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A Remote Monitoring System for Rodent Infestation Based on LoRaWAN
Shin-Chi Lai1,2, Szu-Ting Wang3, Kuan-Lin Liu4
1Department of Automation Engineering, National Formosa University, Huwei 632301, 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.
Insights
This study introduces an Internet of Things (IoT) system using Long Range (LoRa) modules for remote rodent monitoring. The system provides real-time data and image analysis to improve rodent control efficiency and reduce environmental impact.
Area of Science:
- Pest Management
- Internet of Things (IoT)
- Wireless Sensor Networks
Background:
- Rodent infestations cause significant disease, property, and crop damage.
- Conventional control methods are labor-intensive and environmentally harmful.
- Need for efficient, remote monitoring solutions in pest control.
Purpose of the Study:
- To develop and evaluate an IoT-based system for remote rodent infestation monitoring.
- To utilize Long Range (LoRa) modules for wireless data transmission.
- To integrate image analysis for enhanced rodent activity detection.
Main Methods:
- Deployment of IoT sensing nodes with LoRa modules for wireless data transmission.
- Cloud server integration for real-time data processing and visualization.
- Image capture and analysis to supplement activity data and understand behavior patterns.
Main Results:
- The system enables remote, real-time monitoring of rodent activity.
- Image analysis provides insights into rodent movement and activity levels.
- Hardware costs are approximately $43 per sensor module and $17 per gateway.
- Sensor modules offer a battery life of two weeks with specified Li-ion batteries.
Conclusions:
- The proposed IoT system offers an objective, digital method for assessing rodent infestations.
- It enhances the efficiency of rodent control personnel through data visualization and analysis.
- The system is cost-effective and suitable for real-world applications in environments like restaurants and factories.
