Harvesting Data the Role of AI in Smart Farming and Precision Agriculture DOI
Muhammad Huzaifa Mahmood,

Muhammad Waseem,

Mujahid Abbas

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2024, Volume and Issue: unknown, P. 37 - 60

Published: Nov. 22, 2024

Integrating AI into data-driven agriculture is not a cure-all but potentially transformative tool. Embracing advanced technologies and driving progress can help ensure more sustainable profitable agricultural future, meeting the needs of growing population. This chapter explores specific role within smart precision agriculture. The covers application in data capture ranging from sensor networks, satellite imagery, drone technology, weather integration to monitor crop health, soil conditions, environmental factors real-time, enhancing It examines how various analysis methods encompassing machine learning algorithms, image recognition & computer vision, predictive analytics interpret provide meaningful insights. also underpinned decision-making scenarios such as targeted irrigation, pest disease control, automated weed selective harvesting, livestock monitoring % management, rotation planning, planting date optimization.

Language: Английский

Advancements in soil management: optimizing crop production through interdisciplinary approaches DOI Creative Commons
R. K. Srivastava,

Subhankar Purohit,

Edris Alam

et al.

Journal of Agriculture and Food Research, Journal Year: 2024, Volume and Issue: unknown, P. 101528 - 101528

Published: Nov. 1, 2024

Language: Английский

Citations

11
Sorghum (Sorghum bicolor) as a Functional Food: Expansion Potential, Sustainable Economy and Policy in East Manggarai DOI Open Access

Johanna Suek,

Damianus Adar

IOP Conference Series Earth and Environmental Science, Journal Year: 2025, Volume and Issue: 1482(1), P. 012007 - 012007

Published: April 1, 2025

Abstract Sorghum ( bicolor ) is recognized as a functional food due to its versatile health, and nutritional benefits. In East Manggarai Regency sorghum was initially introduced but has seen resurgence in the past five years. The study aims describe from expansion potential economic well policy sustainability. research conducted two purposively selected sub-districts, Lamba Leda Selatan Borong. These locations were chosen their significant development of cultivation over A random sampling method used select 48 households population existing farmers. Data collected through questionnaires, FGDs, in-depth discussions. analyzed descriptively by calculating mean values, standard deviations, coefficient variations. Results found that cultivated simple management technique after harvesting rice corn. On average, area for crop 0.69 ± 0.36 ha, with productivity 1511.37/ha. From an sustainability perspective, economically profitable within community, indicated RCR (Revenue-Cost Ratio) value 2.45. Additionally, efficient productive use capital, labor, land underscores viability. also highlights supportive role regulatory frameworks promoting cultivation. To enhance these outcomes, further efforts should focus on optimizing maximize while ensuring sustainable environmental management.

Language: Английский

Citations

0
Design and analysis of a LoRa-based system with scheduled transmissions from IoT nodes to UAV in rural areas DOI
Alessandro Andreadis, Giovanni Giambene, Riccardo Zambon

et al.

Ad Hoc Networks, Journal Year: 2025, Volume and Issue: unknown, P. 103868 - 103868

Published: April 1, 2025

Language: Английский

Citations

0
Architecture and Applications of IoT Devices in Socially Relevant Fields DOI
S. Anush Lakshman, Akash Saxena,

J. Cynthia

et al.

SN Computer Science, Journal Year: 2024, Volume and Issue: 5(7)

Published: Aug. 28, 2024

Language: Английский

Citations

1
Harvesting Data the Role of AI in Smart Farming and Precision Agriculture DOI
Muhammad Huzaifa Mahmood,

Muhammad Waseem,

Mujahid Abbas

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2024, Volume and Issue: unknown, P. 37 - 60

Published: Nov. 22, 2024

Integrating AI into data-driven agriculture is not a cure-all but potentially transformative tool. Embracing advanced technologies and driving progress can help ensure more sustainable profitable agricultural future, meeting the needs of growing population. This chapter explores specific role within smart precision agriculture. The covers application in data capture ranging from sensor networks, satellite imagery, drone technology, weather integration to monitor crop health, soil conditions, environmental factors real-time, enhancing It examines how various analysis methods encompassing machine learning algorithms, image recognition & computer vision, predictive analytics interpret provide meaningful insights. also underpinned decision-making scenarios such as targeted irrigation, pest disease control, automated weed selective harvesting, livestock monitoring % management, rotation planning, planting date optimization.

Language: Английский

Citations

0