The geological environmental damage caused by coal mining has become a hot issue in current research. Especially in the western mining area, the size of the mining working face is large, the mining intensity is high, while the surface movement and deformation are more intense and wider. Therefore, it is necessary to effectively monitor the surface using appropriate means and carrying out research on the overlying strata structure of the stope. In this paper, by using advantages of various subsidence monitoring technologies and the technical framework of the Internet of Things (IoT), a “space–air–ground” integrated collaborative monitoring network is constructed. The evolution law of overlying strata structure is studied based on discrete element simulations and theoretical analysis. Furthermore, a discrete element mechanical parameter inversion method is proposed. The main results, using numerical simulations, are as follows: The mean square error of monitoring surface subsidence is 33.2 mm, the mean square error of mechanical parameter inversion is 13.4 mm, and relative error is as low as 3.8%. The surface subsidence law of adjacent mining under different working face widths and interval coal pillar widths is revealed. The Boltzmann function model of surface subsidence ratio changing with width–depth ratio and the calculation formula of width reduction coefficient of adjacent mining working face are inverted. The critical failure width of the interval coal pillar is determined as 20.5 m. Based on the theory of “arch–beam” structure and numerical simulation results, the overlying strata structure model of adjacent mining in the mining area is constructed. The research results can provide technical support or theoretical reference for mining damage monitoring, subsidence control, and prediction in western mines.