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This study optimizes energy efficiency in the LoRa communication module for beehive monitoring, focusing on image and audio data transfer. It investigates the effects of duty cycle calculations and spreading factor (SF) choice on power consumption and data transmission reliability. An experimental setup involved running optimized audio and image models on an Arduino Nano 33 BLE board. These models captured probabilities of different hive states—being robbed, missing queen, or active hive. The category with the highest probability indicated the current state of the hive. Optimized data results were transferred via the LoRa Grove E5 and displayed upon reception. Power and duty cycle measurements were taken on the LoRa module for spreading factors 7, 8, and 12 at set delay intervals during data transfer to the Mile sight gateway and back. Statistical analysis techniques evaluated the gathered data, revealing a high correlation between SFs, calculated duty cycles, and energy consumption profiles. These findings demonstrate the importance of optimizing duty cycles and SFs to minimize power consumption and ensure effective data transfer, thereby enhancing system reliability and reducing the environmental impact of smart bee monitoring. This promotes sustainable beekeeping practices. Moreover, the implications of this work extend beyond beekeeping, offering valuable insights into energy-efficient Internet of Things applications in environmental and agricultural monitoring.

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Investigating the Correlation Between Choice of Spreading Factor and Duty Cycle Calculations on Energy Consumption Profiles for LoRa: Insights from Optimized Image and Audio Data Transmission in Beehive Monitoring

  • 会议论文

  • 发表日期：

    2026年

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  • Ephrance Eunice Namugenyi,
  • Julianne Sansa Otim,
  • Marco Zennaro,
  • Stephen Wolthusen,
  • Mary Nsabagwa,
  • David Tugume

摘要

This study optimizes energy efficiency in the LoRa communication module for beehive monitoring, focusing on image and audio data transfer. It investigates the effects of duty cycle calculations and spreading factor (SF) choice on power consumption and data transmission reliability. An experimental setup involved running optimized audio and image models on an Arduino Nano 33 BLE board. These models captured probabilities of different hive states—being robbed, missing queen, or active hive. The category with the highest probability indicated the current state of the hive. Optimized data results were transferred via the LoRa Grove E5 and displayed upon reception. Power and duty cycle measurements were taken on the LoRa module for spreading factors 7, 8, and 12 at set delay intervals during data transfer to the Mile sight gateway and back. Statistical analysis techniques evaluated the gathered data, revealing a high correlation between SFs, calculated duty cycles, and energy consumption profiles. These findings demonstrate the importance of optimizing duty cycles and SFs to minimize power consumption and ensure effective data transfer, thereby enhancing system reliability and reducing the environmental impact of smart bee monitoring. This promotes sustainable beekeeping practices. Moreover, the implications of this work extend beyond beekeeping, offering valuable insights into energy-efficient Internet of Things applications in environmental and agricultural monitoring.