Decentralized Sensor Localization by Decision Fusion of RSSI and Mobility in Indoor Environments

The number of the weighting vectors is usually small (e.g. So the K nearest neighbors of the test pattern associated with these weighting vectors in the SOM can be easily found with

To solve the problem of the detection of buried networks, we present an automatic detection approach based on knowledge representation in ontologies and reasoning on this knowledge

We proposed a zoning based localization approach in a belief functions framework using WiFi fingerprints.. Different types of modeling were considered, namely the parametric

Zoning-based Localization in Indoor Sensor Networks Using Belief Functions Theory.. Daniel Alshamaa, Farah Mourad-Chehade,

The kernel density estimation was used to set mass functions, and the belief functions theory combined evidence to determine the sensor’s zone. Experiments on real data prove

In this thesis, indoor localization is realized making use of received signal strength fingerprinting technique based on the existing GSM networks, which can be adopted by

Moreover, cameras and LiDAR [ 29 , 30 ] are used in a configuration that will allow extraction of specific environment primitives (road markings and static interest points) for use

In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation