Emmanuelle De Gentili

Performance of a Protected Wireless Sensor Network in a Fire. Analysis of Fire Spread and Data Transmission

The paper deals with a Wireless Sensor Network (WSN) as a reliable solution for capturing the kinematics of a fire front spreading over a fuel bed. To provide reliable information in fire studies and support fire fighting strategies, a Wireless Sensor Network must be able to perform three sequential actions: 1) sensing thermal data in the open as the gas temperature; 2) detecting a fire i.e., the spatial position of a flame; 3) tracking the fire spread during its spatial and temporal evolution. One of the great challenges in performing fire front tracking with a WSN is to avoid the destruction of motes by the fire. This paper therefore shows the performance of Wireless Sensor Network when the motes are protected with a thermal insulation dedicated to track a fire spreading across vegetative fuels on a field scale. The resulting experimental WSN is then used in series of wildfire experiments performed in the open in vegetation areas ranging in size from 50 to 1,000 m2.

Localization method according to collect data from an acoustic wireless sensor network: Example of Homarus Gammarus in natural area

The platform STELLA MARE (Sustainable TEchnologies for LittoraL Aquaculture and MArine REsearch) has for objective to bring responses in the management of the sea in relation with the professional fishing. In this paper, we introduce an experiment on the monitoring of Homarus Gammarus. Using a passive tracking methodology using an acoustic wireless sensor network (AWSN), we try to follow some individuals, to define movement. The main objective is to build a lobster path according to the collected signal according a classical localization method to test our tracking method. Using a smoothing method and some resolution algorithms we are able to deduct a behaviour of tagged lobsters in an experimental area. This paper describes our methodology to estimate lobsters position according to data collected by an AWSN. This work represent a first step before the building a lobster model to simulate its behaviour in Corsican Mediterranean conditions.