In the era of smart campuses, seamless outdoor wireless connectivity is essential for enabling real-time applications, IoT integration, and uninterrupted user experiences. This project focuses on extending and optimizing outdoor Wi Fi coverage using Juniper AP63 access points, supported by Mist AI for intelligent performance monitoring and environmental adaptation. The deployment aims to eliminate dead zones and ensure robust signal transitions between outdoor AP63 and indoor AP32 zones through seamless device handoff. To address the unique challenges of outdoor environments such as signal degradation from terrain, foliage, and weather this study integrates insights from advanced literature, including clustering-based AP placement, energy-efficient AP activation, and RF propagation modeling. The project also explores environmental optimization strategies to enhance coverage reliability and reduce energy consumption. Performance validation is conducted through field testing and simulation, ensuring that the proposed solution meets the demands of a dynamic, high-density campus environment. This work contributes to the development of scalable, AI-driven outdoor wireless networks that are resilient, energy-aware, and capable of supporting future smart campus innovations.