Energy-autonomous wireless sensor nodes (WSNs) face challenges in environmental monitoring due to energy constraints, transmission efficiency, and regulatory compliance of the used transmission standard. This paper presents a LoRaWAN payload optimization strategy addressing these limitations for a star-type network of energy-autonomous WSNs. By leveraging intelligent batching, data type optimization, and measurement aggregation, consecutive cycles are combined into single frames, thus fully exploiting the full capability of allowed data rates in the EU868 frequency band. Fixed-point representation and redundancy elimination reduce payload size by 31.8% (88→57 bytes). Transmission energy drops by 50% (3552→1776 mJ/day), with full temporal resolution preserved. Duty cycle utilization decreases from 9.6% to 4.8%, lowering collision probability and enhancing scalability in dense deployments.
Karunakaran et al. (Mon,) studied this question.
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