This paper presents an advanced path planning and UAV relay system to enhance connectivity in rural and mountainous environments. The system addresses the challenge of poor signal coverage in such areas by using a two-stage framework. The first stage identifies areas of interest where connectivity is poor, while the second stage employs an energy-aware and resilient path planning algorithm to maximize coverage links. A viewshed analysis is used to determine visibility between points of interest and cell towers, enabling the creation of a blockage map that prevents UAVs from passing through areas with no coverage. The approach is validated using open-access datasets of mountainous regions, demonstrating its effectiveness in improving communication networks in remote and challenging environments. The system uses the Longley–Rice propagation model to estimate signal pathloss and identify areas with poor coverage. A viewshed analysis is conducted to determine the mutual visibility region between points of interest and cell towers, which is then used to create a blockage map for the A* algorithm. The A* algorithm is used to plan the UAV relay path, considering energy constraints and weather conditions. The system also incorporates energy awareness and wind resilience, allowing the UAV to determine the optimal time to return to a charging station based on battery levels and wind conditions. The results show that the proposed framework can link 1.7 more points of interest compared to traditional methods. The system also demonstrates improved performance in hazardous weather conditions, with a 6.1% increase in path length and a 6.9% increase in successful links. The framework is capable of maintaining communication between UAVs and cell towers in mountainous areas, ensuring reliable connectivity in remote environments. Future work will focus on improving the accuracy of viewshed analysis using LIDAR data and optimizing the algorithm's memory consumption.This paper presents an advanced path planning and UAV relay system to enhance connectivity in rural and mountainous environments. The system addresses the challenge of poor signal coverage in such areas by using a two-stage framework. The first stage identifies areas of interest where connectivity is poor, while the second stage employs an energy-aware and resilient path planning algorithm to maximize coverage links. A viewshed analysis is used to determine visibility between points of interest and cell towers, enabling the creation of a blockage map that prevents UAVs from passing through areas with no coverage. The approach is validated using open-access datasets of mountainous regions, demonstrating its effectiveness in improving communication networks in remote and challenging environments. The system uses the Longley–Rice propagation model to estimate signal pathloss and identify areas with poor coverage. A viewshed analysis is conducted to determine the mutual visibility region between points of interest and cell towers, which is then used to create a blockage map for the A* algorithm. The A* algorithm is used to plan the UAV relay path, considering energy constraints and weather conditions. The system also incorporates energy awareness and wind resilience, allowing the UAV to determine the optimal time to return to a charging station based on battery levels and wind conditions. The results show that the proposed framework can link 1.7 more points of interest compared to traditional methods. The system also demonstrates improved performance in hazardous weather conditions, with a 6.1% increase in path length and a 6.9% increase in successful links. The framework is capable of maintaining communication between UAVs and cell towers in mountainous areas, ensuring reliable connectivity in remote environments. Future work will focus on improving the accuracy of viewshed analysis using LIDAR data and optimizing the algorithm's memory consumption.