Cost Estimation Based on Use Case Points in The Development of AIoT Monitoring Infusion Test Software

Artificial Intelligence of Things (AIoT) based infusion drip monitoring software plays an important role in improving the effectiveness and safety of healthcare services. However, most existing studies on infusion monitoring systems still focus primarily on hardware aspects, sensor accuracy, and technical integration, while software development effort planning and cost estimation, particularly for web based monitoring dashboards, remain insufficiently discussed. Therefore, this study aims to estimate the development effort and cost of AIoT based infusion drip monitoring software when implemented at an industrial scale. The proposed approach employs the Use Case Point s (UCP) method, beginning with problem identification and a literature review related to software cost estimation techniques. Subsequently, a Use Case Diagram is developed based on observations conducted during the prototype development process to identify system actors and core software functionalities. The results indicate a UCP value of 52,08, corresponding to an estimated development effort of 1.041,6 working hours. Referring to standard working time regulations of 8 hours per day or 40 hours per week, this effort is equivalent to an estimated development duration of approximately 6,5 months. Furthermore, by allocating the estimated effort across development activities and involved roles, the total development cost is estimated at IDR 98.148.855. These findings provide a quantitative and systematic reference for time and cost planning in the development of AIoT based monitoring software within the healthcare domain.