针对煤矿井下工作场景恶劣复杂、人员健康及环境参数监控难度大、易造成安全事故等问题,采用物联网技术,设计了一种基于无线传感器网络(Wireless Sensor Networks,WSN)和射频识别(Radio Frequency Identification,RFID)的矿井作业人员健康监测系统。该系统利用WSN实时监控人体的心率、血氧及井下环境温湿度、气体浓度等数据;利用RFID技术定位井下作业人员;将所采集信息数据传输至服务器实时检测,实现安全预警并及时定位救援,从而远程监测作业人员健康。
In recent years, target tracking has been considered one of the most important applications of wireless sensornetwork (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally criticalobjectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. Theproposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH)election, pre-selection, and task set selectionmechanisms, where the latter two kinds of selections forma two-layerselection mechanism. The CH election innovatively introduces the movement trend of the target and establishesa scoring mechanism to determine the optimal CH, which can delay the CH rotation and thus reduce energyconsumption. The pre-selection mechanism adaptively filters out suitable nodes as the candidate task set to applyfor tracking tasks, which can reduce the application consumption and the overhead of the following task setselection. Finally, the task node selection is mathematically transformed into an optimization problem and thegenetic algorithm is adopted to form a final task set in the task set selection mechanism. Simulation results showthat HMNCS outperforms other compared mechanisms in the tracking accuracy and the network lifetime.
Xue ZhaoShaojun TaoHongying TangJiang WangBaoqing Li
