Machine learning for the assessment and prediction of nitrite in the aquaculture water

Nguyen, Nhan; Nguyen, Khang; Dinh, Ngan; Tran, Nhut Minh

doi:10.1109/mapr56351.2022.9924656

Cited by 3 publications

(1 citation statement)

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“…Moreover, Google Colab [199,200] has gained traction as a collaborative platform for machine learning and data analysis tasks. Leveraging its integration with Google Drive and Jupyter Notebooks, Google Colab provides researchers with a flexible and scalable environment for running machine learning algorithms and experimenting with large datasets.…”

Section: Reporting Componentsmentioning

confidence: 99%

IoT Solutions with Artificial Intelligence Technologies for Precision Agriculture: Definitions, Applications, Challenges, and Opportunities

Senoo,

Anggraini,

Kumi

et al. 2024

Electronics

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The global agricultural sector confronts significant obstacles such as population growth, climate change, and natural disasters, which negatively impact food production and pose a threat to food security. In response to these challenges, the integration of IoT and AI technologies emerges as a promising solution, facilitating data-driven decision-making, optimizing resource allocation, and enhancing monitoring and control systems in agricultural operations to address these challenges and promote sustainable farming practices. This study examines the intersection of IoT and AI in precision agriculture (PA), aiming to provide a comprehensive understanding of their combined impact and mutually reinforcing relationship. Employing a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we explore the synergies and transformative potential of integrating IoT and AI in agricultural systems. The review also aims to identify present trends, challenges, and opportunities in utilizing IoT and AI in agricultural systems. Diverse forms of agricultural practices are scrutinized to discern the applications of IoT and AI systems. Through a critical analysis of existing literature, this study contributes to a deeper understanding of how the integration of IoT and AI technologies can revolutionize PA, resulting in improved efficiency, sustainability, and productivity in the agricultural sector.

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Section: Reporting Componentsmentioning

confidence: 99%