1. An Adaptive Sampling Period Approach for Management of IoT Energy Consumption: Case Study Approach.
- Author
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Rodriguez-Pabon, Carlos, Riva, Guillermo, Zerbini, Carlos, Ruiz-Rosero, Juan, Ramirez-Gonzalez, Gustavo, and Corrales, Juan Carlos
- Subjects
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ENERGY management , *VALUE chains , *INTERNET of things , *AGRICULTURAL processing , *ENERGY consumption , *ADAPTIVE natural resource management , *SAMPLING methods - Abstract
The Internet of Things (IoT) opens opportunities to monitor, optimize, and automate processes into the Agricultural Value Chains (AVC). However, challenges remain in terms of energy consumption. In this paper, we assessed the impact of environmental variables in AVC based on the most influential variables. We developed an adaptive sampling period method to save IoT device energy and to maintain the ideal sensing quality based on these variables, particularly for temperature and humidity monitoring. The evaluation on real scenarios (Coffee Crop) shows that the suggested adaptive algorithm can reduce the current consumption up to 11% compared with a traditional fixed-rate approach, while preserving the accuracy of the data. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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