Smart Doctor Finder and Queue Tracker

The healthcare platform is a great idea because it offers a streamlined process for locating doctors and managing queues. It has positive implications for patients seeking reliable healthcare by shortening the waiting time and providing an enhanced experience. The utilization of artificial intelligence and real-time data makes finding the right doctor and tracking the queue easier. Other features such as applications, video consultations, languages, and wearable devices can be integrated to add value to the platform. In general, the healthcare platform could make the system more convenient and reliable.

[1]   D. M. Rames, Dhruthi E, Elina D., and Farman Ul Haq, “Smart Hospital Appointment System with Queue Waiting Time Predictor”, International Journal of Emerging Trends in Engineering and Development (IJETED). This article aimed at designing a waiting-time predictor using historical data and patient-arrival information to enable online appointments plus give insights on patients’ traffic flows inside the hospital. It considered how best technology could be leveraged to reduce waiting lists and free up doctors’ time while still treating patients according to their due time. [2]   S. Siddiqui, S. Fatima, A. Ali, S. K. Gupta, H. K. Singh, and S. Kim “Modelling of Queuing Systems Using Blockchain Based on Markov Process for Smart Healthcare Systems”, Scientific Reports . This paper used the Markov chains and Markovian batch-service framework to develop models that would reduce the waiting time of patients in queues while also focusing on securing patient information using the blockchain method. [3] A. O. Itegboje and Y. N. Asafe, “A Systematic Review of Queue Management System: A Case of Prolonged Wait Times in Hospital Emergency Rooms”, South Asian Research Journal of Engineering and Technology . This work focused on reviewing the methods used in managing queues to reduce waiting times in hospital emergency rooms. The paper identified the major causes of the extended waiting hours in emergency units and came up with ways these durations could be reduced in future especially with regard to medical informatics and electronic medical records [4]   S. Gunasegaram, B. Gowtham, K. Gowdham, B. C. Gopish, and B. Elamathi, “Smart Queue Management” Advanced International Journal for Research (AIJFR). This paper gave a detailed account of developing a smart queue management system that would reduce waiting times for patients in hospitals. It made use of a java backend system alongside digital tokens, AI, ML, and IoT to regulate the services provided. This was done by developing an interactive dashboard for the hospital staff and sending out notification updates via emails or SMS to patients. [5]  Deeksha M. Rames, Dhruthi E, Elina D., and Farman Ul Haq, “Smart Hospital Appointment System with Queue Waiting Time Predictor”, study on online scheduling,  real-time  patient  monitoring, historical-data-based waiting-time prediction, and patient notification for improving hospital appointment management. [6]   Shadab Siddiqui, Shahin Fatima, Aleem Ali, Shashi Kant Gupta, Hemant Kumar Singh, and Seongki Kim, “Modelling of Queuing Systems Using Blockchain Based on Markov Process for Smart Healthcare Systems”, study on Markov-chain-based healthcare queue modelling, Markovian batch-service systems, blockchain-based patient-data security, and efficient queue processing. [7]    Ajibike O. Itegboje and Yekini N. Asafe, “A Systematic Review of Queue Management System: A Case of Prolonged Wait Times in Hospital Emergency Rooms”, systematic review focusing on prolonged emergency-room waiting times, queue-management approaches, medical informatics, and electronic medical records. [8]   S. Gunasegaram, B. Gowtham, K. Gowdham, B. C. Gopish, and B. Elamathi, “Smart Queue Management”, study on digital token allocation, AI/ML/IoT-supported dynamic service management, patient notifications, and interactive hospital dashboards.