Use Cases of Technologies in Precision Agriculture: Selected Abstracts Submitted to the 10th Asian-Australasian Conference on Precision Agriculture (ACPA10)
Redmond R. Shamshiri, Maryam Behjati, Siva K. Balasundram, Ibrahim A. Hameed, Ahmad Kamil Zolkafli, An Ho-Song, Arina Mohd Noh, Badril Hisham Abu Bakar, Wasiu Balogun, Beom-Sun Kang, Cong-Chuan Pham, Dang Khanh Linh Le, Dong Hee Noh, Dong-Seok Kim, Eliezel Habineza, Farizal Kamaroddin, Gookhwan Kim, Heetae Kim, Hyunjung Hwang, Jaesung Park
- 发表年份
- 2024
- 引用次数
- 1
- 访问权限
- 开放获取
摘要
This chapter is a collection of selected abstracts presented at the 10th Asian-Australasian Conference on Precision Agriculture, held from October 24th to 26th in Putrajaya, Malaysia. It aims to emphasize the transformative potential of technology in precision agriculture and smart farming. The featured studies highlight the transformative impact of technology and current improvements in agriculture, offering modern solutions including machine learning, robotics, remote sensing, and geographic information systems (GIS). From autonomous navigation for mobile robots to stress classification in crop production systems, and from phenotypic analysis with LiDAR technology to real-time sensor monitoring in greenhouse agriculture, the majority of abstracts underline the integration of digital tools in different fields of farming with the core objective of reshaping conventional farming techniques and eliminating dependency on manual works. Key examples include the development of a distributed sensing system (DSS) used for orchard robots, stress classification for tomato seedlings through image-based color features and machine learning, and the integration of remote sensing and AI in crop protection. Other solutions, such as automated spraying robots for cherry tomato greenhouses, active back exoskeletons for rice farm lifting tasks, and advancements in seedling transplanting techniques, have shown promising results for contributing to sustainable farming practices by providing accurate and timely information for decision-making amid climate change-induced uncertainties.
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