TY - GEN
T1 - Unmanned Aerial Vehicle (UAV) in precision agriculture
T2 - 1st International Conference on Emerging Smart Technologies and Applications, eSmarTA 2021
AU - Yaqot, Mohammed
AU - Menezes, Brenno C.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/10
Y1 - 2021/8/10
N2 - Humanity has facing emerging global issues as new virus diseases, extremes in weather conditions, increasing climatic changes, depletion of the environment and natural resources, sharply rising demand for food, to just name a few. Therefore, the agriculture industry has been challenged in its processes and products, resulting in a surge of application of novel technologies and practices to maintain itself sustainable. Despite that, this industry is still responsible for 37% of the worldwide workforce, consumes 34% of the global arable land, utilizes 70% of the total water, and emits up to 30% of greenhouse gases (GHG). Progressively widespread in the sector, smart farming is a high-tech, efficient, and sustainable approach achieved by applying integrated technologies within the agricultural value chain processes. It includes increasing feed and food production and decreasing of their waste, prediction of diseases, better estimation of product yields ahead of time, determination of the best harvest time, monitoring of plants-growth cycles, etc. The results are going to yield a sustainable use of soil and water resources while maintaining the green landscape and biodiversity of nature. Emerging remote-sensing technologies and artificial intelligence applications have become essential tools to address these challenges. Drones, also known as Unmanned aerial vehicles (UAVs) are among the most promising industry 4.0 (I4) applications for the next generation of agriculture. This paper is a forehead into applications of drones from the innovation economy's standpoint as a viable tool and an effective manpower replacement in the agro-industry. In such a field, artificial intelligence (AI) has the potential to be the engine for automation of processes to be integrated into cyber-physical systems and enhanced modeling towards improved agriculture, more efficiently than the previous stages of the applications of technologies in this sector. Agricultural communities and businesses must take a strategic approach for continuous improvement production processes by implementing quicker, safer, and cheaper plans through data analytics and farming as a service (FaaS).
AB - Humanity has facing emerging global issues as new virus diseases, extremes in weather conditions, increasing climatic changes, depletion of the environment and natural resources, sharply rising demand for food, to just name a few. Therefore, the agriculture industry has been challenged in its processes and products, resulting in a surge of application of novel technologies and practices to maintain itself sustainable. Despite that, this industry is still responsible for 37% of the worldwide workforce, consumes 34% of the global arable land, utilizes 70% of the total water, and emits up to 30% of greenhouse gases (GHG). Progressively widespread in the sector, smart farming is a high-tech, efficient, and sustainable approach achieved by applying integrated technologies within the agricultural value chain processes. It includes increasing feed and food production and decreasing of their waste, prediction of diseases, better estimation of product yields ahead of time, determination of the best harvest time, monitoring of plants-growth cycles, etc. The results are going to yield a sustainable use of soil and water resources while maintaining the green landscape and biodiversity of nature. Emerging remote-sensing technologies and artificial intelligence applications have become essential tools to address these challenges. Drones, also known as Unmanned aerial vehicles (UAVs) are among the most promising industry 4.0 (I4) applications for the next generation of agriculture. This paper is a forehead into applications of drones from the innovation economy's standpoint as a viable tool and an effective manpower replacement in the agro-industry. In such a field, artificial intelligence (AI) has the potential to be the engine for automation of processes to be integrated into cyber-physical systems and enhanced modeling towards improved agriculture, more efficiently than the previous stages of the applications of technologies in this sector. Agricultural communities and businesses must take a strategic approach for continuous improvement production processes by implementing quicker, safer, and cheaper plans through data analytics and farming as a service (FaaS).
KW - Data analytics
KW - Drones
KW - Information and communication technologies
KW - Innovation economy
KW - UAV
UR - https://www.scopus.com/pages/publications/85115097253
U2 - 10.1109/eSmarTA52612.2021.9515736
DO - 10.1109/eSmarTA52612.2021.9515736
M3 - Conference contribution
AN - SCOPUS:85115097253
T3 - 2021 1st International Conference on Emerging Smart Technologies and Applications, eSmarTA 2021
BT - 2021 1st International Conference on Emerging Smart Technologies and Applications, eSmarTA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 August 2021 through 12 August 2021
ER -