The paper proposes a comprehensive concept of energy modeling for wireless sensor networks (WSNs). A structural model of the node operating cycle is introduced, distinguishing between full and partial cycles, which enables clear separation of background and active energy consumption and improves modeling accuracy. A new multifactor mathematical model of WSN energy consumption over the vegetation period is developed and formalized simultaneously in scalar and matrix forms. This provides a unified description of network nodes, ensures network scalability, and accounts for variable operating modes. Based on the multifactor model, a software application for predicting the energy consumption of a wireless sensor network, “Energy Consumption Analyzer”, has been developed. The Friis transmission equation is specialized, and a modified Weissberger model is calibrated to describe signal attenuation in a vegetation environment. On the basis of these models, a practically applicable signal attenuation model for vegetation environments of the orchard type is proposed, specifically adapted to the impact of this type of environment on radio signal propagation. Empirical modeling based on experimental data and the synthesis of theoretical and empirical models are performed, enabling the solution of the inverse problem of determining the minimum required transmission power to ensure a given quality of service (QoS) and yielding an analytical model of adaptive power control. A dynamic model of WSN energy consumption is developed, establishing the relationship between energy expenditure and communication quality. A daily optimization coefficient for hierarchical power control is proposed, which forms the basis for a method to improve the energy efficiency of wireless sensor networks. Keywords: wireless sensor networks, sensor node, radio signal, signal attenuation, energy consumption, modeling, empirical models, energy efficiency, precision agriculture.
Hanna Antonova (Fri,) studied this question.