Energy optimization is a critical issue in randomly deployed dense wireless sensor networks (WSNs). In dense WSNs, the transmitted signal from a source sensor suffers by the interfering signals from surrounding sensors and unwanted events. In such network scenarios nodes are more likely to become non-functional because of noisy environment and residual battery energy depletion etc. This further arises the need for redundant sensor deployment and an energy efficient solution is to schedule sensors to go into sleep state periodically. In this present paper, we address a probabilistic coordinated sensor scheduling scheme to overcome the redundancy in sensor deployment and conserve energy thus extending the overall network lifetime. This scheme uses the concept of inhibition distance of hard-core point process (HCPP) for coordination among sensors with little communication overhead. We analyze the influence of various channel parameters and interferers on sensor activation probability. Further, we perform Monte Carlo simulation and show that the coverage fraction achieved by the coordinated scheduling outperforms random scheduling at same active sensor density. We also study the impact of node failure and K-coverage degree on the achievable coverage fraction in interference limited WSNs.