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Paper ID:IJSREM65798

AI-Based Medicine Assistance System for Intelligent Medication Management and Healthcare Support

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65798

Volume:

10 |

7 |

Jul 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM65798

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AP

Aditya Patil

Computer Science and Engineering

Vidarbha Institute of Technology

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TT

Tanvi Telange

Computer Science and Engineering

Vidarbha Institute of Technology

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SG

Shreya Gajbhiye

Computer Science and Engineering

Vidarbha Institute of Technology

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DA

Divyani Adhau

Computer Science and Engineering

Vidarbha Institute of Technology

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RM

Ritika Mandal

Computer Science and Engineering

Vidarbha Institute of Technology

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DT

Dr.Nilesh T.Gole

Computer Science and Engineering

Vidarbha Institute of Technology

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Abstract

Medication errors and poor adherence to prescribed treatment plans remain significant challenges in healthcare, particularly among elderly patients and individuals managing multiple medications. This paper presents an Artificial Intelligence (AI)-based Medicine Assistance System, a smart healthcare platform designed to provide accurate medication information, improve patient safety, and enhance medication adherence. The proposed system enables users to manually enter or scan the name of a medicine, after which it retrieves essential information, including dosage recommendations, administration guidelines, potential side effects, precautions, and storage instructions. To improve medication safety, the system analyzes multiple prescriptions and identifies potential drug–drug interactions, generating alerts for harmful combinations. The platform also incorporates personalized medication scheduling and reminder functionalities to help users follow prescribed treatment plans effectively. Designed with accessibility in mind, the system supports features such as multilingual assistance, voice-based interaction, and simplified medical explanations, making it suitable for elderly individuals, caregivers, and patients with chronic illnesses. Experimental evaluation demonstrates that the proposed system provides an efficient, low-cost, and user-friendly solution for intelligent medication management while reducing the risk of medication errors and improving healthcare outcomes. The proposed platform has potential applications in home healthcare, telemedicine, and digital health ecosystems.

KEYWORDS

Artificial Intelligence (AI) Medicine Assistance System Smart Healthcare Medication Management Drug–Drug Interaction Detection Medicine Reminder Patient Safety Healthcare Informatics Telemedicine Voice Assistance Multilingual Support Digital Health.

Cite This Article

Aditya Patil, Tanvi Telange, Shreya Gajbhiye, Divyani Adhau, Ritika Mandal, Dr.Nilesh T.Gole, "AI-Based Medicine Assistance System for Intelligent Medication Management and Healthcare Support," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 7, pp. 1-4, Jul 2026. https://doi.org/10.55041/IJSREM65798

Full Article/Conclusion

The proposed Medicine Assistance System successfully addresses key healthcare challenges, including medication management, preliminary health guidance, and emergency preparedness, through a unified web-based platform. The system integrates secure user authentication, intelligent medicine reminders, an AI-assisted symptom checker, a health dashboard, and emergency contact management to improve patient safety and medication adherence. Experimental testing demonstrated that the application is reliable, secure, and user-friendly, achieving high user satisfaction during evaluation. Developed using modern web technologies and open-source tools, the proposed system provides a cost-effective and accessible digital healthcare solution suitable for patients, caregivers, and healthcare professionals, with future scope for advanced AI integration and mobile application support.

References

[1]          Ada Health GmbH. (2016). Ada: Your Health Companion. Retrieved from https://ada.com [2]          Bangor, A., Kortum, P. T., & Miller, J. T. (2008). An empirical evaluation of the System Usability Scale. International Journal of Human-Computer Interaction, 24(6), 574-594. [3]          Boulos, M. N. K., Brewer, A. C., Karimkhani, C., Buller, D. B., & Dellavalle, R. P. (2014). Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online Journal of Public Health Informatics, 5(3), e229. [4]          Brooke, J. (1996). SUS: A "quick and dirty" usability scale. In P. W. Jordan, B. Thomas, B. A. Weerdmeester, & I. L. McClelland (Eds.), Usability evaluation in industry (pp. 189-194). Taylor & Francis. [5]          Brown, M. T., & Bussell, J. K. (2011). Medication adherence: WHO cares? Mayo Clinic Proceedings, 86(4), 304-314. [6]          Celler, B. G., Lovell, N. H., & Basilakis, J. (2003). Using information technology to improve the management of chronic disease. Medical Journal of Australia, 179(5), 242-246. [7]          Dayer, L., Heldenbrand, S., Anderson, P., Gubbins, P. O., & Martin, B. C. (2013). Smartphone medication adherence apps: potential benefits to patients and providers. Journal of the American Pharmacists Association, 53(2), 172-181. [8]          Enshaeifar, S., Zoha, A., Markides, A., Skillman, S., Acton, S. T., Elsaleh, T., ... & Barnaghi, P. (2018). Health management and pattern analysis of daily living activities of people with dementia using in-home IoT sensors. PLOS ONE, 13(7), e0200157.

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Publication Date

7/24/2026

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Review Rounds: 2

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