Wireless data transmission in complicated terrains like cities or deep woodlands sometimes raises dependability concerns. These issues are caused by barriers, multipath fading, and signal interference. Our study uses adaptive wireless sensors to improve data transmission reliability to solve this problem. These sensors are meant to dynamically modify gearbox parameters in real time, unlike standard sensors. This distinguishes them. The study uses key research methods. Dynamic Path Selection chooses the best transmission paths for data packets. Adaptive Modulation and Coding (AMC) alters modulation and coding rates based on real-time environmental information. The study also uses Spatial Diversity using Beamforming. This method concentrates energy using multi-antenna systems, increasing signal intensity and decreasing interference. Practical experiments in clutter-filled regions showed improved gearbox reliability. Compared to standard systems, adaptive sensors reduced packet loss by 45% and increased throughput by 30%. Adaptive wireless sensors increase connection reliability in difficult conditions. These sensors may be utilised for many applications, including urban IoT frameworks and autonomous navigation. © 2024 Elsevier B.V., All rights reserved.