The integration of the Internet of Things (IoT) with computer vision technology is transforming the shopping experience by empowering the expansion of smart, secure, and efficient shopping systems. This research presents an IoT-enabled trolley that scans the products automatically using computer vision and integrates secured transaction mechanisms. The proposed system influences affordable and accessible IoT devices to create a smart shopping cart that can automatically identify and scan the products using computer vision techniques. Furthermore, the system integrates advanced security protocols to ensure safe and reliable communication between IoT components. The research deliberated the design and implementation of the model, emphasizing the incorporation of RFID tags, a computer vision algorithm called faster region-based convolutional neural network (R-CNN) with long short-term memory (LSTM) network, and secured communication methods. The experimental results prove the effectiveness of the system in accurately recognizing products and streamlining the shopping process. The comparative results show that the proposed method outperforms the state-of-the-art algorithms with a mean average precision (MAP) of 89%.