An Automated Pest Identification and Classification in Crops Using Artificial Intelligence—A State-of-Art-Review
Jose Mekha, V Parthasarathy.
Abstract
Agriculture in India remains the nation’s livelihood and a deciding factor for the Indian economy. Among the challenges the planters face from seeding to harvesting, the infestation due to pests creates excellent concern with a significant impact on productivity. Researchers are making frequent attempts and trying to provide solutions using modern tools and techniques. The recent advancement in research through artificial intelligence (AI) and derivatives such as machine learning (ML) and deep learning (DL) helps to a greater extent to the efforts of circumventing the pest infestation with the timely detection and intimation for possible remediation. This article presents a comprehensive report of seminal works that have been consequential in identifying infestation in crops as the use of ML and DL in pest detection and classification by various researchers. Further, a report on the examination of various ML and DL techniques applied by the researchers for pest with accuracy has been presented to explore further possibilities in applying ML and DL techniques for pest control. Finally, this article suggests the scope to incinerate the pest infestation with the advent of artificial intelligence algorithms.