Abstract: Abstract: For bactrocera dorsalis field monitoring, the current method had some disadvantages: a heavy workload, low efficiency, poor reliability, low accuracy, and it could not large-scale and fast monitor the orchard pest situation in real time. Agriculture experts eager to have a solution to automatically count the number of bactrocera dorsalis and remotely observe the trapping result in real time to reduce their labor so that they could focus more on the study of the characteristics of insects. Therefore, combining the image target detection technology and the target tracking technology to develop an automated counting system by using a video image sensor would be necessary. In order to realize the real-time monitoring, the bactrocera dorsalis trapping, and a rapid diagnosis, an IOT-Based remote monitoring equipment for bactrocera dorsalis trapping was provided in this paper. The equipment included a trap monitoring device, a solar power supply device, and the monitoring control device. The trap monitoring device was comprised of a top cover, a transparent funnel, a trap bottle, a LED, and a camera; the solar energy device was comprised of a solar panel, a storage battery, and a solar panel bracket; the bactrocera dorsalis monitoring control system device was comprised of a Fit-pc controller, a 3G communication module, and the independent software for counting bactrocera dorsalis' numbers. This equipment combined machine vision technology and telecommunication technology with solar power technology. The purpose of the equipment was to achieve a whole function for bactrocera dorsalis trap monitoring with plant diseases and insect pests information collection, together with processing, transmission, and self-supply. It could monitor the trapping process and precise calculation of the number of bactrocera dorsalis anytime and anywhere, and also automatically transmit the results to the remote server or store it in a local storage card. For object extraction，this paper used an HSV color space for image filtering, then used median filtering and morphological filtering for the image to reduce white noise, eliminating holes in the target area to improve the image quality, and then divided the image into blocks based on the adjacent pixels of the image and used these blocks for Geometric feature matching, so that the bactrocera dorsalis area could be extracted. Finally, this paper used the watershed algorithm based on weight for an image segment to get the tracking object and tag the object. For bactrocera dorsalis tracking, this paper used a Kalman filter to predict the target movement position, narrowing the range of target searching and target matching, reducing the amount of calculation of the target matching; and established a cost model by using centroid Euclidean distance, survival time, and the color difference of the target between two consecutive frames; updated the cost model of each tracked target, and handled the missing target to ensure the stability and accuracy of the tracking algorithm. For bactrocera dorsalis metering, this paper studied a counting strategy for moving targets. This equipment was tested in the laboratory environment. There were 138 bactrocera dorsalis entered in the equipment in 830 s, the detected result of the system was 131, and the detection success rate was 94.9%. Also this equipment was tested in the Yangtao Park for more than a year (from November 2013 to December 2014), and the system hardware and software could work cooperatively and stably. The system stopped running only when there was a shortage of solar power, rendering it ineffective under grim weather for lack of the light. The IOT-Based remote monitoring equipment for bactrocera dorsalis trapping could automatically track and count the number of bactrocera dorsalis. It could also provide simple and effective monitoring information to the regional monitoring personnel, improve work efficiency, greatly improve the performance of the monitoring system, and had a wide range of applications in agriculture. This equipment had important practical applications.