Inventory and Attendance Management System for Construction Firm with Voice Assistant

The goal of this paper is to provide an inventory management system used in the construction sector. With this approach, the Constructing firm's manual activities are turned into a computerized system. In firms where data is still maintained on paper, it minimizes paperwork and human mistakes. It will improve the overall performance of the system. In this paper, the proposed solution is a computerized inventory management application that can run on any mobile operating system. The system is being developed using an incremental methodology. We selected Google's Firebase for database development and deployment, which is designed to expand linearly with the size of the data being synced. To make the managing and editing process easier, we added Voice Assistant for the Application. A user can provide a command verbally, which is subsequently converted to text using Machine Learning and carried out after analysis. To convert speech to text, we used the react-native voice API. We utilized a string-matching algorithm to separate data after it was collected. We examined many string-matching algorithms and discovered that Jaro Winkler had the highest string-matching accuracy. We also utilized Kmeans clustering on database data to group them into clusters based on High, Medium, and Low Costs, so that site administrators may focus on those material alternatives to lower overall costs and increase profits.