TY - GEN
T1 - Standalone fuzzy logic controller applied to greenhouse horticulture using internet of things
AU - Carrasquilla-Batista, Arys
AU - Chacón-Rodríguez, Alfonso
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - In this paper, a standalone Fuzzy Logic Controller (FLC) with Internet of Things (IoT) capabilities is developed for analysis and linguistic decision making about fertigation (fertilizers + water) in a greenhouse. The following input variables are evaluated: automatic drainage measuring, Electrical Conductivity (EC) and pH values of drainage. In order to determine if water content is easily available to crops, the lexical uncertainty given by 'easily available' was quantified into a numerical value, as output is given a scalar value associated to fertigation. The result is a controller that embeds structural human knowledge about irrigation scheduling into an analytic FLC, in order to provide agricultural scientists with quick access to a particular crop's main production and growth related variables, and allowing for future data driven decisions on the spot. The controller was validated with real data collected from two particular crops, cucumber and greenpepper, using remote sensors connected to Internet. Final results seem support the continuing development of affordable yet efficient applications based on FLC and IoT, that provides effective production tools for horticulture producers in developing countries.
AB - In this paper, a standalone Fuzzy Logic Controller (FLC) with Internet of Things (IoT) capabilities is developed for analysis and linguistic decision making about fertigation (fertilizers + water) in a greenhouse. The following input variables are evaluated: automatic drainage measuring, Electrical Conductivity (EC) and pH values of drainage. In order to determine if water content is easily available to crops, the lexical uncertainty given by 'easily available' was quantified into a numerical value, as output is given a scalar value associated to fertigation. The result is a controller that embeds structural human knowledge about irrigation scheduling into an analytic FLC, in order to provide agricultural scientists with quick access to a particular crop's main production and growth related variables, and allowing for future data driven decisions on the spot. The controller was validated with real data collected from two particular crops, cucumber and greenpepper, using remote sensors connected to Internet. Final results seem support the continuing development of affordable yet efficient applications based on FLC and IoT, that provides effective production tools for horticulture producers in developing countries.
KW - Agriculture in protected environments
KW - Fuzzy logic controller
KW - Greenhouse horticulture
KW - Internet of things
UR - http://www.scopus.com/inward/record.url?scp=85078202131&partnerID=8YFLogxK
U2 - 10.1109/IESTEC46403.2019.00108
DO - 10.1109/IESTEC46403.2019.00108
M3 - Contribución a la conferencia
AN - SCOPUS:85078202131
T3 - Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019
SP - 574
EP - 579
BT - Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Engineering, Sciences and Technology Conference, IESTEC 2019
Y2 - 9 October 2019 through 11 October 2019
ER -