In this paper, inspired to the high-speed global search ability for genetic algorithm and the positive feedback mechanism for ant colony algorithm, our energy-efficient scheme, called ACGR, was proposed for routing optimization design, in which the communication messages, treated as ants with limited lifetime, are sent by nodes for searching the optimal routing path. Through the proposed scheme, multiple candidate routing paths could be obtained firstly. Then each candidate path is considered as a gene sequence and through the selection, crossover and mutation operations on them, the optimal energy routing path is determined. Simulation results have shown that the proposed algorithm provides promising solution because it takes into account the energy of each node, and extends the lifetime of the wireless sensor network.

This paper presents a Debris Flow Disaster Faster-than-early Forecast System (DFS) with wireless sensor networks. Debris flows carrying saturated solid materials in water flowing downslope often cause severe damage to the lives and properties in their path. Faster-than-early or faster-than-real-time forecasts are imperative to save lives and reduce damage. This paper presents a novel multi-sensor networks for monitoring debris flows. The main idea is to let these sensors drift with the debris flow, to collect flow information as they move along, and to transmit the collected data to base stations in real time. The Raw data are sent to the cloud processing center from the base station. And the processed data and the video of the debris flow are display on the remote PC. The design of the system address many challenging issues, including cost, deployment efforts, and fast reaction.