Insect pest monitoring is one of the most important steps in effective pest management, as timely detection can prevent pest populations from reaching damaging levels. Conventional monitoring methods such as visual scouting, sticky traps, light traps and pheromone traps are useful. Still, they often depend on frequent field visits and manual identification and counting of insects. Recent advances in artificial intelligence (AI), computer vision, sensors, wireless communication, and the Internet of Things (IoT) are transforming traditional traps into smart traps. These systems can automatically detect, photograph, identify, and count insects while transmitting data to farmers or researchers in near real time. Such technology can support early pest detection, improve decision-making and reduce unnecessary pesticide applications. This article highlights the development of smart insect traps, their working principles, applications in pest monitoring, selected case studies and their potential role in precision pest management.
Smart traps, AI, insect monitoring, computer vision, IoT, precision agriculture, pest management
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