DawaCheck — Counterfeit Medicine Verification System

Inspiration

Counterfeit medicines are a serious problem because people may unknowingly purchase medicines that are fake, expired, or do not match the information provided on their packaging. We wanted to explore how technology could make medicine verification easier and more accessible.

This inspired us to build DawaCheck, a mobile-based system that helps users check medicine authenticity using QR codes, barcodes, packaging information, and available verification data.

What it does

DawaCheck helps users verify medicine information through a simple mobile interface.

A user can scan a medicine's QR code or barcode and provide packaging information. The system can then check available verification data such as:

• Medicine name
• Batch number
• Expiry date
• Manufacturer
• QR/barcode information
• Packaging details

Based on the available information, DawaCheck provides a clear verification result to help the user identify potentially suspicious medicines.

How I built it

We designed DawaCheck as a mobile-based AI and verification system.

The basic workflow is:

Scan → Extract Information → Verify → Analyze → Display Result

The system is designed to combine barcode/QR scanning with AI and Computer Vision concepts for analyzing medicine packaging. A database or trusted verification source can then be used to compare the extracted medicine information.

Challenges I ran into

One of the main challenges was deciding how to verify a medicine reliably instead of depending on only one piece of information.

Medicine packaging can also vary between manufacturers, making image-based verification more challenging. Another challenge was thinking about how to handle incomplete, missing, or inconsistent medicine information without giving users a misleading result.

Accomplishments that I'm proud of

I am proud of turning a real-world healthcare problem into a practical technology-based solution.

DawaCheck brings together AI, Computer Vision, barcode/QR verification, mobile technology, and data verification into one concept. We also focused on making the system simple enough that a normal user could understand the verification result.

What I learned

Through DawaCheck, I learned more about how AI and Computer Vision can be applied to real-world problems.

I also learned that building a verification system is not only about developing a model. The quality and reliability of the underlying data, validation process, and user experience are equally important.

What's next for DawaCheck — Counterfeit Medicine Detection & Verification System

The next step is to develop a working prototype and integrate reliable medicine verification data.

We plan to improve DawaCheck with:

• More reliable medicine databases and verification sources
• Better QR/barcode scanning
• OCR for extracting information from packaging
• Computer Vision for packaging analysis
• AI-based counterfeit detection
• Batch and expiry verification
• A simple and user-friendly mobile interface

Our long-term goal is to make DawaCheck a reliable first-level verification tool that can help people make safer decisions about the medicines they purchase.

Built With

• api
• app
• artificial
• barcode
• code
• computer
• database
• intelligence
• learning
• machine
• mobile
• ocr
• python
• qr
• rest
• scanning
• vision