High-quality and completeness of real time drilling data have become critical factors to capitalize the improvement of data analysis for decision making. This paper proposes a combined architecture that supports edge computing technology with high frequency real time data to produce smart alerts as well as for the remote monitoring of real time data status for large number of rigs in a centralized location to enhance the surveillance of real time drilling data transfers. Unlike the traditional real time data surveillance method that monitors the data in the WITSML town server, this innovative technique analyzes the real time data quality right on the edge device. It offers smart computation to produce rule-based intelligent alarms for effective decision-making. This method delivers flexibility and effectiveness in WITSML real time data monitoring as it is fully independent from direct access to the WITSML Store. The biggest advantage of this approach is that it handles the remote surveillance of numerous rigs and gives absolute control over data aggregation. Managing sensitive drilling data has started to play a key role in cost optimization and critical decision- making, especially when running an active mission critical operation. The new approach of edge computing to analyze the WITSML data from its activity file at the rig site is a breakthrough in the real time data monitoring concept. A rule-based smart alarm system to check the statistics of real time data on the edge increases the confidence of the decision-making process as any data transfer issue can be detected faster. Further analysis and active monitoring of multiple rigs data transmission can be done by a centralized control panel, accessed from the real time operations center in town. Having a system with a precise method to actively monitor the status of real time data transfers on multiple rig sites and smartly generate alerts, assures end users to manage their well efficiently. Emphasizing the requirement to ensure the nature, quality and latency of real time information at rig site will reduce the lost and non-productive time overall.