This paper presents a better routing technique for WBANs, therefore improving their communication performance, reliability, and energy economy. Using contemporary optimization techniques, most notably PSO and ACO, the proposed model achieves dynamically choosing suitable communication routes that lower energy consumption while maximizing data transmission efficiency. Among the key performance metrics, the proposed approach beats conventional routing systems on are energy economy, packet delivery ratio, latency, and network lifetime. The better routing algorithm significantly lowers energy usage and increases network reliability when compared to more traditional methods, so it is a perfect option for real-time health monitoring systems. The findings underline the requirement of applying intelligent optimization algorithms in order to overcome the challenges of WBANs and provide a consistent and extendable solution for important healthcare uses. Future study will mainly aim to improve the scalability of the model integrating machine learning techniques and investigate its possible usage in next-generation networks such as 5G.