Sustainable Enterprise Clouds for Smart Surgery, Insurance, and Urban Air Monitoring with Optimized QA in Multi-Team Development

Emilia Becker Paul Weber

doi:10.15662/IJRAI.2025.0806004

Authors

Emilia Becker Paul Weber University of Kassel, Kassel, Germany Author

DOI:

https://doi.org/10.15662/IJRAI.2025.0806004

Keywords:

Sustainable Enterprise Cloud, Smart Surgery, Insurance Automation, Urban Air Monitoring, Multi-Team Software Development, Optimized Quality Assurance, Energy-Efficient Cloud Computing, Cross-Domain Intelligence, Workflow Optimization, Scalable Intelligent Systems

Abstract

Sustainable enterprise cloud infrastructures are increasingly essential for integrating smart technologies across healthcare, insurance, and urban environmental monitoring. This paper proposes a framework that leverages cloud-based platforms to support smart surgery systems, automated insurance workflows, and urban air quality monitoring while emphasizing energy-efficient operations. Optimized quality assurance (QA) mechanisms are embedded across multi-team software development environments to ensure high-quality, reliable, and scalable outputs. By combining sustainable cloud computing, domain-specific intelligence, and coordinated QA strategies, the framework enhances operational efficiency, reduces environmental impact, and fosters cross-domain innovation. The results demonstrate the potential of sustainable cloud solutions to deliver robust, intelligent, and eco-friendly enterprise applications.

References

1. Oquendo Torres, F. A., & Segovia Vargas, M. J. (2024). Sustainability risk in insurance companies: A machine learning analysis. Global Policy, 15(S7), 47 64. Wiley Online Library

2. Raju, L. H. V., & Sugumar, R. (2025, June). Improving jaccard and dice during cancerous skin segmentation with UNet approach compared to SegNet. In AIP Conference Proceedings (Vol. 3267, No. 1, p. 020271). AIP Publishing LLC.

3. Khanmohammadi, S., & Samadi, M. (2023). A cloud based urban monitoring system by using a quadcopter and intelligent learning techniques. Journal of Automation, Mobile Robotics and Intelligent Systems, 16(2), 11 19. jamris.org

4. Reddy, B. T. K., & Sugumar, R. (2025, June). Effective forest fire detection by UAV image using Resnet 50 compared over Google Net. In AIP Conference Proceedings (Vol. 3267, No. 1, p. 020274). AIP Publishing LLC.

5. Urs, A. Technology-Driven Improvement in Post-Operative Care. IJAIDR-Journal of Advances in Developmental Research, 16(1).

6. “Air quality monitoring and forecasting using smart drones and recurrent neural network for sustainable development in Chennai city.” (2022). Sustainable Cities and Society, 85, 104077. ScienceDirect

7. Thomas Johnson & Kieran Woodward. (2025). Enviro IoT: Calibrating low cost environmental sensors in urban settings. arXiv preprint arXiv:2502.07596. arXiv

8. Ali, A., et al. (Date). A framework for air pollution monitoring in smart cities by using IoT and smart sensors. Informatica, 46(5). puffbird.ijs.si

9. Peddamukkula, P. K. (2024). Immersive Customer Engagement_The Impact of AR and VR Technologies on Consumer Behavior and Brand Loyalty. International Journal of Computer Technology and Electronics Communication, 7(4), 9118-9127.

10. “When Sharing Economy Meets IoT: Towards Fine grained Urban Air Quality Monitoring through Mobile Crowdsensing on Bike share System.” (Year). Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(2). ACM Digital Library

11. Insurtech Digital. (n.d.). 5 Ways insurtech contributes to environmental sustainability. InsurTech Digital. InsurTech Digital

12. Gandhi, S. T. (2024). Fusion of LiDAR and HDR Imaging in Autonomous Vehicles: A Multi-Modal Deep Learning Approach for Safer Navigation. International Journal of Humanities and Information Technology, 6(03), 6-18.

13. Komarina, G. B. (2024). Transforming Enterprise Decision-Making Through SAP S/4HANA Embedded Analytics Capabilities. Journal ID, 9471, 1297.

14. Ishtiaq, W., Zannat, A., Parvez, A. S., Hossain, M. A., Kanchan, M. H., & Tarek, M. M. (2025). CST-AFNet: A Dual Attention-based Deep Learning Framework for Intrusion Detection in IoT Networks. Array, 100501.

15. NTT DATA. (n.d.). On the path to sustainability: The insurance industry’s footprint. NTT DATA whitepaper. insurance.nttdata.com

16. Karanjkar, R., & Karanjkar, D. (2024). Optimizing Quality Assurance Resource Allocation in Multi Team Software Development Environments. International Journal of Technology, Management and Humanities, 10(04), 49-59.

17. Alcon. (2018, October 23). Alcon to develop SMART Suite digital health platform for cataract surgery. Alcon press release. alcon.com

18. Surgery Cloud. (n.d.). Meeting the challenges of today’s modern surgery practices. Surgery Cloud About Us. Surgery-Cloud

19. Sethupathy, U. K. A. (2023). Building Resilient APIs for Global Digital Payment Infrastructure. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 6(5), 8969-8980.

20. Seoul National University Bundang Hospital. (n.d.). SMART OR system for minimally invasive surgery. SNUBH SMART OR. global.snubh.org

21. Shekhar, P. C. (2024). Testing Approaches in Life Insurance: Accelerated and Fluid less Underwriting Amidst Data-Driven Dynamics.

22. “Urban Air Pollution Mapping Using Fleet Vehicles as Mobile Monitors and Machine Learning.” (2021). Environmental Science & Technology. American Chemical Society Publications

23. GASDUINO: Wireless Air Quality Monitoring System Using Internet of Things. (2020). arXiv preprint arXiv:2005.04126. arXiv

24. Balaji, P. C., & Sugumar, R. (2025, June). Multi-level thresholding of RGB images using Mayfly algorithm comparison with Bat algorithm. In AIP Conference Proceedings (Vol. 3267, No. 1, p. 020180). AIP Publishing LLC.

25. Gonepally, S., Amuda, K. K., Kumbum, P. K., Adari, V. K., & Chunduru, V. K. (2023). Addressing supply chain administration challenges in the construction industry: A TOPSIS-based evaluation approach. Data Analytics and Artificial Intelligence, 3(1), 152–164.

26. Adari, Vijay Kumar, “Interoperability and Data Modernization: Building a Connected Banking Ecosystem,” International Journal of Computer Engineering and Technology (IJCET), vol. 15, no. 6, pp.653-662, Nov-Dec 2024. DOI:https://doi.org/10.5281/zenodo.14219429.

27. Ballamajalu, R., Nair, S., Chhabra, S., Monga, S. K., SVR, A., Malati Hegde, Y., … Tripathi, S. N. (2018). Toward SATVAM: An IoT network for air quality monitoring. arXiv preprint arXiv:1811.07847. arXiv

28. Brainlab. (n.d.). Brainlab: software technology for planning and navigating surgical procedures. Brainlab software information.