Technological advances have made Wireless Sensor Networks (WSN) more reliable, low cost, and widely used in a variety of applications. As WSN nodes are low power battery operated with limited lifespan, optimizing their resources (sensing, channel use, computing) is an essential task for the success of applications implemented over these networks. Even though this task could be challenging for large WSN, its impact in terms of network survivability and economic benefits can be significant. In this paper, we will focus on optimizing radio data transmission and evaluate its impact on power saving. We will analyze the data collected from a large WSN, more than 20,000 nodes, used for water meter readings in the City of Moncton. Two data driven approaches, reduction and prediction-based, are evaluated and compared. Then we propose a system for data collection and transmission that improves power consumption, in comparison with the existing one, without affecting the effectiveness of the application in terms of water consumption monitoring and detection of leaks. Experimental results show substantial power savings and significant increases in battery lifespan.