Sensors Driven AI-Based Agriculture Recommendation Model for Assessing Land Suitability

• DOI: 10.3390/s19173667
• Publication Date: 2019-08-26T08:38:23Z
• Authors: Durai Raj Vincent; N Deepa; Dhivya Elavarasan; Kathiravan Sriniv...; Sajjad Hussain Ch...; Celestine Iwendi
• Keywords: Arable land; Precision Agriculture; Multilayer perceptron; Perceptron

The world population is expected to grow by another two billion in 2050, according the survey taken Food and Agriculture Organization, while arable area likely only 5%. Therefore, smart efficient farming techniques are necessary improve agriculture productivity. land suitability assessment one of essential tools for development. Several new technologies innovations being implemented as an alternative collect process farm information. rapid development wireless sensor networks has triggered design low-cost small devices with Internet Things (IoT) empowered a feasible tool automating decision-making domain agriculture. This research proposes expert system integrating Artificial Intelligence systems such neural Multi-Layer Perceptron (MLP) suitability. proposed will help farmers assess cultivation terms four decision classes, namely more suitable, moderately unsuitable. determined based on input collected from various devices, which used training system. results obtained using MLP hidden layers found be effective multiclass classification when compared other existing model. trained model evaluating future assessments classifying after every cultivation.