Evidence map›Paper›PMID 39669441›Full record

ArticleHardwareX2024

Automated entrance monitoring to investigate honey bee foraging trips using open-source wireless platform and fiducial tags.

Diego Penaloza-Aponte, Sarabeth Brandt, Erin Dent, Robyn M Underwood, Benedict DeMoras, Selina Bruckner, Margarita M López-Uribe, Julio V Urbina

Abstract read
In one paragraph

Article in HardwareX, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  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

8 authors.

Diego Penaloza-AponteSchool of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, 16802, PA, USA.
Sarabeth BrandtSchool of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, 16802, PA, USA.
Erin DentDepartment of Geography, Texas A&M University, College Station, 77843, TX, USA.
Robyn M UnderwoodDepartment of Entomology, The Pennsylvania State University, University Park, 16802, PA, USA.
Benedict DeMorasDepartment of Entomology, Cornell University, Ithaca, NY 14853, USA.
Selina BrucknerDepartment of Entomology, The Pennsylvania State University, University Park, 16802, PA, USA.
Margarita M López-UribeDepartment of Entomology, The Pennsylvania State University, University Park, 16802, PA, USA.
Julio V UrbinaSchool of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, 16802, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Honey bee foraging is a complex behavior because it involves tens of thousands of organisms making decisions about where to collect pollen and nectar based on the quality of resources and the distance to flowers. Studying this aspect of their biology is possible through direct observations but the large number of individuals involved in this behavior makes the implementation of technologies ideal to scale up this type of study. Consequently, there is a need for instruments that can facilitate accurate assessments of honey bee foraging at the colony level. To address this need, this work aimed to develop an automated imaging system for monitoring the in-and-out activity of honey bee foragers as they walk through a customized entrance with a camera sensor at the hive entrance. We used AprilTags attached to each bee's thorax to provide unique identification numbers that allowed the system to track in-and-out events throughout the foraging season of the colony. Our design relies on low-cost Raspberry Pi computers and cameras, along with commercially off-the-shelf components, making it easily reproducible with the open-source documentation provided. We successfully deployed and evaluated our system in six locations, demonstrating consistent results. In this paper, we present the details about the development of the system, data collected from multiple colonies, and post-processing analysis from one of our apiaries. Our results highlight the system's effectiveness in monitoring honey bee trips, capturing various behaviors associate with their activities outside the colony, which lay the groundwork for future estimations of foraging distances.

Indexed as

Automated image monitoringFiducial tagsField instrumentInsects behaviorRaspberry Pi

Identifiers

PMID39669441
PMCPMC11636203

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.