This project aims to develop a mobile application for pharmacists that utilizes OCR (Optical Character Recognition) to read handwritten prescriptions from uploaded images or camera captures. The extracted medication details will be matched with a database to provide accurate prescription information.

The objective of proposed application is to enhance the management of chronic care disease by facilitating comprehensive data collection, treatment adherence, and patient-provider communication. The application aims to address the current lack of real-world data and studies in urology. It enables healthcare providers to monitor patient-reported symptoms, track pain trends, and assess treatment efficac Doctors can access a dashboard displaying all  patients, prioritize cases based on symptom severity, and receive alerts for critical cases. Patients can easily log symptoms, monitor their  scores, and receive reminders for medications and lifestyle changes, ensuring better adherence to treatment plans. It enables secure messaging between patients and providers, allowing for timely updates, treatment adjustments, and symptom reports. Patients can access personalized educational materials, including multimedia resources and chatbot support, to manage their condition effectively. The platform aims to deliver personalized, data-driven care, improve patient outcomes, and contribute valuable real-world evidence to further research and understanding of the problem

It is a digital tipping and peer-to-peer payment platform designed to simplify, modernize, and enhance the tipping process for service professionals, creators, and gig workers. It empowers individuals to receive cashless tips directly through digital payments, providing an easy, secure, and fast way for customers and supporters to express appreciation. The platform is ideal for industries where cash tips are common but declining due to the rise of cashless transactions.