Molecular Entomology 2024, Vol.15, No.5, 209-220 http://emtoscipublisher.com/index.php/me 213 Figure 1 Scheme of monitoring system design (Adopted from Thereza et al., 2020) Advanced data analytics and machine learning models can further enhance this process by predicting pest outbreaks based on historical data and real-time environmental conditions. AI-powered systems can analyze vast amounts of data from multiple sources, identifying correlations between specific weather patterns and pest behavior. In a recent study, AI-based IoT systems were shown to predict pest infestations with an accuracy of over 90%, allowing for timely interventions and reducing pesticide use (Chen et al., 2020). By enabling farmers to apply pesticides only when and where necessary, data-driven decision-making helps to minimize the environmental impact of pest control, lower costs, and improve the sustainability of agricultural practices. 4.3 Advantages of integrated technologies The integration of IoT and remote sensing technologies offers numerous advantages for precision pest management in tea plantations. One of the most significant benefits is the ability to detect pest infestations early and intervene before they cause widespread damage. Remote sensing technologies, such as drones equipped with multispectral cameras, can survey large areas quickly, identifying pest hotspots by detecting changes in plant health. IoT sensors provide complementary ground-level data, such as soil moisture or temperature, which can be crucial for understanding the conditions that may lead to pest outbreaks. This integrated approach allows for more precise and targeted pest control measures, reducing the need for broad-spectrum pesticide applications that can harm the environment and lead to pesticide resistance in pests. UAVs equipped with multispectral cameras offer rapid and accurate monitoring of crop health and pest infestations, enabling more effective pest control while reducing resource wastage and improving the overall efficiency of farm management (Modica et al., 2020). Moreover, the integration of these technologies leads to cost savings and improved efficiency. Automation plays a key role, as IoT sensors and drones can monitor the plantation autonomously, reducing the need for manual inspections. In one study, the combination of IoT and drone technology in agricultural management reduced labor costs by automating tasks such as pesticide application and field monitoring (Sarangi et al., 2020). The ability to apply pesticides or other treatments only where and when they are needed also reduces resource wastage, lowering input costs and minimizing environmental impact. In addition, the data collected through these technologies can be stored and analyzed over time, helping farmers to identify long-term trends and optimize their pest management strategies for future growing seasons. By integrating IoT and remote sensing, tea plantations can achieve more sustainable, cost-effective, and efficient pest management. The integration of UAV-based
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