Objective In order to overcome the disadvantages of traditional rodent monitoring methods which were labor-intensive, time-consuming, and of low accuracy, this article used a new portable and efficient electronic monitoring system to monitor the rodents in the target areas in real time. Methods In 2016-2017, the convolutional neural network recognition technology based on deep-learning artificial intelligence was used in laboratory to recognize rodent species and analyze and record their activities, habits, and numbers in the target areas. The system box was developed after continuous adjustment and improvement. In the field application test, a categorical data analysis was performed. Results The system had over 95.00% accuracy of rodent recognition, recording, and analysis and about 90.00% counting accuracy in laboratory, which could monitor the rodent activities within 50 m in diameter in real time with clear images. In the field application, the catching rate was significantly higher than that using sticky boards. Conclusion This portable monitoring system/box realizes the intelligent real-time rodent monitoring based on the local area network, which changes the traditional rodent monitoring methods and provides a digital and smart solution of rodent surveillance information.