A Hybrid Binary Grey Wolf Optimiser for WSN Deployment in Indoor Environments Based on BIM Database

Wireless Sensor Networks (WSNs) represent a key component in smart building systems. An efficient WSN deployment involves selecting the most appropriate positions within the building to place sensors in order to maximize coverage and minimize the deployment cost. This paper proposes a novel approach called the Hybrid Binary Grey Wolf Optimiser (HBGWO) to automate the WSN deployment in indoor environments. The proposed approach integrates the Building Information Modeling (BIM) database to accurately model the physical layout and structural characteristics of the deployment area. Furthermore, a Steiner Tree-based heuristic has been developed to reduce the number of active sensors while preserving the network coverage. Experimental results demonstrate the efficiency and superiority of the HBGWO approach compared to existing methods in literature in terms of network coverage and deployment cost under the connectivity constraint.