Skip to Main content Skip to Navigation
Conference papers

Anomaly Detection with Wireless Sensor Networks.

Abstract : The aim of this study is to suggest two automated techniques able to help medical staff to detect earlier than usual some diseases using wireless sensor networks (WSNs). In this context, a patient is equipped with physical sensors (for temperature, pressure, ..). This WSN will perform some computations and will run an alarm when a disease is suspected. The first technique uses a population protocol to handle data exchanged between motes and provides an efficient algorithm to suggest that a disease is diagnosed on a patient. The algorithm is distributed, i.e., the decision may be done by any mote dealing with the disease detection. The second technique uses a token algorithm where, some motes, denoted as masters. Each of them is in charge of deciding if a specific disease occurs. This technique is not totally distributed but enhances the network efficiency regarding to the energy consumption, the time execution and the number of exchanged messages.
Complete list of metadata
Contributor : Nathalie Dessart Connect in order to contact the contributor
Submitted on : Monday, September 20, 2010 - 7:01:08 PM
Last modification on : Monday, May 4, 2020 - 3:36:06 PM


  • HAL Id : hal-00519599, version 1



Nathalie Dessart, Hacène Fouchal, Philippe Hunel, Nicolas Vidot. Anomaly Detection with Wireless Sensor Networks.. The 9th IEEE International Symposium on Network Computing and Applications (IEEE NCA10), Jul 2010, Cambridge, MA, United States. pp.204-209. ⟨hal-00519599⟩



Record views