Cloud computing capabilities are extended to the edge of the network with fog computing in the modern computing landscape. This proximity to data sources and end-users offers several advantages, including reduced latency, enhanced real-time processing, and improved privacy. In this context, task scheduling becomes crucial to orchestrate computational tasks efficiently across fog nodes. Effective task scheduling ensures optimal resource utilization, minimizes latency, and enhances the overall performance of fog computing systems. This proposed work introduces a resource-aware task scheduling approach in a fog computing environment to improve latency and responsiveness for latency-sensitive applications. The model considers the residual energy along with memory constraint of the fog node as the basis for assigning the fog node for task execution. Tournament Selection algorithm is used by the task scheduler for action selection. The results show that the proposed approach performs better in reducing the task response time compared to existing approaches.