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Growing, Production and Environmental Engineering
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| VITOSHKIN HELENA |
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Team:Dr. G. Mittelman (ARO) Dr. A. Kribus (Tel-Aviv University) |
| Innovative solar beam splitting concepts: cogeneration and photochemistry |
Our group develops innovative applications that require solar spectral beam splitting mirrors. Applications are investigated in several areas: cogeneration of power and heat, greenhouse water treatment with photochemistry, production of solar electricity in agricultural fields and alternative fuels production. The overall goal is to develop technology that could be upscaled and implemented in commercial-size plants.
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Sensing, Information and Mechanization Engineering
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| COHEN YAFIT |
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Team:Dr. Victor Alchanatis, Dr. Alon Ben-Gal, Dr. Yishai Netser |
| Digital ag: Fusion of aerial thermal and satellite multi-spectral imaging for remote sensing-based irrigation management |
Satellite thermal imaging have coarse spatial resolution and aerial platforms require substantial financial investments, which may inhibit their large-scale adoption. The study aims to increase the capacity of aerial thermal imaging by fusing satellite multi-spectral images in the VIS-NIR range. The study incorporates image processing and "big-data" analysis techniques (deep and machine learning) The successful candidate is expected to develop semi-automatic tools for near-real-time acquisition and analysis of aerial and satellite images of different characteristics, lead the research, and summarize the results in reports and scientific publications.
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| COHEN YAFIT |
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Team:Dr. Victor Alchanatis, Dr. Alon Ben-Gal, Dr. Aviva peeters, Prof. George Vellidis. |
| Precision agriculture: Dynamic irrigation management zones using multivariable layers and spatial statistics |
To use variable rate irrigation systems, a field is divided into irrigation management zones (IMZs). While IMZs are dynamic in nature, most of IMZs prescription maps are static. In this study we explore and develop various approaches to delineate dynamic irrigation management zones using remote-sensing, GIS, image processing and spatial statistics. The successful candidate is expected to develop semi-automatic tools for near-real-time acquisition and analysis of aerial and satellite images of different characteristics, lead the research, and summarize the results in reports and scientific publications.
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| End to end electro-optics system for agricultural-biological systems under environmental conditions |
The Agro-Optics and Sensing lab is focused on removing the acquisition barriers in optical sensing of agricultural-biological systems under environmental conditions. In the first project, the research is focused on water quality problems. In a second project, the research focus on advance fruit content analysis. Both projects require the establishment of an active electro-optics and machine learning systems. The research confronts the mutual relation between machine learning algorithm, light propagation in an optical system, interaction of light ant mater in biological water environment micro-biology and chemical lab experiments. Upon his or her skills the researcher will be involved in one of the two proposed projects and other activities of the laboratory.
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| Development of a variable rate drip irrigation system |
This research projects aims to develop an irrigation system which can deliver variable rates of irrigation using drip irrigation systems. A first conceptual design has been performed, and a first prototype has been constructed. The current work aims to focus on detailed design and construction of prototypes; to characterize its performance in terms of fluidics and mechanics; to extend the specifications of the first design to additional features; to test the prototypes in lab and field conditions; and to incorporate manufacturing principles to design a component that might be produced in mass production.
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| Improving the performance of UAV acquired thermal infrared imaging for field crops irrigation management |
Crop canopy temperature has been shown to be indicative of water status. Statistical models linking between normalized canopy temperature indices and crop physioligical paramters have been also developed, based on zenith acquired images around midday. In order to expand acquisition of images through UAVs, the throughput has to be increased. This works aims to increase UAV thermal images acquisition throughput by 1) determining the off-zenith angles that enable reliable canopy temperature mapping and 2) develop procedures to extend the acquisition time interval as wide as possible around the solar zenith 3) Develop procedures for reliable estimation of the minimum reference temperature for canopy water status estimation
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| Updated on: 07/07/19 14:11 |
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