## 1 Introduction  
With the acceleration of urbanization and breakthroughs in modern construction technology, the scale of super-high-rise buildings (height \(\geq\) 300 m) has been continuously expanding, particularly in China, where the number of such structures ranks among the highest globally. While these buildings showcase remarkable engineering achievements, their construction presents unique challenges, including complex high-altitude working conditions, fluctuating dynamic loads, and heightened structural safety risks ([PERSON] et al., 2023 [1]; [PERSON] et al., 2022 [2]). Among them, climbing scaffolds serve as essential structural supports in super-high-rise construction, requiring frequent vertical ascents, with their stability directly affecting both safety and efficiency ([PERSON] et al., 2023 [3]). However, as super-high-rise buildings are often located in dense urban areas, the \"urban canyon\" effect exacerbates the impact of strong wind loads, construction vibrations, and temperature fluctuations on climbing scaffold stability. Traditional monitoring methods, such as manual inspections and static sensors, struggle to meet the requirements for real-time tracking and risk assessment in such dynamic environments ([PERSON], et al., 2017 [4]; [PERSON] et al., 2019 [5]). Consequently, developing a high-precision, automated monitoring system suitable for complex super-high-rise environments has become an urgent research challenge in engineering safety. The current research on climbing scaffold monitoring primarily focuses on two aspects. The first is structural condition monitoring, specifically stress distribution and deformation analysis ([PERSON] et al., 2023 [6]). Studies have investigated key scaffold components such as main frames, attachment nodes, and crossbeams, aiming to identify stress concentration zones and overload risks ([PERSON], 2022 [7]). Additionally, displacement and inclination sensors have been used to track scaffold deformations and displacements during operation, assessing structural stability ([PERSON] et al., 2023 [8]). [PERSON] et al. [9] proposed a novel axial force measurement method, validating its effectiveness for detecting scaffold anomalies through 115 experimental cases. Similarly, [PERSON] et al. [10] deployed fiber Bragg grating static level meters to monitor scaffold ascent displacement and evaluate the influence of differential support point movements on the climbing process. However, these methods rely on discrete sensor deployment, making it difficult to achieve full-scale dynamic monitoring, and their effectiveness is often limited by the signal transmission stability. The second major area of research concerns the impact of external loads on scaffold stability. Studies have shown that wind speed, wind direction, and turbulence effects significantly influence scaffold dynamics ([PERSON] et al., 1996 [11]). Typically, environmental factors are assessed using meteorological sensors and vibration monitoring devices to evaluate how external forces affect scaffold stability in real time, ensuring safe operation in complex environments ([PERSON] et al., 2024 [12]; [PERSON] et al., 2024 [13]). [PERSON] et al. [14] and [PERSON] et al. [15] employed computational fluid dynamics (CFD) simulations and wind tunnel experiments to derive wind load effects on scaffolds and proposed wind pressure calculation models for safety-net-covered scaffolding. Additionally, temperature and humidity sensors have been used to analyze material degradation under extreme weather conditions, preventing issues such as corrosion or brittleness. [PERSON] et al. [16] deployed meteorological sensors to assess wind thrust and vibration risks, contributing to extreme weather disaster prevention. However, these studies primarily focus on environmental parameters without directly correlating them to scaffold displacement responses.