Journal of Advances in Biology & Biotechnology

Insect pests remain a major challenge to agricultural production because they reduce crop yields, affect produce quality, and increase dependence on chemical control measures. Conventional pest management practices, including manual field scouting and repeated pesticide applications, are often labour-intensive, time-consuming, and less effective for the early detection of rapidly changing pest populations. This review discusses recent innovations in insect pest management, with an emphasis on the role of artificial intelligence, smart sensors, precision agriculture, and related digital technologies. Artificial intelligence supports pest identification, population monitoring, risk prediction, and decision-making through machine learning, computer vision, image recognition, and predictive analytics. When integrated with drones, automated traps, remote sensing platforms, Internet of Things devices, and sensor networks, these tools can provide real-time information on pest occurrence, crop condition, soil status, and environmental variables. Such information can support timely interventions, improve pesticide-use efficiency, and reduce unnecessary chemical applications. The review also considers nano pesticides as emerging pest control tools that may improve pesticide delivery, controlled release, and target specificity. However, their environmental fate, toxicity, regulatory approval, and field-level adoption require careful evaluation. Artificial intelligence-based pest management offers important opportunities for sustainable agriculture, but wider adoption depends on reliable datasets, technical infrastructure, farmer training, affordability, data security, and context-specific decision support. Overall, combining artificial intelligence with smart monitoring and precision farming technologies may improve the accuracy, efficiency, and sustainability of insect pest management systems.