Artificial Intelligence is a field that complements IoT technology. While IoT is responsible for collecting and collating data, it integrally needs AI systems to analyze, learn, and automate. Thus, any IoT system comprises an intelligent counterpart besides sensors and actuators for the analysis, interpretation, and decision-making including actions. Since IoT applications are not completely equivalent to intelligent software solutions due to the inherent requirement of hardware components, this article focuses on the estimation of the cost and effort of designing such applications. We applied the traditional software engineering measurement methods for estimating the appropriateness of an IoT solution before its adoption. Through this article, we make an attempt to measure the functionality of an Intelligent system using the function point count technique (FPC) and evaluate it for all essential characteristics of typical automation-based applications. Five different IoT applications namely, healthcare, smart environment monitoring, IoT-based inventory management, smart home security, and smart home automation were considered and FPC values for all these applications were calculated. The different values of function points directly could be used to infer the complexity designing of the product. The article also analyzes the cost and effort to design intelligent applications in the context of the coding language. These estimates computed give an insight to the language choices for designing such applications.