions to the ongoing challenges in the current smart agriculture landscape and IoT applications.

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Section: Smart Agriculture Applications For Vineyards and Wineries: T...mentioning

confidence: 99%