Wireless sensor networks (WSNs) play a crucial role in a wide range of applications, including environmental monitoring and industrial automation. Enhancing coverage is one of the biggest challenges with in WSNs deployment. The thesis objective is to design an inclusive 3D algorithm for mobile wireless sensor network (MWSN) deployment. This work begins by conducting an extensive analysis of existing coverage-enhancing algorithms in WSNs and highlighting their limitations. The thesis designs a new hybrid algorithm that considers network connectivity, energy consumption, and signal propagation metrics to maximize coverage efficiency while preserving resources. We test the viability and effectiveness of the proposed hybrid algorithm against other deployment algorithms using MATLAB-based realistic simulations on 3D surfaces. These simulations show that the Hybrid Genetic and Particle Swarm Coverage Enhancement (HGPSCE) algorithm achieves higher coverage and system efficiency in a 3D environment compared to the existing algorithms. This thesis advances the field of WSNs by introducing a new hybrid coverage enhancement algorithm, specially designed for mobile sensors in 3D environments. Keywords: WSNs, hybrid algorithm, coverage enhancement, 3D environment, cooperative sensing, mobility-based approach