Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/BA3B9923-BCDE-4538-952E-DDCE658EB4DE | ||
| Year | 2015 | ||
| Type of Item | Master Thesis | ||
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| Bibliographic Citation | Christos Konstantopoulos, "Self-powered plant sensor for scatter radio", Master Thesis, School of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece, 2015 https://doi.org/10.26233/heallink.tuc.24437 | ||
| Appears in Collections |
In agriculture applications (e.g. greenhouses, vineyards etc.) it is required toautomatically gather information about environmental variables such as soil and air humidity, as well as temperature in the vicinity of plants within the same field, with low-cost and high-scalability. Thus, sensor networks that areextending over a broad area and gather environmental datafor microclimate monitoring, are indispensable for the application of optimal crop management techniques. The field of plant electro-physiology investigates the correlation of environmental variables with the electrical signals that are produced by diverse types of plants.Existing research in measurement of electrical signalsgenerated by plants has been conducted using high-costequipment, such as laboratory multi-meters and data-loggers,in order to perform the signal-conditioning and data acquisitionoperations required. This thesis introduces for first time in the existing research literature a novel low cost and self-powered sensor node that belongs to a large-scale scatter radio network and simultaneously is powered in a parasitic way to the plants, as well as is able to acquire and transmit these types of signals from each plant. Furthermore, in the context of this thesis, several experimental prototypes of the proposed node were developed, as well as used to gather measurements of electrical signals that are generated from multiple Avocado plants. The experimental results demonstrate the successful operation of the proposed WSN node, as well as indicate the correlation of plants signals with solar irradiation and plant irrigation events. Thus, the proposed system can be employed in precision agriculture applications for automated irrigation scheduling, control of the plant ambient conditions etc. based on data derived directly by the plants.
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