Evidence map›Paper›PMID 37112136›Full record

ArticleSensors (Basel, Switzerland)2023

Investigation of Self-Powered IoT Sensor Nodes for Harvesting Hybrid Indoor Ambient Light and Heat Energy.

Heng Xiao, Nanjian Qi, Yajiang Yin, Shijie Yu, Xiangzheng Sun, Guozhe Xuan, Jie Liu, Shanpeng Xiao, Yuan Li, Yizheng Li

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Heng XiaoSchool of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China.ORCID 0009-0006-1422-9772
Nanjian QiDepartment of Precision Instrument, Tsinghua University, Beijing 100084, China.
Yajiang YinDepartment of Precision Instrument, Tsinghua University, Beijing 100084, China.
Shijie YuSchool of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China.
Xiangzheng SunDepartment of Precision Instrument, Tsinghua University, Beijing 100084, China.
Guozhe XuanDepartment of Precision Instrument, Tsinghua University, Beijing 100084, China.
Jie LiuSchool of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China.
Shanpeng XiaoChina Mobile Research Institute, Beijing 100053, China.
Yuan LiChina Mobile Research Institute, Beijing 100053, China.
Yizheng LiChina Mobile Research Institute, Beijing 100053, China.
Beijing Advanced Sciences and Innovation Center · CNBeijing Information Science & Technology University · CNChina Mobile (China) · CN

Funding

Optoelectronic Measurement and Intelligent Perception Zhongguancun Open Lab., and Space Optoelectronic Measurement and Perception Lab., Beijing Institute of Control Engineering No.LabSOMP-2022-02
6 · The paper itself

Abstract

Sensor nodes are critical components of the Internet of Things (IoT). Traditional IoT sensor nodes are typically powered by disposable batteries, making it difficult to meet the requirements for long lifetime, miniaturization, and zero maintenance. Hybrid energy systems that integrate energy harvesting, storage, and management are expected to provide a new power source for IoT sensor nodes. This research describes an integrated cube-shaped photovoltaic (PV) and thermal hybrid energy-harvesting system that can be utilized to power IoT sensor nodes with active RFID tags. The indoor light energy was harvested using 5-sided PV cells, which could generate 3 times more energy than most current studies using single-sided PV cells. In addition, two vertically stacked thermoelectrical generators (TEG) with a heat sink were utilized to harvest thermal energy. Compared to one TEG, the harvested power was improved by more than 219.48%. In addition, an energy management module with a semi-active configuration was designed to manage the energy stored by the Li-ion battery and supercapacitor (SC). Finally, the system was integrated into a 44 mm × 44 mm × 40 mm cube. The experimental results showed that the system was able to generate a power output of 192.48 µW using indoor ambient light and the heat from a computer adapter. Furthermore, the system was capable of providing stable and continuous power for an IoT sensor node used for monitoring indoor temperature over a prolonged period.

Indexed as

hybrid energy harvestingInternet of Things (IoT)self-poweredsolar energythermoelectric

Identifiers

PMID37112136
PMCPMC10142936
OpenAlexW4363678819

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.