The rapid growth of the Internet of Things (IoT) has resulted in the generation of massive volumes of heterogeneousdata that require continuous collection, storage, processing, and real-time analysis. Traditional computing infrastructuresoftenexperience limitations in scalability, computational efficiency, storage capacity, and response latency when handlinghighfrequency IoT data streams. Cloud computing has emerged as a powerful solution by providing on-demand computingresources,distributed storage, virtualization, and elastic service provisioning capable of supporting large-scale IoT environments. However,achieving real-time data processing remains a significant challenge because IoT applications such as smart healthcare, intelligenttransportation, industrial automation, environmental monitoring, and smart cities require immediate data analysis withminimallatency and high processing reliability. This experimental study investigates the effectiveness of a cloud computing frameworkforreal-time IoT data processing by evaluating its scalability, resource utilization, processing efficiency, response time, anddatathroughput. The proposed framework integrates cloud infrastructure, distributed computing, virtualization, and real-timedataanalytics into a unified architecture capable of supporting dynamic IoT workloads. A mathematical framework andalgorithmicstrategy are developed to evaluate processing performance, system scalability, network latency, resource allocation, andQualityofService (QoS) within cloud-enabled IoT environments. Experimental evaluation demonstrates that the proposed cloudcomputingframework significantly improves real-time data processing efficiency, reduces processing latency, enhances resourceutilization,and supports scalable IoT deployments. The proposed framework provides valuable guidance for researchers, cloudserviceproviders, and IoT system developers seeking to build efficient, reliable, and scalable cloud-based real-time IoTdataprocessingsystems. Keywords: Cloud Computing, Internet of Things (IoT), Real-Time Data Processing, Distributed Computing, Cloud Framework.