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technology","award":["111-I-071-2"],"award-info":[{"award-number":["111-I-071-2"]}]},{"name":"MOE Talent Cultivation Project for STEAM education in the research and de-velopment of intelligent driving open source industrial technology","award":["111-I-071-1"],"award-info":[{"award-number":["111-I-071-1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s23094185","type":"journal-article","created":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T03:04:08Z","timestamp":1682305448000},"page":"4185","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Remote Monitoring System for Rodent Infestation Based on LoRaWAN"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0011-3649","authenticated-orcid":false,"given":"Shin-Chi","family":"Lai","sequence":"first","affiliation":[{"name":"Department of Automation Engineering, National Formosa University, Huwei 632301, Taiwan"},{"name":"Smart Machinery and Intelligent Manufacturing Research Center, National Formosa University, Yunlin 632301, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Szu-Ting","family":"Wang","sequence":"additional","affiliation":[{"name":"Doctor\u2019s Program of Smart Industry Technology Research and Design, National Formosa University, Huwei 632301, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kuan-Lin","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, National Yunlin University of Science and Technology, Douliu 64002, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang-Yu","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Automation Engineering, National Formosa University, Huwei 632301, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1353\/pbm.1973.0034","article-title":"Was Shibasaburo Kitasato the Co-Discoverer of the Plague Bacillus?","volume":"16","year":"1973","journal-title":"Perspect Biol. 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