Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65221
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
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.
Department of Computer Engineering
JSPM Narhe Technical Campus
Department of Computer Engineering
JSPM Narhe Technical Campus
Department of Computer Engineering
JSPM Narhe Technical Campus
Department of Computer Engineering
JSPM Narhe Technical Campus
Department of Computer Engineering
JSPM Narhe Technical Campus
Healthcare infrastructure in India faces persistent challenges in hospital bed management, primarily due to the absence of centralized, real-time information systems. During emergencies, the inability to quickly locate available beds results in delayed treatment and adverse patient outcomes. This paper presents BookMyBed, a smart cloud-based hospital bed booking and healthcare analytics system. The system enables patients to search hospitals by location, verify real-time bed availability across General, ICU, and Test bed categories, and confirm bookings through a responsive web interface. The proposed architecture integrates HTML5, CSS3, and JavaScript on the frontend with Supabase cloud backend services and PostgreSQL for real-time synchronization across multiple healthcare facilities. A Chart.js-powered analytics dashboard and geospatial heatmap module support monitoring of ICU occupancy trends, patient demand patterns, and regional high-risk zone identification. Experimental evaluation demonstrates an average response time of 1–3 seconds, support for 50+ concurrent users, and 99% system availability. BookMyBed demonstrates the potential of cloud-native healthcare platforms in improving hospital resource management and healthcare decision-making.
KEYWORDS
This paper presented BookMyBed, a cloud-native hospital bed booking and healthcare analytics system addressing critical gaps in hospital resource management. By integrating real-time bed availability, patient-initiated booking, multi-view analytics dashboards, and geospatial risk visualization in a unified Supabase/PostgreSQL cloud platform, the system delivers measurable improvements in healthcare resource accessibility and administrative decision-making. The system achieved all target performance benchmarks with average response times of 1.2–2.8 seconds, 99.1% availability, and real-time synchronization latency under 2.5 seconds. BookMyBed uniquely combines features absent in existing platforms without requiring hardware infrastructure, demonstrating the viability of cloud-native BaaS-powered healthcare applications.
[1] World Health Organization, “World Health Statistics 2023: Monitoring Health for the SDGs,” WHO Publications, Geneva, 2023. [Online]. Available: https://www.who.int/data/gho/publications/world-health-statistics [2] A. Ahmadi, P. Asl, and F. Aarabi, “Hospital Information Systems: A Systematic Review on the State-of-the-Art and Emerging Trends,” Int. J. Med. Inform., vol. 120, pp. 72–81, Dec. 2018. DOI: 10.1016/j.ijmedinf.2018.09.011 [3] Supabase, Inc., “Supabase Documentation: Backend-as-a-Service Platf [4] The PostgreSQL Global Development Group, “PostgreSQL 16 Documentation,” 2024. [Online]. Available: https://www.postgresql.org/docs/16/ [5] Chart.js Contributors, “Chart.js: Simple yet Flexible JavaScript Charting for Designers and Developers,” v4.4, 2024. [Online]. Available: https://www.chartjs.org/docs/latest/ [6] Ministry of Health and Family Welfare, Govt. of India, “eHospital: Hospital Management Information System,” National Informatics Centre, 2023. [Online]. Available: https://ehospital.gov.in [7] R. Mehrotra, A. Sharma, and S. Singh, “COVID-19 and Hospital Bed Allocation: Challenges and Digital Solutions in the Indian Context,” Indian J. Public Health, vol. 64, pp. S142–S144, 2020. DOI: 10.4103/ijph.IJPH_496_20 [8] S. Dash, S. K. Shakyawar, M. Sharma, and S. Kaushik, “Big Data in Healthcare: Management, Analysis and Future Prospects,” J. Big Data, vol. 6, no. 1, pp. 1–25, 2019. DOI: 10.1186/s40537-019-0217-0
Publication Date
6/20/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
3
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...