Neuro-fuzzy-based smart DSS for crop specific irrigation control and SMS notification generation for precision agriculture | Zendy

Saroj Kumar Lenka | Zendy; Ambarish G. Mohapatra | Zendy

Open Access

Neuro-fuzzy-based smart DSS for crop specific irrigation control and SMS notification generation for precision agriculture

Author(s) -

Saroj Kumar Lenka,

Ambarish G. Mohapatra

Publication year - 2016

Publication title -

international journal of convergence computing

Language(s) - English

Resource type - Journals

eISSN - 2048-9137

pISSN - 2048-9129

DOI - 10.1504/ijconvc.2016.10001396

Subject(s) - irrigation , precision agriculture , agricultural engineering , fuzzy logic , agriculture , computer science , crop , control (management) , engineering , artificial intelligence , agronomy , forestry , geography , biology , ecology

A feed forward neural network and fuzzy logic-based hybrid smart decision support system (DSS) for crop specific irrigation notification and control in precision agriculture (PA) is proposed in this paper. This proposed neuro-fuzzy smart DSS can be implemented in any farm land, green-house and poly-house for efficient irrigation management and control for PA. A feed forward neural network is trained and linear regression is performed to predict soil moisture content (MC) in hourly basis. The predicted soil MC is utilised by fuzzy logic-based smart DSS model to produce SMS notification to the farmer. The proposed DSS model can work on real-time mode using National Instruments LabVIEW. This hybrid smart DSS prediction algorithm is implemented using data group of 24 cases measured in the farming land located in Bhubaneswar, the southern part of India. Crop wise evapotranspiration is also calculated using Blaney-Criddle method to notify the farmers via SMS service.

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