Unravelling the use of artificial intelligence in management of insect pests

Abstract

As per the FAO, the insect pest causes 30 to 40 percent loss every year across the globe. The identification, classification and management of insect pest is very important to avoid significant loss. Practicing the above process by adopting manual methods are time consuming and less effective to achieve the task. The traditional methods often fall short in addressing dynamic pest behaviours, resulting in crop losses and increased chemical usage. Therefore, adoption of the Artificial Intelligence (AI) techniques in pest identification and management act as a good substitute that arises from the challenges posed by evolving pest populations and the desire for sustainable agricultural practices. AI offers a transformative approach by utilizing advanced algorithms to analyse intricate data patterns from numerous sources like sensors and imagery. This enables accurate pest identification, early detection, and predictive modelling, enhancing decision-making for pest control, by minimizing indiscriminate pesticide application and optimizing interventions. AI not only reduces economic losses but also promotes eco-friendly strategies for efficient and resilient pest management systems. The present review is an endeavour to explain the intermingling and future scope of AI in insect pest management.

Keywords

• Artificial Intelligence
• Machine and deep learning
• Sensors
• Pest detection and classification
• Monitoring
• Decision making