Evidence map›Paper›PMID 37177388›Full record

ArticleSensors (Basel, Switzerland)2023

A Remote Monitoring System for Rodent Infestation Based on LoRaWAN.

Shin-Chi Lai, Szu-Ting Wang, Kuan-Lin Liu, Chang-Yu Wu

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Shin-Chi LaiDepartment of Automation Engineering, National Formosa University, Huwei 632301, Taiwan.ORCID 0000-0003-0011-3649
Szu-Ting WangDoctor's Program of Smart Industry Technology Research and Design, National Formosa University, Huwei 632301, Taiwan.
Kuan-Lin LiuDepartment of Electronic Engineering, National Yunlin University of Science and Technology, Douliu 64002, Taiwan.
Chang-Yu WuDepartment of Automation Engineering, National Formosa University, Huwei 632301, Taiwan.
National Formosa University · TWNational Yunlin University of Science and Technology · TW

Funding

Ministry of Science and Technology 109-2221-E-150-043Ministry of Science and Technology 110-2221-E-150-045National Science and Technology Council 111-2221-E-150-002-MY2
6 · The paper itself

Abstract

Rodent infestations are a common problem that can result in several issues, including diseases, damage to property, and crop loss. Conventional methods of controlling rodent infestations often involve using mousetraps and applying rodenticides manually, leading to high manpower expenses and environmental pollution. To address this issue, we introduce a system for remotely monitoring rodent infestations using Internet of Things (IoT) nodes equipped with Long Range (LoRa) modules. The sensing nodes wirelessly transmit data related to rodent activity to a cloud server, enabling the server to provide real-time information. Additionally, this approach involves using images to auxiliary detect rodent activity in various buildings. By capturing images of rodents and analyzing their behavior, we can gain insight into their movement patterns and activity levels. By visualizing the recorded information from multiple nodes, rodent control personnel can analyze and address infestations more efficiently. Through the digital and quantitative sensing technology proposed at this stage, it can serve as a new objective indicator before and after the implementation of medication or other prevention and control methods. The hardware cost for the proposed system is approximately USD 43 for one sensor module and USD 17 for one data collection gateway (DCG). We also evaluated the power consumption of the sensor module and found that the 3.7 V 18,650 Li-ion batteries in series can provide a battery life of two weeks. The proposed system can be combined with rodent control strategies and applied in real-world scenarios such as restaurants and factories to evaluate its performance.

Indexed as

ComputersInternet of ThingsData CollectionElectric Power SuppliesEnvironmental PollutionInternet of ThingsLoRaLoRaWANremote monitorrodent monitor

Identifiers

PMID37177388
PMCPMC10180839
OpenAlexW4366828989

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.