Digital technology and artificial intelligence, as pioneers of technological innovation, are gradually penetrating all levels of society and changing the way we work and live.
In the field of agriculture, the problem of rodent infestation has always been a major problem for farmers. Due to the lack of effective ecological control means and differences in rodent control efforts between regions, the problem of rodent infestation in farmland occurs from time to time, bringing serious losses to agricultural production. Traditional rodent pest management methods face many challenges and limitations.
However, with the application of AI, cloud computing and IoT technologies, rodent pest monitoring, prevention and control have ushered in new opportunities for development. These technologies make rodent pest monitoring more intuitive, data-driven and immediate through real-time data collection, image processing, intelligent identification and wireless transmission. Based on a large amount of data analysis, these technologies provide accurate and efficient monitoring solutions for prevention and control work, thus improving the effectiveness and efficiency of rodent pest management.
The Rodent Pest Monitoring Device is an agricultural aid that monitors the activities of field rats in real time through IoT devices. The system consists of three main components: field monitoring hardware, wireless transmission network and data processing platform.
The monitoring hardware is installed in the farmland and is capable of capturing rat activity and surrounding environment data. This information is transmitted via the wireless network to the cloud platform, which analyses the data and generates easy-to-understand charts and reports. In this way, farmers can intuitively understand the severity and location of the rat infestation, and take timely preventive and control measures to effectively reduce crop losses.
When a rat enters the monitoring box, the sensor detects and activates the camera to record video. This video data will be initially processed and then sent to a data analysis platform in the background via a wireless network. There, the system uses big data analytics to identify and classify rodent images and calculate their bio-indicators. Ultimately, the data management system translates this information into easy-to-understand charts and reports showing rodent distribution, colony structure, population changes, density trends and activity patterns. The system also provides video metadata retrieval, equipment status monitoring and real-time anomaly alerts.
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