Efficiency Analysis of Barcode and QR Code in Context to Pharmaceutical Drug Label: An Implementation Approach with Open-Source Libraries and PCB Technology

The government has mandated the inclusion of QR codes on the packaging of 300 medicines to combat counterfeit drugs. This amendment, effective from August 1, 2023, covers a range of medications, from pain relief to vitamin supplements. Enforced by the central government, this amendment to the Drug and Cosmetics Act of 1940 requires pharmaceutical companies to incorporate QR codes on medicine packaging. The objective is to enhance consumer empowerment by offering vital information, fostering transparency, and ensuring the authenticity of pharmaceutical products ( https://cdsco.gov.in/opencms/opencms/system/modules/CDSCO.WEB/elements/download_file_division.jsp?num_id=OTIwMg ). This research paper presents a cost-effective QR code detection solution developed using open-source Python libraries. The methodology involves the utilization of various libraries, including pandas, pylibdmtx, Python: Pillow (a fork of PIL), NumPy, cv2, json, MySQL, pyzbar, threading, time, and pymysql. The implementation phase includes the use of 25 demo samples each of QR codes and 2D Data Matrix codes, which are generated and stored in the system. The paper evaluates the efficiency of the solution by measuring the time taken for the detection of these codes. It presents the findings of a study on QR code detection efficiency using open-source Python libraries. The time required for detecting 50 codes, comprising 25 QR codes and 25 2D Data Matrix codes, is meticulously recorded as 0.12s and 0.17s, respectively, in accordance with the implementation screenshot. This research paper investigates the applicability of 25 QR codes and 25 2D Data Matrix codes initially stored in a digital system. The focus is on their prospective use on printed circuit boards (PCBs) with constrained rotation lengths. The study sets the stage for future work, with the primary goal of measuring the efficiency of these codes in scenarios with spatial limitations. The paper delves into the details of these findings within the results and discussion section, highlighting the practicality and cost-effectiveness achieved through the utilization of open-source Python libraries and a systematic approach in implementing the QR code detection system. Future research directions may include scalability testing, real-world implementation trials, and exploring additional applications of the developed QR code detection system in diverse industries. By addressing the menace of counterfeit drugs through innovative technology, this research contributes to the ongoing efforts to safeguard public health and promote trust in pharmaceutical products.