Path Loss Determination Using Linear and Cubic Regression Inside a Classic Tomato Greenhouse

The production of tomatoes in greenhouses, in addition to its relevance in nutrition and health, is an activity of the agroindustry with high economic importance in Spain, the first exporter in Europe of this vegetable. The technological updating with precision agriculture, implemented in order to e...

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Bibliographic Details
Published in:International journal of environmental research and public health 2019-05, Vol.16 (10), p.1744
Main Authors: Cama-Pinto, Dora, Damas, Miguel, Holgado-Terriza, Juan Antonio, Gómez-Mula, Francisco, Cama-Pinto, Alejandro
Format: Article
Language:English
Subjects:
Agricultural economics
Agriculture
Agriculture - methods
Communication
Environment, Controlled
Environmental monitoring
Environmental Monitoring - instrumentation
Environmental Monitoring - methods
Foliage
Greenhouses
Land use
Leaves
Lycopersicon esculentum - physiology
Microwave frequencies
Millimeter waves
Orchards
Precision farming
Radio attenuation
Radio equipment
Radio signals
Radio Waves
Receivers & amplifiers
Remote sensors
Reviews
Sensors
Spain
Tomatoes
Transmitters
Vegetation
Wave attenuation
Wave propagation
Wireless networks
Wireless sensor networks
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Summary:The production of tomatoes in greenhouses, in addition to its relevance in nutrition and health, is an activity of the agroindustry with high economic importance in Spain, the first exporter in Europe of this vegetable. The technological updating with precision agriculture, implemented in order to ensure adequate production, leads to a deployment planning of wireless sensors with limited coverage by the attenuation of radio waves in the presence of vegetation. The well-known propagation models FSPL (Free-Space Path Loss), two-ray, COST235, Weissberger, ITU-R (International Telecommunications Union-Radiocommunication Sector), FITU-R (Fitted ITU-R), offer values with an error percentage higher than 30% in the 2.4 GHz band in relation to those measured in field tests. As a substantial improvement, we have developed optimized propagation models, with an error estimate of less than 9% in the worst-case scenario for the later benefit of farmers, consumers and the economic chain in the production of tomatoes.
ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph16101744