Multi-obstacle visual sensor network deployment optimization based on improved difference algorithm

The VSN is much more sensitive to the obstacle than other sensors, which means the obstacle can affect the visual sensor perception range, different from the traditional wireless sensor networks(WSNs). Nowadays, most research on optimal VSN deployment mainly focuses on the scenes without obstacles, neglecting multi-obstacle scenes due to the limitation of real scene model simulation. However, Building Information Model (BIM) technology can provide reliable real scene data as input for the optimal algorithm due to the features that it can give the geometric and non-geometric properties of actual scene elements automatically. This paper proposes a novel BIM-SAMDE framework that combines BIM and Segment-Adaptive-Migration Differential Evolution algorithm. This paper also presents a multi-nodes effective perception coverage analysis algorithm to calculate the optimal effective coverage rate for collaborative visual sensor network deployment in multi-obstacle cases. The simulation result shows that the proposed BIM-SAMDE framework can automatically obtain the multi-obstacle scenes data. The proposed SAMDE algorithm has the superior optimizing performance in multi-obstacle scenes, with a fast convergence rate compared with other optimal algorithms.