A Smart and Mechanized Agricultural Application: From Cultivation to Harvest

Applied Sciences

Sajjad Nematzadeh¹  Metin Zontul²  Anselme Muzirafuti³  Giovanni Randazzo³  Stefania Lanza⁴  Fahri Erenel⁵  Fateme Aysin Anka⁵  Ilkay Yelmen⁶  Amir Seyyedabbasi⁷  Farzad Kiani⁷ 

[1] Computer Engineering Department, Faculty of Engineering and Architecture, Nisantasi University, Istanbul 34398, Turkey;Department of Computer Engineering, Faculty of Engineering, Istanbul Topkapı University, Istanbul 34093, Turkey;Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università degli Studi di Messina, Via F. Stagno d’Alcontres, 31, 98166 Messina, Italy;GeoloGIS s.r.l., Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università degli Studi di Messina, Via F. Stagno d’Alcontres, 98166 Messina, Italy;Political Science and Public Administration Department, Faculty of Economics, Administrative and Social Sciences, Istinye University, Istanbul 34396, Turkey;R&D Center, Turkcell Technology, Istanbul 34854, Turkey;Software Engineering Department, Faculty of Engineering and Natural Science, Istinye University, Istanbul 34396, Turkey;

关键词: autonomous robots;    remote sensing;    smart agriculture;    climate change;    environmental protection;    drone;   

DOI  :  10.3390/app12126021

来源: DOAJ

【 摘 要 】

Food needs are increasing day by day, and traditional agricultural methods are not responding efficiently. Moreover, considering other important global challenges such as energy sufficiency and migration crises, the need for sustainable agriculture has become essential. For this, an integrated smart and mechanism-application-based model is proposed in this study. This model consists of three stages. In the first phase (cultivation), the proposed model tried to plant crops in the most optimized way by using an automized algorithmic approach (Sand Cat Swarm Optimization algorithm). In the second stage (control and monitoring), the growing processes of the planted crops was tracked and monitored using Internet of Things (IoT) devices. In the third phase (harvesting), a new method (Reverse Ant Colony Optimization), inspired by the ACO algorithm, was proposed for harvesting by autonomous robots. In the proposed model, the most optimal path was analyzed. This model includes maximum profit, maximum quality, efficient use of resources such as human labor and water, the accurate location for planting each crop, the optimal path for autonomous robots, finding the best time to harvest, and consuming the least power. According to the results, the proposed model performs well compared to many well-known methods in the literature.

【 授权许可】

Unknown