Revolutionizing data transmission efficiency in IoT-enabled smart cities: A novel optimization-centric approach

In the modern era, IoT-based smart cities play a crucial role in enhancing the development and quality of life in advanced countries. As digital technologies and advanced metering systems become increasingly integrated with IoT devices in smart city applications, efficient data transmission strategies are essential. This paper introduces a novel approach, the Deep Belief-based Optimal Moth Flame Routing Protocol (DB-OMRP), designed to improve data transfer and extend the lifetime of IoT networks in smart cities. The proposed method leverages Moth Flame Optimization (MFO) to identify the optimal cluster head (CH), while the Deep Belief Network (DBN) further optimizes energy consumption across the system. The DB-OMRP algorithm is implemented in MATLAB, demonstrating a 14mJ reduction in energy consumption per millisecond and a 10% decrease in packet loss compared to traditional methods.