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Wijewardane, N
Acharya, I
Medici, M
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Authors
Wijewardane, N
Ge, Y
Canavari, M
Medici, M
Rossetti, G
Kovacs, P
Maimaitijiang, M
Millett, B
Dorissant, L
Acharya, I
Janjua, U.U
Dilmurat, K
Topics
Proximal Sensing in Precision Agriculture
Robotics, Guidance and Automation
Big Data, Data Mining and Deep Learning
Type
Oral
Poster
Year
2016
2022
2024
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1. Laboratory Evaluation of Two VNIR Optical Sensor Designs for Vertical Soil Sensing

Visible and near infrared reflectance spectroscopy (VNIR) is becoming an extensively researched technology to predict soil properties such as soil organic carbon, inorganic carbon, total nitrogen, moisture  for precision agriculture. Due to its rapid, non-destructive nature and ability to infer multiple soil properties simultaneously, engineers have been trying to develop proximal sensors based on the VNIR technology to enable horizontal soil sensing and mapping. Since the vertical variation... N. Wijewardane, Y. Ge

2. Agricultural Robots Classification Based on Clustering by Features and Function

Robotic systems in agriculture (hereafter referred to as agrobots) have become popular in the last few years. They represent an opportunity to make food production more efficient, especially when coupled with technologies such as the Internet of Things and Big Data. Agrobots bring many advantages in farm operations: they can reduce humane fatigue and work-related accidents. In contrast, their large-scale diffusion is today limited by a lack of clarity and exhaustiveness in the regulatory framework... M. Canavari, M. Medici, G. Rossetti

3. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask Learning

Rapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches with... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat