Sensor anomaly detection in wireless sensor networks for healthcare.

摘要: Wireless Sensor Networks (WSN) are vulnerable to various sensor faults and faulty measurements. This vulnerability hinders efficient timely response in WSN applications, such as healthcare. For example, measurements can create false alarms which may require unnecessary intervention from healthcare personnel. Therefore, an approach differentiate between real medical conditions will improve remote patient monitoring systems quality of service afforded by WSN. In this paper, a novel is proposed detect anomaly analyzing collected physiological data sensors. The objective method effectively distinguish true alarms. It predicts value historic values compares it with the actual sensed for particular instance. difference compared against threshold value, dynamically adjusted, ascertain whether anomalous. has been applied datasets existing approaches. Experimental results demonstrate effectiveness system, providing high Detection Rate (DR) low False Positive (FPR).