Evidence map›Paper›PMID 37533957›Full record

ArticleEnergy science & engineering2021

Indoor light energy harvesting for battery-powered sensors using small photovoltaic modules.

Andrew Shore, John Roller, Jennifer Bergeson, Behrang H Hamadani

Abstract read
In one paragraph

Article in Energy science & engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Andrew ShoreNational Institute of Standards and Technology, Gaithersburg, MD 20899 USA.
John RollerNational Institute of Standards and Technology, Gaithersburg, MD 20899 USA.
Jennifer BergesonNational Institute of Standards and Technology, Gaithersburg, MD 20899 USA.
Behrang H HamadaniNational Institute of Standards and Technology, Gaithersburg, MD 20899 USA.

Funding

Intramural NIST DOC 9999-NIST
6 · The paper itself

Abstract

As interest in Internet-of-Things (IoT) devices like wireless sensors increases, research efforts have focused on finding ways for these sensors to self-harvest energy from the environment in which they are installed. Photovoltaic (PV) cells or mini-modules are an intuitive choice for harvesting indoor ambient light, even under low light conditions, and using it for battery charging and powering of these devices. Characterizations of battery charging, for small rechargeable batteries from low charge to full charge, have been investigated using PV mini-modules of equal area. We present battery charging results using three different PV technologies, monocrystalline silicon (c-Si), gallium-indium-phosphide (GaInP) and gallium-arsenide (GaAs) under a warm color temperature (3000 K) LED lighting at an illuminance of 1000 lx. Battery charging times are shortest for the more efficient GAInP and GaAs mini-modules whose spectral response are a better match to the LED test source, which contains mostly visible photons, and longest for the less efficient Si cells. As a demonstration, a wireless temperature sensor mote was attached to the charging circuit and operated to determine its power consumption in relation to the available charging power. The mote's maximum power draw was less than the charging power from the least efficient c-Si mini-module. Our findings affirm the feasibility of utilizing PV under typical indoor lighting conditions to power IoT devices.

Indexed as

battery chargingenergy harvestingindoor lightphotovoltaicswireless sensor

Identifiers

PMID37533957
PMCPMC10395376

What OpenQuestion holds

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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.