IoT-based smart grid architectures improve energy management, operational efficiency, and reliability have been developed in response to the growing demand for sustainable energy solutions. High transmission latency, ineffective routing, restricted scalability, and inadequate real-time monitoring are some of the problems that plague traditional smart grid techniques. Hence this research proposes an Internet of Things (IoT) integrated smart grid architecture that utilizes Firefly Optimization Algorithm (FOA) for intelligent energy routing and improved performance in order to overcome these constraints. The smart grid system uses sensors to capture energy inputs from wind and photovoltaic (PV) sources to enable real-time monitoring and data collection. The shortest and most efficient energy transmission path is identified using Firefly Optimization method, which guarantees low energy loss and maximum efficiency. This method minimizes overloading, drastically cuts down on transmission delays, and improves the grid's overall responsiveness. The end user is guaranteed a dependable, economical, and ecologically sustainable power supply of the combination of IoT integration for automation, renewable energy sources, and intelligent routing. This architecture greatly lowers average latency and overhead while achieving high packet delivery ratio (PDR) and throughput. Additionally, it reduces energy use, guaranteeing reliable and effective grid operation.