This work uses AI edge computing technology, which combines the SSD recognition model with an FPN and replaces the SSD image pyramid with a feature pyramid to make the recognition of small objects such as medicines more sensitive to improve the recognition accuracy. Moreover, this work also combines with the drug counting algorithm to count the number of medications in the medicine bag.This work uses the edge computing method to identify drugs in the AI embedded system module in the device. AI performs the image recognition results output by Object Detection and filters the frame selection area by 90% through the algorithm to filter the objects, so as to obtain more accurate Count the number of medicines. When the medicines are placed in a medicine bag to block each other, this work uses OpenCV to perform Hough conversion on the photos to calculate the correct amount.The goal of this work is to integrate into the current standard drug dispensing process in the hospital. This work can assist the dispensing staff in checking whether the drug name, dose, and quantity in the medicine bag are consistent with the prescription of the medicine bag, thereby reducing the error rate of manual inspection and improving the efficiency of dispensing verification. A medical center in the south cooperated to verify the actual adjustment.