Green Software Tracker for Web Applications Using AI

Web applications consume computing resources such as CPU, memory, and network bandwidth during request processing. High resource consumption can increase energy usage and contribute to carbon emissions. This research proposes a Green Software Tracker for Web Applications Using AI to monitor resource utilization and estimate the environmental impact of web applications. The proposed system uses Python and the psutil library to collect process-level CPU and memory data at defined intervals. It aims to estimate energy consumption using a documented estimation method and calculate associated carbon emissions using an appropriate electricity emission factor. A dashboard is planned to display resource usage, estimated emissions, a Green Score, and recommendations for improving software efficiency. The current recommendation approach is rule-based. Further implementation and experimental evaluation are required to validate the estimation method and assess the system's performance