Abstract

The integration of unmanned aerial vehicles (UAVs) with artificial intelligence (AI) and Internet of Things (IoT) technologies has revolutionized precision agriculture by enabling targeted delivery of fertilizers, pesticides, and nutrients. Drone-based precision spraying systems facilitate accurate, site-specific interventions, minimizing agrochemical usage, reducing environmental contamination, and improving crop productivity. Advanced sensing modalities, including multispectral, hyperspectral, and thermal imaging, combined with ground-based soil and weather sensors, provide high-resolution spatial and temporal data that inform intelligent spraying strategies. AI algorithms, particularly machine learning and reinforcement learning models, optimize flight paths, detect crop stress, and support adaptive variable-rate spraying. IoT-enabled platforms ensure real-time connectivity, data fusion, and remote mission management, fostering an integrated, autonomous ecosystem for sustainable farming. This chapter explores the evolution, system architecture, sensor technologies, AI-driven decision-making, IoT integration, and operational considerations of drone-based spraying platforms, highlighting research gaps, technological advancements, and future directions for scalable, high-efficiency agricultural interventions. The findings underscore the transformative potential of UAV-assisted precision spraying in enhancing resource efficiency, crop health, and environmental sustainability across diverse agroecological settings.

Introduction

The global demand for sustainable agriculture has driven the integration of digital technologies into traditional farming systems, creating pathways for precise and efficient crop management [1]. Conventional spraying methods for fertilizers, pesticides, and nutrients are often characterized by overapplication, uneven distribution, and high operational costs, leading to negative environmental consequences such as soil degradation, water contamination, and reduced biodiversity [2]. In this context, unmanned aerial vehicles (UAVs), commonly referred to as drones, have emerged as transformative tools in precision agriculture [3]. Equipped with advanced sensors and automation capabilities, drones can conduct targeted spraying operations, optimizing chemical usage while maintaining high coverage accuracy [4]. By reducing manual intervention, drone-based spraying systems also mitigate health risks associated with chemical exposure, enabling safer operational environments. The integration of UAVs within precision agriculture frameworks reflects a broader shift toward data-driven, autonomous farming, where crop inputs are applied based on real-time field conditions rather than uniform estimations. This paradigm enhances both economic and environmental sustainability, positioning drone spraying as a cornerstone of modern agronomic practices [5].

The effectiveness of drone-assisted precision spraying is largely determined by the integration of advanced sensing technologies and artificial intelligence algorithms [6]. Multispectral, hyperspectral, and thermal imaging sensors mounted on UAVs capture high-resolution data on crop health, nutrient status, and pest infestations, enabling early detection of stress and disease [7]. Ground-based soil and weather sensors complement aerial observations by providing localized measurements of soil moisture, temperature, pH, and ambient environmental conditions. Data fusion from these heterogeneous sources allows the generation of detailed prescription maps, guiding site-specific interventions that minimize input wastage and maximize crop productivity [8]. Artificial intelligence techniques, including machine learning and reinforcement learning, process these complex datasets to identify patterns, predict disease outbreaks, and optimize flight paths [9]. By leveraging AI, UAVs can adjust spraying parameters dynamically in response to real-time environmental changes, ensuring precision and efficacy across heterogeneous agricultural landscapes. Such intelligent systems elevate drone platforms from simple mechanical sprayers to integrated decision-support tools, capable of autonomous, adaptive operations [10].

The role of the Internet of Things (IoT) in UAV-based precision spraying extends the scope and functionality of drone operations by creating connected ecosystems for real-time data exchange [11]. IoT-enabled devices, including wireless soil probes, weather stations, and drone telemetry modules, transmit continuous information to cloud-based platforms, enabling centralized monitoring and remote decision-making [12]. Edge and cloud computing allow high-speed processing of large volumes of spatial, temporal, and environmental data, facilitating rapid generation of spraying prescriptions and flight adjustments [13]. This connectivity also enhances operational safety, providing automatic alerts for deviations in flight paths, equipment malfunctions, or environmental risks [14]. The combination of IoT and UAV technology creates a closed-loop system, where sensing, analysis, and action occur in an integrated, automated cycle. By linking aerial and terrestrial sensors with predictive analytics, drone spraying platforms achieve higher reliability, scalability, and precision than conventional methods, supporting the broader objectives of smart farming [15].