TY - CHAP
T1 - Unmanned aerial vehicles in precision agriculture towards circular economy
T2 - a process system engineering (PSE) assessment
AU - Yaqot, Mohammed
AU - Menezes, Brenno C.
AU - Al-Ansari, Tareq
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/1
Y1 - 2021/1
N2 - Farming is a complex and responsive business that considers types of soils and crops, topography, climate, etc., while minimising inputs like land and water for an optimal yield. Typically, a farm to be managed involves planting, irrigation, spraying of nutrients and pesticides, manual inspection when looking for signals of harvesting stress or pest infestation, etc. When these activities are unreliable, yields of crops fluctuate so do the enterprise margins. However, to reach higher levels of performance, today's agribusiness moves towards more sustainable and efficient operations within the so-called precision agriculture. From such a scenario, a process system engineering assessment is proposed to evaluate the impacts of industry 4.0 (I4) applications under circular economy (CE) concepts in the agricultural field. Particularly, we highlight drones or unmanned aerial vehicles as a tool in the agroindustry since numerous researchers and industries are designing and testing different principles and technologies that could be applied by replacing manpower with drones in engineering fields. A sensitivity risk analysis compares the I4 adoption and its CE impacts against an outdated agricultural-based production structure for corn production. It has been evaluated using subjective ratings for twenty sub-process components such as irrigation, monitoring, among others. The findings indicate that investments in agricultural drones’ capabilities will modify sub-processes under CE principles, resulting in a process system re-engineering in this field. Agricultural drones can increase the economy of the processes coupled with environmentally friendly applications, whereby the impact on the social pillar of the CE is still debatable.
AB - Farming is a complex and responsive business that considers types of soils and crops, topography, climate, etc., while minimising inputs like land and water for an optimal yield. Typically, a farm to be managed involves planting, irrigation, spraying of nutrients and pesticides, manual inspection when looking for signals of harvesting stress or pest infestation, etc. When these activities are unreliable, yields of crops fluctuate so do the enterprise margins. However, to reach higher levels of performance, today's agribusiness moves towards more sustainable and efficient operations within the so-called precision agriculture. From such a scenario, a process system engineering assessment is proposed to evaluate the impacts of industry 4.0 (I4) applications under circular economy (CE) concepts in the agricultural field. Particularly, we highlight drones or unmanned aerial vehicles as a tool in the agroindustry since numerous researchers and industries are designing and testing different principles and technologies that could be applied by replacing manpower with drones in engineering fields. A sensitivity risk analysis compares the I4 adoption and its CE impacts against an outdated agricultural-based production structure for corn production. It has been evaluated using subjective ratings for twenty sub-process components such as irrigation, monitoring, among others. The findings indicate that investments in agricultural drones’ capabilities will modify sub-processes under CE principles, resulting in a process system re-engineering in this field. Agricultural drones can increase the economy of the processes coupled with environmentally friendly applications, whereby the impact on the social pillar of the CE is still debatable.
KW - Precision agriculture
KW - circular economy
KW - industry 4.0
KW - society 5.0
UR - http://www.scopus.com/inward/record.url?scp=85110447559&partnerID=8YFLogxK
U2 - 10.1016/B978-0-323-88506-5.50241-2
DO - 10.1016/B978-0-323-88506-5.50241-2
M3 - Chapter
AN - SCOPUS:85110447559
T3 - Computer Aided Chemical Engineering
SP - 1559
EP - 1565
BT - Computer Aided Chemical Engineering
PB - Elsevier B.V.
ER -