A Remote Monitoring System for Rodent Infestation Based on LoRaWAN

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 9; p. 4185
• Main Authors: Lai, Shin-Chi, Wang, Szu-Ting, Liu, Kuan-Lin, Wu, Chang-Yu
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 22.04.2023; MDPI
• Subjects: Analysis; Anticoagulants; Bandwidths; Computers; Control methods; Crop losses; Data Collection; Disease transmission; Electric Power Supplies; Energy consumption; Environmental Pollution; Internet of Things; Lithium-ion batteries; LoRa; LoRaWAN; Maintenance costs; Monitoring systems; Nodes; Pest control; Poisons; Property damage; Radio communications; remote monitor; Remote monitoring; rodent monitor; Rodents; Rural areas; Sensors; Spread spectrum; Technology; Wireless communications; Internet of Things; LoRa; LoRaWAN; rodent monitor; remote monitor
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23094185

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.