Molecular Entomology 2024, Vol.15, No.5, 209-220 http://emtoscipublisher.com/index.php/me 210 The integration of the Internet of Things (IoT) and remote sensing technologies has revolutionized agriculture, particularly in the realm of precision farming. IoT refers to a network of physical devices, such as sensors and cameras, connected to the internet, enabling real-time data collection and transmission. In agriculture, these devices can monitor critical factors like soil moisture, temperature, humidity, and pest activity. Farmers can access this information remotely, allowing for continuous monitoring and timely interventions. For instance, soil sensors can trigger automated irrigation systems, while pest detection cameras can alert farmers to potential infestations, enabling quick responses to prevent widespread damage (Sawant et al., 2017). Remote sensing, on the other hand, involves the use of satellite or drone-based imaging to monitor crops over large areas. This technology can detect early signs of pest infestation or stress in plants by analyzing changes in color, temperature, and other factors invisible to the naked eye. By combining data from IoT devices with high-resolution remote sensing imagery, farmers can make more informed decisions regarding pest management, irrigation, and crop health. These technologies not only reduce the need for manual inspections, which are time-consuming and labor-intensive, but also allow for more precise application of pesticides and fertilizers, further enhancing sustainability (Filho et al., 2019). This study explores the use of Internet of Things (IoT) and remote sensing technologies in improving Precision Pest Management (PPM) for tea plantations. The main objective is to evaluate how these technologies can enhance pest control strategies, reduce pesticide use, and support sustainable agricultural practices. IoT devices enable real-time monitoring of pest activity and crop health, while remote sensing technologies, such as drones and satellites, provide large-scale monitoring and early detection of pest infestations. The key objectives include assessing the effectiveness of IoT-based pest monitoring systems in tea plantations, analyzing how these technologies can reduce pesticide use through targeted interventions, and evaluating the economic benefits for tea growers, such as cost savings and improved yields. By focusing on real-time data and precision interventions, this study aims to offer practical insights for tea farmers to adopt advanced technologies, ultimately demonstrating how precision agriculture can enhance both productivity and sustainability in tea farming. 2 IoT in Tea Plant Protection 2.1 Sensors for pest detection In the context of tea plant protection, sensors play a pivotal role in detecting pest infestations early, thus enabling timely interventions. IoT-based sensors can monitor various environmental factors and insect activities in tea plantations. These sensors include motion detectors, image-based sensors, and multispectral imaging systems, which provide accurate and continuous data on pest populations. For example, camera-equipped traps can capture high-resolution images of insects, which are then processed through machine learning algorithms for identification and classification. This allows for real-time detection of pest outbreaks, which is critical for minimizing damage to crops and reducing the need for widespread pesticide applications (Chen and zhao, 2024). The use of AI in conjunction with sensors enhances the precision of pest identification. Advanced systems are now able to differentiate between species of pests, thus allowing for targeted treatment rather than broad-spectrum pesticide use. A comparative study of camera- and sensor-based traps showed that integrating sensors with wireless communication technologies significantly improves detection accuracy and operational efficiency in pest management (Passias et al., 2023). Moreover, using multispectral imaging helps in detecting smaller and camouflaged pests, which are often missed by traditional monitoring techniques. By enhancing early pest detection, sensor-based systems reduce crop losses and pesticide reliance, contributing to more sustainable tea cultivation practices. 2.2 Real-time monitoring and data collection Real-time monitoring enabled by IoT technologies is critical in modern tea plant protection strategies. In tea plantations, IoT-based sensors collect continuous data on environmental conditions, such as humidity, temperature, and soil moisture, as well as pest activity. This data is transmitted wirelessly to cloud platforms, where it is analyzed in real time to provide actionable insights to farmers. For example, in Indonesia’s tea plantations, a smart farming system that utilizes LoRa technology allows for efficient wireless data transmission over long distances, ensuring that farmers in remote areas can still monitor and manage their crops in real-time (Thereza et al., 2020).
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