Construction Expense Tracker

Construction Expense Tracker

Abhishek K K, Adithyan C, Adithya Prakash, Anunandha K Asokan, Soumya Thomas

Department of Computer Science (ADS), Vimal Jyothi Engineering College (KTU)

Chemperi, Kannur.

Abstract—The Building Expense Tracker is a machine- learning-driven solution designed to streamline construction bud- get management and cost forecasting. By accepting inputs such as a building plan and other construction-related parameters, the system can track real-time expenses while predicting future costs and estimating material quantities as the project progresses. Leveraging advanced techniques like regression analysis and optimization algorithms, it learns from historical data to provide accurate cost projections and trend insights. This enables project managers to anticipate budget overruns and allocate resources efficiently. Additionally, the system generates automated reports on both current and expected expenses, enhancing decision- making throughout the construction process. The system predicts the quantities of materials needed as the construction progresses, ensuring efficient resource allocation. By automating expense tracking and cost prediction, the system eliminates manual errors and inefficiencies also ensures smoother project execution with optimized financial management. Ultimately, this project aims to reduce inefficiencies, improve financial planning, and enhance overall construction management, making it an essential tool for contractors, architects, and developers focused on optimizing resources and budgets.

Index Terms—Machine Learning, Cost Prediction, Construc- tion Budget, Expense Tracking, Resource Optimization