Ai-Based Android Application For Hr Competency Mapping in Construction Companies: A Machine Learning Approach To Talent Management

Abstract

Construction is a project-based, labour-intensive and risk-prone industry in which organisational performance depends heavily on the competence of engineers, supervisors, planners and site staff. Traditional competency mapping in construction firms is manual, paper-based and subjective, which leads to inconsistent appraisals, delayed promotion decisions and training that is poorly aligned with real skill gaps. This article presents an AI-based Android application that digitises competency assessment and uses machine learning to predict employee competency, quantify skill gaps, assess promotion eligibility and recommend targeted training. The system follows a three-tier architecture comprising an Android client (Java), a PHP REST API with a MySQL database, and a Python AI/ML engine (Scikit-learn, Pandas) based on a Random Forest model. An illustrative employee profile shows how ten competency factors are converted into a competency score, level, skill gap and training plan. The article concludes that mobile, AI-driven competency mapping can improve the objectivity, speed and strategic value of HR decisions in construction organisations.