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Article
Computer Science, Hardware & Architecture
Tanzila Saba et al.
Summary: The growth of Internet of Agriculture Things (IoAT) with wireless technologies has brought significant advances to smart farming systems. However, predicting soil and crop conditions still poses a challenge. This paper proposes a smart optimization model that uses machine learning to develop reliable and quality-aware sustainable agriculture. The model automates data collection and transmission, analyzes performance variables, and integrates blockchain-based security principles to reduce communication interference. Simulations and experiments validate the efficacy of the proposed model in network parameters.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
Nilesh Kumar Jadav et al.
Summary: →Massive population growth and rising environmental issues pose challenges in agriculture, such as land scarcity, pesticide overuse, and global food demand. To tackle this, we proposed a blockchain and AI-powered smart agriculture framework to predict pesticide levels in crops. The blockchain ensures data integrity, storing records securely. Evaluation metrics show that our framework outperforms baseline approaches in accuracy, scalability, and latency.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Computer Science, Information Systems
Darah Aqel et al.
Summary: This paper proposes a new approach for automatic detection and classification of plant leaf diseases using ELM deep learning algorithm. The approach utilizes image segmentation, feature extraction, and optimization algorithms to achieve promising results in terms of classification measures.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Prabhat Kumar et al.
Summary: Smart agriculture utilizes low-cost and low-energy-consuming sensors and devices to improve agricultural production in terms of quantity and quality. However, the use of an open communication channel, i.e., the Internet, and real-time generation of large amounts of data pose potential risks of misuse. To address these challenges, a deep privacy-encoding-based federated learning framework is proposed, which effectively identifies normal and attack patterns.
Letter
Biotechnology & Applied Microbiology
Philipp E. Bayer et al.
PLANT BIOTECHNOLOGY JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Anusha Vangala et al.
Summary: Agriculture is a vital area for human sustenance, and innovation is crucial for its survival as resources diminish. The rapid development of IoT and blockchain technology can improve the state of the food chain. This study proposes a generalized blockchain-based security architecture, conducts detailed cost analysis on schemes, and uncovers drawbacks in existing research through meticulous comparative analysis.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Information Systems
Mohamed Amine Ferrag et al.
Summary: Smart Agriculture integrates advanced technologies to enhance agricultural productivity, but also faces new cybersecurity threats. This study proposes a deep learning-based intrusion detection system for DDoS attacks, evaluating its performance on various real traffic datasets.
Article
Management
Manuel Jesus Ramirez et al.
Summary: This study examines the antecedents and performance outcomes of supply chain integration in the agri-food industry in Latin America, with a focus on the quinoa supply chain. Trust and commitment were found to be crucial drivers for successful integration, particularly when involving farmers. High levels of integration were shown to enhance operational performance and positively impact economic indicators.
INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT
(2021)
Article
Agronomy
Dagoberto Armenta-Medina et al.
Article
Computer Science, Information Systems
Maanak Gupta et al.
