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Energy consumption is an important issue in the design of Wireless Sensor Networks (WSNs) which typically are powered by limited energy. A suitable clustering algorithm for grouping sensor nodes can raise energy efficiency for WSNs. However, there exist some overheads for clustering, such as cluster-head selection, assignment, and cluster construction. In this paper, we propose a new regional energy aware clustering with isolated nodes for wireless sensor networks, called REAC-IN. In REAC-IN, the cluster-heads are selected by the calculated weight based on the residual energy of each sensor and the regional average energy of all sensors in each cluster. A distributed clustering algorithms may result in isolated nodes which are far away from cluster-heads. Such isolated nodes may need to communicate with the sink directly by consuming much energy. In order to reduce the energy consumption and prolong the network lifetime, we use regional average energy and the distance between sensors and the sink to determine whether the isolated nodes sleep or transmit data. Our simulation results validate that REAC-IN can outperform other clustering algorithms, such as LEACH, HEED and DEEC algorithms, and has better performance in terms of the total amount of transferred data, the total network energy consumption, and the network life-time.

This study aims at designing a forecasting system providing the predicted weather information based on the past weather data. Meanwhile, the augmented reality on the mobile device helps users obtain the weather around users' locations.

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