CivicEarth- crowdsourced civic issue reporting and resolution system.

Rapid urban growth has notably escalated civic challenges including road deterioration, inadequate waste management, flooding, and environmental contamination.Current civic complaint management systems are frequently manual, inefficient, and lack transparency, leading to delayed responses and diminished trust from citizens.This paper introduces CivicEarth, an intelligent platform powered by machine learning that aims to automate the detection of civic issues and enhance communication between citizens and government entities.The system allows users to upload images of civic problems, which are automatically assessed using a Convolutional Neural Network (CNN)-based image classification model to determine the type of issue.The platform features a scalable backend created with Node.js and Express.js, a responsive frontend developed with React and Tailwind CSS, and a centralized database to facilitate efficient management of complaints.Additionally, CivicEarth integrates geolocation mapping, real-time monitoring, and a government dashboard to promote transparency and accountability.By automating the classification of issues and optimizing the routing of complaints, the suggested system decreases response times, boosts operational efficiency, and improves citizen participation.CivicEarth showcases the effective combination of machine learning and contemporary web technologies to facilitate smart governance and create more responsive and sustainable urban settings.