One of the promising research areas in recent times is mobile and sensor networks. The use of sensors to collect sensitive information such as radiation dosage, humidity, context information, and so on is receiving attention from both the industry and academia. In previous studies, sensors are proposed to enable radiation readings and these readings are sent to a smartphone where the user can be informed about potential hazard. The mobile sends signals such as beep, vibration and push notification to inform users. Different flow patterns are proposed to enable the data sharing such as sequential, parallel, and choice. While this mobile-sensor ecosystem is tested to determine the optimal path that minimizes latency, a critical issue such as energy minimization is ignored. In this paper, we studied the various flow patterns and their implications for energy consumption on both the sensor and the mobile device. Our preliminary evaluations employ the Sensor Tag device from Texas Instruments and iPod Touch. The results show the process flow with the most computation consumes high energy rather than the flow pattern with the highest latency.