A Framework for Tasks Allocation and Scheduling in Precision Agriculture Settings

Santilli, Matteo; Carpio, Renzo Fabrizio; Gasparri, Andrea

doi:10.1109/icar53236.2021.9659387

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…In particular, the Arduino platform has become a popular choice due to its affordability and ease of integration [ 36 ]. In addition, researchers have developed algorithms such as DCTA (Dynamic Converge cast Tree Algorithm) [ 37 ], OASNDFA (Optimized Algorithm of Sensor Node Deployment for intelligent Agricultural monitoring) [ 38 ], BOP (Beacon Only Period) [ 39 ], distributed localization algorithms [ 40 ], polynomial-time algorithms for node deployment [ 41 ], range-based localization algorithms [ 42 ], electromagnetic induction algorithms [ 43 ], MLR (Multiple Regression Analysis) [ 44 ], PCR (Principal Component Regression) [ 45 ], and PLSR (Partial Least Squares Regression) [ 46 ] methods for efficient monitoring and intelligent irrigation of crops. The review also highlights the introduction of new communication protocols, including the Fuzzy-based Energy Efficiency Protocol [ 47 , 48 ], APTEEN (Adaptive Periodic Threshold-sensitive Energy Efficient sensor Network protocol) [ 49 , 50 ], while operating systems such as Tiny OS and Tiny OS2.0 [ 51 ] are frequently adopted for sensor implementations in PA [ 35 ].…”

Section: Introductionmentioning

confidence: 99%

Smart Sensors and Smart Data for Precision Agriculture: A Review

Soussi,

Zero,

Sacile

et al. 2024

Sensors

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Precision agriculture, driven by the convergence of smart sensors and advanced technologies, has emerged as a transformative force in modern farming practices. The present review synthesizes insights from a multitude of research papers, exploring the dynamic landscape of precision agriculture. The main focus is on the integration of smart sensors, coupled with technologies such as the Internet of Things (IoT), big data analytics, and Artificial Intelligence (AI). This analysis is set in the context of optimizing crop management, using resources wisely, and promoting sustainability in the agricultural sector. This review aims to provide an in-depth understanding of emerging trends and key developments in the field of precision agriculture. By highlighting the benefits of integrating smart sensors and innovative technologies, it aspires to enlighten farming practitioners, researchers, and policymakers on best practices, current challenges, and prospects. It aims to foster a transition towards more sustainable, efficient, and intelligent farming practices while encouraging the continued adoption and adaptation of new technologies.

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