This paper presents the design of a novel intelligent monitoring platform for low and medium altitudes, aiming to offer a new solution for the development of intelligent equipment operating in this airspace. Current monitoring tasks are primarily performed by fixed-wing and multi-rotor UAVs, but these platforms face significant technical bottlenecks in flight endurance and monitoring precision. This research aims to address these deficiencies. The platform is based on a small-scale unmanned airship featuring a semi-rigid, hybrid lift-body structure. Improvements were made upon the traditional ellipsoidal hull; the hull profile was optimized using a geometric superposition method, introducing an aerodynamic camber line with a maximum camber (m) of 4% to enhance aerodynamic performance at small angles of attack. In terms of its energy system, the platform is powered by a purely electric energy system composed of solar panels and batteries; solar energy is used during the day, while surplus energy is stored in the batteries for night operations, thereby effectively extending flight endurance. For intelligent monitoring, the platform integrates an intelligent recognition and positioning system based on machine vision, which is deployed on a Jetson Nano and utilizes a YOLO11 instance segmentation model. The team has experimentally proven that the platform can effectively achieve intelligent monitoring in low and medium altitude airspace. Furthermore, the structural integrity of the gondola and the aerodynamic advantages of the modified hull have also been verified via simulation analysis. This work provides a new design concept for intelligent monitoring equipment. The platform can also be applied to scenarios such as forest fire prevention, precision agriculture, and long-term ecological monitoring, offering a new solution for the design of unmanned intelligent monitoring equipment.