A Real-World Evaluation of Energy Budget Estimation Algorithms for Autonomous Long Range IoT Nodes

Gléonec, Philip-Dylan; Ardouin, Jérémy; Gautier, Matthieu; Berder, Olivier

doi:10.1109/ict.2018.8464885

Cited by 3 publications

(2 citation statements)

References 8 publications

(14 reference statements)

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“…Moreover, as the delay between two EBE executions can be long, it is necessary to use a model-free EBE algorithm that can converge towards an optimized duty cycle in a few executions. However, previous work [ 41 ] has shown that EBE algorithms have low performance differences when they are properly optimized, which enables the use of simple algorithms to compute

. For this study, LQ-tracker [ 25 ] is used as the EBE algorithm, since it provides good performance without requiring its parameters to be tuned.…”

Section: Multi-source Multi-task Node Architecturementioning

confidence: 99%

Energy Allocation for LoRaWAN Nodes with Multi-Source Energy Harvesting

Gléonec

Ardouin²,

Gautier

et al. 2021

Sensors

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Many connected devices are expected to be deployed during the next few years. Energy harvesting appears to be a good solution to power these devices but is not a reliable power source due to the time-varying nature of most energy sources. It is possible to harvest energy from multiple energy sources to tackle this problem, thus increasing the amount and the consistency of harvested energy. Additionally, a power management system can be implemented to compute how much energy can be consumed and to allocate this energy to multiple tasks, thus adapting the device quality of service to its energy capabilities. The goal is to maximize the amount of measured and transmitted data while avoiding power failures as much as possible. For this purpose, an industrial sensor node platform was extended with a multi-source energy-harvesting circuit and programmed with a novel energy-allocation system for multi-task devices. In this paper, a multi-source energy-harvesting LoRaWAN node is proposed and optimal energy allocation is proposed when the node runs different sensing tasks. The presented hardware platform was built with off-the-shelf components, and the proposed power management system was implemented on this platform. An experimental validation on a real LoRaWAN network shows that a gain of 51% transmitted messages and 62% executed sensing tasks can be achieved with the multi-source energy-harvesting and power-management system, compared to a single-source system.

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. For this study, LQ-tracker [ 25 ] is used as the EBE algorithm, since it provides good performance without requiring its parameters to be tuned.…”

Section: Multi-source Multi-task Node Architecturementioning

confidence: 99%

Energy Allocation for LoRaWAN Nodes with Multi-Source Energy Harvesting

Gléonec

Ardouin²,

Gautier

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…To sum up, there is currently no commercial LoRa-based platform powered by energy harvesting but only few research works that mainly focus on the validation of the SW (energy manager) part [18,20] and do not address the dimensioning of the hardware elements [7].…”

Section: Related Work On Energy Harvesting For Long-range Platformsmentioning

confidence: 99%

The Smaller the Better: Designing Solar Energy Harvesting Sensor Nodes for Long-Range Monitoring

Mabon

Gautier

Vrigneau

et al. 2019

Wireless Communications and Mobile Computing

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Emerging Low Power Wide Area Networks (LPWAN) represent a real breakthrough for monitoring applications, since they give the possibility to generate and transmit data over dozens of kilometers while consuming few energy. To further increase the autonomy of such wireless systems, the present paper proposes an original methodology to correctly dimension the key elements of an energy autonomous node, namely, the supercapacitor and the battery that mainly give the form factor of the node. Among the LPWAN candidates, LoRa is chosen for real field experiments with a custom wireless platform that proves its energy neutrality over a finite horizon. Different LoRa configurations are explored, leading to adequate dimensioning. As an example, it is shown that, for the same quality of service, the size of the solar panel needed to keep a LoRa node autonomous in the South of France is less than half of the size required in North of France.

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Adapting Quality of Service of Energy‐Harvesting IoT Devices

Gautier¹,

Berder²

2022

Intelligent Security Management and Control in the IoT

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A Real-World Evaluation of Energy Budget Estimation Algorithms for Autonomous Long Range IoT Nodes

Cited by 3 publications

References 8 publications

Energy Allocation for LoRaWAN Nodes with Multi-Source Energy Harvesting

Energy Allocation for LoRaWAN Nodes with Multi-Source Energy Harvesting

The Smaller the Better: Designing Solar Energy Harvesting Sensor Nodes for Long-Range Monitoring

Adapting Quality of Service of Energy‐Harvesting IoT Devices

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