IoT Based Automated Medication Dispensing with Data Analytics and Visualisation

In the healthcare sector, medication errors pose significant challenges, resulting in patient harm, adverse drug reactions and increased treatment expenses. These errors could occur in different processes such as prescription, drug dispensing and medication administration, frequently arising from healthcare providers' limited familiarity with medications and their patients' medical backgrounds. Dispensing inaccuracies are influenced by factors such as workload and confusion surrounding drug names, whereas administration errors occur due to lapses in verifying patient identity or use of expired medications. Manual processes are susceptible to errors and thus there is a clear need for a cost-effective solution employing IoT technology for automated medication dispensing. This project's core objectives include: decreasing dispensing errors, reduction of medical staff burdens, and the implementation of real-time monitoring. The final outputs of this study include an IoT-connected dispensing prototype, a Cloud-based data repository, and an analytical dashboard to enhance and visualise medical decision-making.

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Publication Details

Published
2024-08-19
DOI
https://doi.org/10.1109/ficloud62933.2024.00029
Primary Topic
Big Data and Business Intelligence
Type
article
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article

IoT Based Automated Medication Dispensing with Data Analytics and Visualisation

Lillian Yee Kiaw Wang, Dinesh Sangarran Ramachandram, Yong Hong Yap, Pui San Saw et al.
Big Data and Business Intelligence
article

IoT Based Automated Medication Dispensing with Data Analytics and Visualisation

Lillian Yee Kiaw Wang, Dinesh Sangarran Ramachandram, Yong Hong Yap, Pui San Saw, Seungro Lee, William Ho
article en

Abstract

In the healthcare sector, medication errors pose significant challenges, resulting in patient harm, adverse drug reactions and increased treatment expenses. These errors could occur in different processes such as prescription, drug dispensing and medication administration, frequently arising from healthcare providers' limited familiarity with medications and their patients' medical backgrounds. Dispensing inaccuracies are influenced by factors such as workload and confusion surrounding drug names, whereas administration errors occur due to lapses in verifying patient identity or use of expired medications. Manual processes are susceptible to errors and thus there is a clear need for a cost-effective solution employing IoT technology for automated medication dispensing. This project's core objectives include: decreasing dispensing errors, reduction of medical staff burdens, and the implementation of real-time monitoring. The final outputs of this study include an IoT-connected dispensing prototype, a Cloud-based data repository, and an analytical dashboard to enhance and visualise medical decision-making.

Monash University Malaysia (MY)
Openalex Percentile: Top 70%
Big Data and Business Intelligence
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IoT Based Automated Medication Dispensing with Data Analytics and Visualisation — Lillian Yee Kiaw Wang, Dinesh Sangarran Ramachandram, et al. · (2024) | TGRS Research Map | TGRS