This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering program (CFDA 47.070) provides $157,299 from October 1, 2023 to September 30, 2025 to the Bakersfield Auxiliary For Sponsored Programs Administration at California State University, Bakersfield. The project aims to devise a framework for automating end-to-end resource management of 5G-enabled Internet of Things (IoT) devices using reinforcement learning techniques with massive multiple-input multiple-output (MIMO) technology. The research will address the challenges of efficiently managing network resources, coordinating, and optimizing different parts of the 5G network to handle the diverse requirements of IoT devices. Key deliverables include: a) designing 5G network slicing using massive MIMO for IoT devices, b) developing a reinforcement learning model to solve orchestration problems of IoT devices in large-scale 5G networks, and c) integrating the reinforcement learning solution into a massive MIMO network-sliced 5G-enabled IoT network. This work aims to simplify network management, reduce costs, save energy, balance workloads, optimize mobility, and improve overall performance of 5G-enabled IoT systems.