Functional modeling and parametric evaluation of components of an IoT data collection system for precision agriculture

The article considers the development of a functional model of an automated IoT monitoring data acquisition and processing system for precision agriculture tasks using the IDEF0 structural analysis methodology. The modeling object is a hardware-software complex including field IoT sensors, data transmission channels, and server processing infrastructure. A context diagram at level A-0 was constructed and decomposition to level A0 was performed, including four functional blocks: primary data acquisition from sensors, preprocessing and aggregation at the edge gateway, wireless data transmission, and server processing with control action generation. A comparative analysis of technical characteristics of three types of IoT sensors (soil moisture sensors, weather stations, UAV multispectral cameras) was conducted by accuracy, polling frequency, and power consumption parameters. Performance evaluation of three data transmission protocols (LoRa, NB-IoT, Wi-Fi) was performed by throughput, range, and latency criteria. Experimental measurements were carried out at 12 farms in Krasnodar Krai during 2019–2024. Results showed that the LoRa protocol provides the optimal ratio of transmission range (up to 11.2 km) and power consumption (42 mA in transmission mode) for field conditions. The average data processing cycle time from sensor to control command generation was 8.3 s. The developed functional model formalizes information flows and control actions in the IoT monitoring system, providing a basis for designing automated systems in agroengineering.