Journal of Information Technology and Sciences

Automated Drug Dispenser for Efficient Hospital Medication Management

2026-06-20T08:12:56+00:00

Medication errors and non-adherence remain critical challenges in modern healthcare systems, especially among elderly patients and individuals with chronic illnesses. Manual methods of medication management often lead to missed doses, incorrect timing, and increased dependency on caregivers. To address these issues, this project proposes an IoT-based Automated Drug Dispenser (ADD) that ensures accurate, timely, and secure medication delivery. The system integrates key technologies such as RFID for patient authentication, a servo/gear motor for automated dispensing, GSM for real-time SMS alerts, and IoT platforms like Blynk for remote monitoring. Each patient is assigned a unique RFID tag, which enables secure identification and personalized medication scheduling. The system verifies the prescribed schedule using a real-time clock and dispenses the correct dosage automatically at the appropriate time. Additionally, the system sends alerts to caregivers in case of missed doses or system errors, ensuring continuous monitoring and timely intervention. The inclusion of a user-friendly LCD interface enhances usability by providing real-time feedback and instructions to the user. The system is designed to be cost-effective, scalable, and suitable for hospitals, elderly care centers, and home healthcare environments. Overall, the proposed solution improves medication adherence, reduces human errors, and minimizes the workload on healthcare professionals, contributing to safer and more efficient patient care.

AI-Voice-based Automated Form Filling System

2026-06-16T10:32:25+00:00

Manual completion of banking forms is often time-consuming, error-prone, and challenging for elderly, visually impaired, and physically challenged individuals. To address these issues, an AI Voice-Based Automated Form Filling System is proposed that enables users to complete banking forms through voice interaction. The system utilizes Speech Recognition technology to capture user responses and convert spoken input into text. Natural Language Processing (NLP) techniques are employed to extract, organize, and validate relevant information before automatically populating the required form fields. The system interacts with users by asking questions related to personal and banking details, thereby reducing the need for manual typing. Validation mechanisms are incorporated to ensure the correctness and consistency of information such as names, phone numbers, and identification details. After successful validation, the collected data is automatically entered into the selected banking form, and a completed PDF document is generated. The proposed system improves form-filling efficiency, minimizes human errors, and enhances accessibility for users with limited technical skills. Experimental observations indicate that the system significantly reduces the time required for form completion compared with traditional manual methods. The integration of Artificial Intelligence, Speech Recognition, and NLP technologies provides a user-friendly and efficient solution for modern banking applications.