Recent research in Data Aggregation in Wireless Sensor Networks (WSNs) focuses on developing energy-efficient, secure, and latency-aware mechanisms to optimize data collection and transmission across large-scale sensor deployments. Advanced aggregation tree construction algorithms dynamically adapt to varying node energies and network conditions to reduce communication overhead and prolong network lifetime. Privacy-preserving data aggregation techniques using encryption and lightweight security protocols are being explored to ensure confidentiality while minimizing processing costs. Additionally, adaptive scheduling and multi-channel communication approaches are employed to address delays and congestion in dynamic environments. These innovations collectively aim to enhance data accuracy, energy conservation, and reliability, making data aggregation a key enabler of sustainable and high-performance WSNs.