Future of sustainable farming: exploring opportunities and overcoming barriers in drone-IoT integration

Sustainable agriculture is being transformed by drone-IoT integration, improving precision, efficiency, and sustainability. This study examines the pros and downsides of using various technologies to handle connectivity, data management, and power consumption issues. We assess existing integration methods, such as multispectral imaging, real-time IoT monitoring, and machine learning-driven predictive analytics, to gain actionable insights into soil health, crop conditions, and pest control. We also explore regulatory frameworks and technical constraints, including data security and affordability that prevent widespread use. Research shows that drone IoT solutions improve agricultural output, resource consumption, and farm efficiency, but cost and infrastructure hurdles limit availability, especially for smallholder farmers. These findings show that supporting regulatory frameworks and economical technology solutions are needed to increase adoption. Advances in agricultural autonomous decision-making could increase food security and sustainable farming worldwide.

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Publication Details

Journal
Discover Sustainability
Published
2024-12-18
DOI
https://doi.org/10.1007/s43621-024-00736-y
Citations
16
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
9.59
Controls
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article

Future of sustainable farming: exploring opportunities and overcoming barriers in drone-IoT integration

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16 citations
Discover Sustainability
Smart Agriculture and AI
9.59
article

Future of sustainable farming: exploring opportunities and overcoming barriers in drone-IoT integration

Tehseen Mazhar, Muhammad Amir Khan, Tariq Shahzad, Sunawar Khan, Habib Hamam, Sghaier Guizani
article en
16 citations

Abstract

Sustainable agriculture is being transformed by drone-IoT integration, improving precision, efficiency, and sustainability. This study examines the pros and downsides of using various technologies to handle connectivity, data management, and power consumption issues. We assess existing integration methods, such as multispectral imaging, real-time IoT monitoring, and machine learning-driven predictive analytics, to gain actionable insights into soil health, crop conditions, and pest control. We also explore regulatory frameworks and technical constraints, including data security and affordability that prevent widespread use. Research shows that drone IoT solutions improve agricultural output, resource consumption, and farm efficiency, but cost and infrastructure hurdles limit availability, especially for smallholder farmers. These findings show that supporting regulatory frameworks and economical technology solutions are needed to increase adoption. Advances in agricultural autonomous decision-making could increase food security and sustainable farming worldwide.

Discover SustainabilityVol. 5(1)
Alfaisal University (SA), Université de Moncton (CA), COMSATS University Islamabad (PK), Islamia University of Bahawalpur (PK), University of Johannesburg (ZA), Government of Pakistan (PK), National College of Business Administration and Economics (PK), Government of Punjab (PK), Universiti Teknologi MARA (MY)
Zero hunger
Openalex Percentile: Top 2%
Smart Agriculture and AI
9.59
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Future of sustainable farming: exploring opportunities and overcoming barriers in drone-IoT integration — Tehseen Mazhar, Muhammad Amir Khan, et al. · Discover Sustainability (2024) | TGRS Research Map | TGRS