Drones and AI in insect surveillance: Transforming pest forecasting systems

Abstract

Insect pests pose a severe threat to global food security, with estimated losses of 20-40% of crop yields each year. Traditional monitoring relies on manual scouting and simple weather models, often reacting too late to prevent damage. In contrast, modern systems combine Unmanned Aerial Vehicles (drones) with artificial intelligence (AI) to create rapid, high-resolution insect surveillance and forecasting. Drones equipped with advanced sensors (multispectral, thermal, RGB cameras, etc.) survey fields and orchards, while AI algorithms process the imagery and sensor data to identify pests and predict infestation trends. This synergy enables early outbreak detection and automated alerts, allowing farmers to target only affected areas and significantly reduce pesticide use. In this article, we review the theoretical foundations of AI-based image recognition and sensor data analysis, and we describe the latest drone monitoring platforms. We then examine practical applications in India and worldwide, showing how AI-enabled drones improve pest forecasting and crop protection. The benefits improved yields, resource efficiency, and faster response are highlighted, along with current challenges such as technical and regulatory hurdles. Finally, we discuss future trends in precision agriculture, illustrating how emerging drone-AI innovations will further enhance integrated pest management systems.