In the context of increasing technogenic risks and the need for rapid response to radiation-related emergencies, mobile environmental monitoring systems are becoming a critical component of national safety and public health protection. This article presents a comprehensive approach to modeling the processing of spatially distributed environmental data collected by unmanned aerial vehicles (UAVs) equipped with IoT-based radiation sensors. The proposed system architecture is based on a three-tier client-server model that separates data acquisition, processing, and visualization tasks. The UAV platform integrates lightweight, energy-efficient IoT sensors capable of real-time data transmission, including geolocation and radiation dose measurements. The core contribution of this research lies in the development of a data processing algorithm tailored for dynamic, irregularly spaced measurements. The algorithm includes noise filtering, temporal and spatial aggregation, and spatial interpolation using the Inverse Distance Weighting (IDW) method. The IDW technique was selected for its simplicity, transparency, and high sensitivity to local variations, making it suitable for generating det
📖 افتح في inklap 🔗 DOI 📮 اطلب بحثاً