A Remote Monitoring System for Rodent Infestation Based on LoRaWAN

Author:

Lai Shin-Chi12ORCID,Wang Szu-Ting3,Liu Kuan-Lin4,Wu Chang-Yu1

Affiliation:

1. Department of Automation Engineering, National Formosa University, Huwei 632301, Taiwan

2. Smart Machinery and Intelligent Manufacturing Research Center, National Formosa University, Yunlin 632301, Taiwan

3. Doctor’s Program of Smart Industry Technology Research and Design, National Formosa University, Huwei 632301, Taiwan

4. Department of Electronic Engineering, National Yunlin University of Science and Technology, Douliu 64002, Taiwan

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.

Funder

Ministry of Science and Technology, Taiwan

Smart Machinery and Intelligent Manufacturing Research Center, and Higher Education SPROUT Project, National Formosa University, Yunlin, Taiwan

Ministry of Education (MOE) Female Researching Talent Cultivation Project for STEM field

MOE Talent Cultivation Project for STEAM education in the research and de-velopment of intelligent driving open source industrial technology

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference49 articles.

1. Was Shibasaburo Kitasato the Co-Discoverer of the Plague Bacillus?;Perspect Biol. Med.,1973

2. The History of Plague-Part 1: The Three Great Pandemics;Frith;J. Mil. Veterans Health,2012

3. Yersinia Pestis--Etiologic Agent of Plague;Perry;Clin. Microbiol. Rev.,1997

4. Singleton, G. (2003). Impacts of Rodents on Rice Production in Asia, IRRI.

5. Towards Sustainable Management of Rodents in Organic Animal Husbandry;Meerburg;NJAS Wagening. J. Life Sci.,2004

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