A Metacognitive Architecture for Data Analysis in Predictive, Descriptive and Prescriptive Tasks for Smart Cotton Pest Management

The use of information technology -in agriculture- plays an important role in Smart-Pest Management. Particularly, Artificial intelligence helps to identify, monitor, control and make decisions about pests in crops. In this paper, we present a new metacognitive architecture, called Metacognitive Architecture for a SmartPest Management of Cotton. Especially, this paper presents several contributions: (1) a new architecture that implements several metacognitive tasks (meta-memory, meta-learning, meta-reasoning, meta-comprehension, meta-knowledge); (2) a case study of the architecture for predictive and prescriptive problems, in the context of integrated pest management in cotton; (3) an integrated approach of data analytics and metacognition in smart systems.