Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM68125
Volume:
10 |
10 |
Oct 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
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.
Electronics and Telecommunication Engineering
Priyadarshini College of Engineering, Nagpur
Electronics and telecommunication engineering
Priyadarshini college of engineering, Nagpur
Electronics and telecommunication engineering
Priyadarshini college of engineering, Nagpur
Electronics and Telecommunication Engineering
Priyadarshini College of Engineering, Nagpur
Electronics and Telecommunication Engineering
Priyadarshini College of Engineering, Nagpur
Paediatrics
NKP Salve Institute of Medical Sciences and Research Centre Nagpur
Electronics and Telecommunication Engineering
Priyadarshini College of Engineering, Nagpur
Temperature-sensitive medical products such as vaccines, insulin, blood products and certain medicines require controlled environmental conditions during transportation and storage. Conventional cold-chain monitoring often depends on manual inspection and may not identify temperature excursions, excessive vibration, unauthorized access or location deviations in real time. This paper presents the design of an AI-based smart cold-chain monitoring system for vaccines and medicines. The proposed system integrates temperature and humidity monitoring, shock and tilt detection, GPS-based location tracking, GSM-based communication, active cooling control, cloud monitoring, OTP-based access security and alert generation in a compact medicine transport box. An ESP32 microcontroller processes the sensor data, controls the cooling system and transmits information to a cloud dashboard and mobile application. A proposed Medicine Health Score combines environmental and transportation conditions into a single engineering-level monitoring indicator on a 0–100 scale. Because calibrated experimental measurements and prototype test logs were not available at the time of writing, this paper presents the system design, the underlying equations and the expected outcomes rather than measured performance results.
KEYWORDS
The AI-Based Smart Cold Chain Monitoring System provides a practical approach to improving the transportation monitoring of vaccines and medicines by combining temperature sensing, humidity monitoring, cooling control, shock and tilt detection, GPS tracking, GSM communication, OTP-based security, local alerts and cloud-based monitoring around an ESP32 microcontroller. The proposed Medicine Health Score provides a simplified way of representing multiple transport-related conditions through one engineering-level indicator, while the underlying sensor history remains available for inspection. The system is intended to reduce dependence on manual inspection and to provide faster information when unsafe conditions occur. No numerical claims regarding sensor accuracy, cooling performance, alert latency, battery runtime, communication reliability or Medicine Health Score validity are made in this paper, because controlled prototype testing has not yet been completed. Future work will focus on sensor calibration, measuring the evaluation parameters of Table I, real transportation trials, validation of the health-score weights, cloud and mobile-application development, and product-specific stability assessment in cooperation with pharmaceutical stakeholders.
1. S. Jiang, S. Jia, and H. Guo, “Internet of Things (IoT)-enabled framework for a sustainable vaccine cold chain management system,” Heliyon, vol. 10, no. 7, Art.no. e28910, 2024, doi: 10.1016/j.heliyon.2024.e 28910. 2. R. Singh, A. D. Dwivedi, and G. Srivastava, “Internet of Things based blockchain for temperature monitoring and counterfeit pharmaceutical prevention,” Sensors, vol. 20, no. 14, Art. no. 3951,2020, doi: 10.3390/s20143951. 3. R. Badia-Melis, U. Mc Carthy, L. Ruiz-Garcia, J. Garcia-Hierro, and J. I. Robla Villalba, “New trends in cold chain monitoring applications — A review,” Food Control, vol. 86, pp. 170–182, 2018, doi: 10.1016/j.foodcont.2017.11.022. 4. A. Alshdadi, S. Kamel, E. Alsolami, M. D. Lytras, and S. Boubaker, “An IoT smart system for cold supply chain storage and transportation management,” Engineering, Technology & Applied Science Research, vol. 14, no. 2, pp. 13167–13172, 2024, doi: 10.48084/etasr.6857. 5. World Health Organization, “How to monitor temperatures in the vaccine supply chain,” WHO/IVB/15.04, World Health Organization, Geneva, Switzerland, 2015. 6. R. T. Hasanat, M. A. Rahman, N. Mansoor, N. Mohammed, M. S. Rahman, and M. Rasheduzzaman, “An IoT based real-time data-centric monitoring system for vaccine cold chain,” in Proc. 2020 IEEE East-West Design & Test Symp. (EWDTS), Varna, Bulgaria, 2020, doi: 10.1109/EWDTS50664.2020.9225047. 7. B. Thiyaneswaran, “IoT based smart cold chain temperature monitoring and alert system for vaccination container,” Przegląd Elektrotechniczny, no. 8, 2022, doi: 10.15199/48.2022.08.38.
Publication Date
10/19/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
1
Total views since publication
PDF Downloads
8
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...