(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Samaratunge, U.S.S.; Amarasinghe, D.H.L.; Kirindegamaarachchi, M.C.; Asanka, B.L.
Technology has become a vital aspect for various
functional purposes throughout the world and some industries
like floriculture have not adapted technology to solve and
facilitate currently facing problems and provide the supply to
the demand. Consequently, we have identified and implemented
a solution that will address major aspects of such industry
barriers. To address these major aspects we proposed a system
Smart Intelligent Floriculture Assistant Agent (SIFAA), which
uses expert knowledge with solutions and guideline such as
identify diseases based on deep learning techniques. It also
suggests remedies for diseases based on the expert knowledge,
recommend best products for customers by using
Reinforcement Learning (RL) technique, motivate cultivators
by using demand forecasting, and apply feature engineering by
using Linear Regression (LR) and ensemble advance LightGBM
Regressors techniques.
