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Environmental Engineering

2023

Artificial intelligence

Articles 1 - 2 of 2

Full-Text Articles in Other Civil and Environmental Engineering

Aicropcam: Deploying Classification, Segmentation, Detection, And Counting Deep-Learning Models For Crop Monitoring On The Edge, Nipuna Chamara, Geng (Frank) Bai, Yufeng Ge Dec 2023

Aicropcam: Deploying Classification, Segmentation, Detection, And Counting Deep-Learning Models For Crop Monitoring On The Edge, Nipuna Chamara, Geng (Frank) Bai, Yufeng Ge

Department of Biological Systems Engineering: Papers and Publications

Precision Agriculture (PA) promises to meet the future demands for food, feed, fiber, and fuel while keeping their production sustainable and environmentally friendly. PA relies heavily on sensing technologies to inform site-specific decision supports for planting, irrigation, fertilization, spraying, and harvesting. Traditional point-based sensors enjoy small data sizes but are limited in their capacity to measure plant and canopy parameters. On the other hand, imaging sensors can be powerful in measuring a wide range of these parameters, especially when coupled with Artificial Intelligence. The challenge, however, is the lack of computing, electric power, and connectivity infrastructure in agricultural fields, preventing …


High-Throughput Phenotyping Of Plant Leaf Morphological, Physiological, And Biochemical Traits On Multiple Scales Using Optical Sensing, Huichun Zhang, Lu Wang, Xiuliang Jin, Liming Bian, Yufeng Ge May 2023

High-Throughput Phenotyping Of Plant Leaf Morphological, Physiological, And Biochemical Traits On Multiple Scales Using Optical Sensing, Huichun Zhang, Lu Wang, Xiuliang Jin, Liming Bian, Yufeng Ge

Department of Biological Systems Engineering: Papers and Publications

Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the fastest responses to external environmental stimuli, leaf phenotypic traits are indicators of plant growth, health, and stress levels. Combination of new imaging sensors, image processing, and data analytics permits measurement over the full life span of plants at high temporal resolution and at several organizational levels from organs to individual plants to field populations of plants. We review the optical sensors and associated data analytics used for measuring morphological, …