Abstract
Energy harvesting technology is becoming popular concerning efficient use of Internet of Things devices, which collect energy present in nature and use it to power themselves. Although the technology is eco-friendly, it is dependent on the vagaries of the surrounding environment; the amount of energy produced is sensitive to the weather and terrain, and intermittent power threatens the system’s stability. Thus, it is essential to collect data that can determine the circumstances of the surrounding environment. Furthermore, these systems should be designed efficiently for continuous energy harvesting. This efficiency can vary depending on the system’s configuration. Core voltage levels and frequencies typically influence efficiency. To maximize system efficiency, power management with an appropriate combination of controllable factors is necessary. We design an energy harvesting system for real-time data acquisition. We propose a methodology to guide the optimal operating power stage considering various adjustable factors for efficient operation. Also, we propose an adaptive operating power mode management model, which involves selecting the optimal operating power step and the transition to a low-power mode (LPM) during idle time. The proposed model was applied to an actual energy harvesting system to demonstrate its effectiveness and facilitated the operation of the harvesting system at low power.
Highlights
Internet of Things (IoT) technology is useful in a variety of areas owing to advances in computing and communication
We extend this methodology to propose an adaptive operating mode management model and apply it to an energy harvesting system implemented to verify the effectiveness of the model
The embedded device uses the MSP432P401R launch pad and the BOOSTXL-SENSORS module. Details of the latter appear in section ‘‘Sensing application for the energy harvesting system.’’ The MSP432P401R Launchpad (Texas Instruments, USA) is an ARM Cortex-M4F-based microcontroller that operates at low power
Summary
Internet of Things (IoT) technology is useful in a variety of areas owing to advances in computing and communication. Small wireless IoT devices constitute a wireless sensor network (WSN) that monitors the surrounding environment These embedded systems are scattered spatially and collect their own data on their surroundings. Power management must be performed through an appropriate and adaptive combination of controllable factors to maximize system efficiency In this regard, our previous research focused on the efficient control of the main microprocessor at the system level to reduce energy consumption. Our previous experiments demonstrated that operating energy harvesting systems at the suggesting operating power using the methodology reduced energy consumption.[6] In this article, we extend this methodology to propose an adaptive operating mode management model and apply it to an energy harvesting system implemented to verify the effectiveness of the model. The ‘‘Experimental results and analysis’’ section describes the optimal operation mode selection process in the energy harvesting system for model verification.
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