CROPSYNC: AI-POWERED SUSTAINABLE CROP MANAGEMENT

Authors

Ziad Doughan, Assistant Professor, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow
Ibrahim Mneimneh, Student, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow
Zouheir Nakouzi, Student, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow
Noor Al Khaib, Student, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow
Samer Damaj, Student, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow
Jamal Chaaban, Student, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow
Hamza Mrad, Student, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow
Sari Itani, Student, Faculty of Engineering, Beirut Arab University, Beirut, LebanonFollow

Keywords

CropSync, AI, IoT, Ensemble Learning, Computer Vision, Precision Agriculture

Disciplines

Agriculture | Artificial Intelligence and Robotics | Biology and Biomimetic Materials | Bioresource and Agricultural Engineering | Data Science | Geochemistry | Robotics

Abstract

CropSync is a smart agriculture system that uses AI and IoT technologies to enable sustain- able crop management and precision farming. The system aims to address the challenges faced by the agriculture sector, such as increasing food production to meet global population demands while minimizing environmental impact. CropSync integrates sensors, cameras, and cloud-based analytics to provide farmers with real-time insights and recommendations for optimizing crop cul- tivation. The system upholds engineering professional and ethical standards, considering broader social, environmental, and economic implications. From a social perspective, CropSync improves food security and enhances farmers’ livelihoods through increased productivity and efficient re- source utilization. The environmental impact is mitigated through sustainable farming practices that reduce water consumption, minimize chemical fertilizer use, and optimize agricultural inputs. Economically, CropSync helps farmers make informed decisions, reduce operational costs, and increase profitability, contributing to the overall viability and resilience of the agricultural sec- tor. The project report details the technical aspects of the CropSync system, including hardware and software components, AI-powered crop recommendation and disease detection models, and a user-friendly mobile application. This paper delves into the AI model development aspect of Cropsync.

Author ORCID Identifier

Ziad Doughan - https://orcid.org/0000-0002-7566-7710

Ibrahim Mneimneh - https://orcid.org/0009-0005-1737-3289

Zouheir Nakouzi - https://orcid.org/0009-0006-1245-8707

Noor Al Khaib - https://orcid.org/0009-0001-7745-6298

Samer Damaj - https://orcid.org/0009-0008-7832-5186

Jamal Chaaban - https://orcid.org/0009-0008-2501-9572

Hamza Mrad - https://orcid.org/0009-0008-0927-571X

Sari Itani - https://orcid.org/0009-0007-7886-510X

Recommended Citation

Doughan, Ziad; Mneimneh, Ibrahim; Nakouzi, Zouheir; Al Khaib, Noor; Damaj, Samer; Chaaban, Jamal; Mrad, Hamza; and Itani, Sari (2024) "CROPSYNC: AI-POWERED SUSTAINABLE CROP MANAGEMENT," BAU Journal - Science and Technology: Vol. 6: Iss. 1, Article 4.
DOI: https://doi.org/10.54729/2959-331X.1145

ISSN

2959-331X