Civix: A Cloud-Native Secure Crowdsourced Civic Issue Reporting System for Intelligent City Governance

Main Article Content

Siddhi Dani

Abstract


As urbanization accelerates, cities experience increasing civic problems in the form of potholes, waste and broken infrastructure that may not be resolved promptly, due to slow grievance mechanisms. Civix is a safe cloud-based crowdsourcing site that allows citizens to report issues using their phones or the web including photos and location information. It categorizes and ranks complaints based on AI and ML, which respond to complaints more quickly. The integration on clouds is reliable, scalable, and safe. Civix offers an open, streamlined system to bridge citizens and governments to enhance the governance of cities. Also the platform allows the citizen to get involved easily by making things simple.This means individuals can get involved in the process with ease.The platform also helps authorities make informed decisions using data.This way people can easily participate in tackling the problems in the city and manage them.


Article Details

Section

Articles

Author Biography

Siddhi Dani

  Department of Computer Science and Engineering

Geetanjali Institute of Technical Studies (GITS)
Udaipur, Rajasthan, India

References

[1] K. Binu, R. Sharma, and P. Verma, “Smartreporter: A crowdsourced complaint resolution system,” IJERT, vol. 15, no. 10, pp. 1–10, 2026.

[2] D. Walwadkar, A. Patil, and S. Joshi, “Smart civic issue reporting system,” IJARSCT, vol. 8, no. 4, pp. 23–30, 2022.

[3] Sen, S., Patel, M., Sharma, A.K. (2021). Software Development Life Cycle Performance Analysis. In: Mathur, R., Gupta, C.P., Katewa, V., Jat, D.S., Yadav, N. (eds) Emerging Trends in Data Driven Computing and Communications. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-16-3915-9_27

[4] E. Younis, M. Al-Samarraie, and R. Wills, “Mobile self-reporting techniques for crowdsourcing,” Springer, 2019.

[5] Patel, Mayank, and Ruksar Sheikh. "Handwritten digit recognition using different dimensionality reduction techniques." International Journal of Recent Technology and Engineering 8.2 (2019): 999-1002.

[6] Menaria, H.K., Nagar, P., Patel, M. (2020). Tweet Sentiment Classification by Semantic and Frequency Base Features Using Hybrid Classifier. In: Luhach, A., Kosa, J., Poonia, R., Gao, XZ., Singh, D. (eds) First International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-15-0029-9_9

[7] S. Tjandra, B. Hartono, and L.