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IoT enabled prescription reading smart medicine dispenser implementing maximally stable extremal regions and OCR

Citation

R. I. Rumi, M. I. Pavel, E. Islam, M. B. Shakir and M. A. Hossain, "IoT Enabled Prescription Reading Smart Medicine Dispenser Implementing Maximally Stable Extremal Regions and OCR," 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, 2019, pp. 134-138, doi: 10.1109/I-SMAC47947.2019.9032709.

Abstract

The concept of the Internet of Things (IoT) integrated with embedded system and new technologies in the healthcare sector has opened a new era. The natural decrease in physical condition of senior citizens with aging prompts and expansion in frequencies of different diseases, for that reason they need to take medicine on time to improve their health conditions. In this research work we are focusing on the circumstances of senior citizens, we have proposed an IoT enabled smart medicine box equipped with camera for scanning the prescription. After the system scans the prescription through camera, a number of preprocessing techniques are applied on the prescription for better extraction of information. Following that, we applied Maximally Stable Extremal Regions (MSER). Later, string manipulation is done on the extracted text and relevant information is uploaded in the database. Afterwards, our medicine box uses the information to notify the patient using buzzer and shows the medication information on the LCD display. A patient has to verify his identity using fingerprint to take the medicine. Finally, the medicine box dispenses specific medicines and updates the consumption time in the database. Our system will also notify the patient if the dispenser is getting low on medicine using the display by showing message.

Description

Type

Conference Proceeding