Advancement in Computer Vision, Artificial Intelligence and Wireless Technology: A Crop Phenotyping Perspective

  • Ronnie S. Concepcion II, Charles Joseph L. Dela Cruz, Aldrian Kiel I. Gamboa, Saleh Ali Abdulkader, Joshua T. Macaldo, Samuel Isaac B. Teruel

Abstract

Artificial intelligence (AI) is a continuously evolving area of computer science that grows with the development of computer technologies. It replicates human thinking developed through deep learning algorithms and applies it to different applications in today’s society. In this time of crisis, ensuring quality and stable food sources is critical in supporting different communities. Given this situation, AI may be applied in crop phenotyping to improve and ensure quality crop growth in agricultural fields. Recent advancements in computer vision and wireless technologies is proven to aid in monitoring and controlling the amount of quality crop growth through crop phenotyping. Crop phenotyping aims to breed high quality crops utilizing the capabilities from a wide array of sensors and analysis procedures. Replicating 100% of the human intelligence is not currently possible but if developed properly, AIs may help in improving crop growth and minimizing the need of human involvement in agriculture. This paper focuses on reviewing recent advancements in computer vision and AI concepts introduced by several studies and how it can be implemented to complement crop phenotyping. Discussed here are the different aspects of advancements in computer vision and artificial intelligence that could be impactful in agriculture. The development of AI applications for crop phenotyping could be a new method in securing stable food sources even in a closed environment. It could aid the agricultural industry in achieving high quality and yield of crops even for crops not in its season. The information from different studies were used to recommend possible methods and improvements in the field of crop phenotyping.

Keywords: artificial intelligence, computer vision, crop growth, crop phenotype, wireless technologies

Published
2020-06-11
How to Cite
Ronnie S. Concepcion II, Charles Joseph L. Dela Cruz, Aldrian Kiel I. Gamboa, Saleh Ali Abdulkader, Joshua T. Macaldo, Samuel Isaac B. Teruel. (2020). Advancement in Computer Vision, Artificial Intelligence and Wireless Technology: A Crop Phenotyping Perspective. International Journal of Advanced Science and Technology, 29(06), 7050 - 7065. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/22480