Evidence map›Paper›PMID 39409526›Full record

ReviewSensors (Basel, Switzerland)2024

Technologies and Solutions for Cattle Tracking: A Review of the State of the Art.

Saúl Montalván, Pablo Arcos, Pablo Sarzosa, Richard Alejandro Rocha, Sang Guun Yoo, Youbean Kim

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. River transport of cattle in northern Brazil - a systematic review.Tropical animal health and production · 2026
    Pooled it
  2. Review
  3. Review
  4. Article
  5. 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

6 authors.

Saúl MontalvánSmart Lab, Escuela Politécnica Nacional, Quito 170143, Ecuador.
Pablo ArcosSmart Lab, Escuela Politécnica Nacional, Quito 170143, Ecuador.ORCID 0009-0008-6442-2858
Pablo SarzosaSmart Lab, Escuela Politécnica Nacional, Quito 170143, Ecuador.
Richard Alejandro RochaSmart Lab, Escuela Politécnica Nacional, Quito 170143, Ecuador.ORCID 0009-0004-5646-1700
Sang Guun YooSmart Lab, Escuela Politécnica Nacional, Quito 170143, Ecuador.ORCID 0000-0003-1376-3843
Youbean KimDepartment of Semiconductor Engineering, Myongji University, Yongin-si 17058, Republic of Korea.ORCID 0009-0008-3317-9859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article presents a systematic literature review of technologies and solutions for cattle tracking and monitoring based on a comprehensive analysis of scientific articles published since 2017. The main objective of this review is to identify the current state of the art and the trends in this field, as well as to provide a guide for selecting the most suitable solution according to the user's needs and preferences. This review covers various aspects of cattle tracking, such as the devices, sensors, power supply, wireless communication protocols, and software used to collect, process, and visualize the data. The review also compares the advantages and disadvantages of different solutions, such as collars, cameras, and drones, in terms of cost, scalability, precision, and invasiveness. The results show that there is a growing interest and innovation in livestock localization and tracking, with a focus on integrating and adapting various technologies for effective and reliable monitoring in real-world environments.

Indexed as

animal monitoringcameracattle trackingdroneIndustry 4.0IoTlocationsolutions

Identifiers

PMID39409526
PMCPMC11479337

What OpenQuestion holds

Textmetadata
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.