Wireless sensor networks are extensively deployed across a range of applications, including military surveillance, wildlife observation, and industrial process monitoring. Addressing the detection and recovery of coverage gaps is a critical challenge in these networks. The progressive depletion of energy in sensor nodes, which have a finite battery life, can cause some nodes to fail, resulting in uncovered areas within the surveillance region. This document presents a technique for identifying and remedying these coverage gaps in wireless sensor networks. The approach begins by organizing the network into units and designating a node as the unit’s representative. In the subsequent stage, the coverage provided by each node and the level of coverage overlap among nodes are assessed. Based on the extent of this overlap, adjustments to node scheduling are determined. Subsequently, cell agents uncover areas within the network that lack coverage, and cells with such gaps are flagged as potential targets for the deployment of mobile nodes to fill these holes. In the final phase, mobile nodes and an ant colony optimization strategy are employed to address these coverage vulnerabilities. The simulation studies indicate that the proposed algorithm in this document is more effective in conserving network energy, decreasing the travel distance of mobile nodes, and enhancing the rate of network hole recovery compared to other existing algorithms.