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Adam Kaliszan, Mariusz Glabowski, Sławomir Hanczewski, Dario Gallucci and Salvatore Vanini

, International Journal of Communication Systems, 2012 [5] T. Issariyakul, E. Hossain, Introduction to Network Simulator NS2, Springer Publishing Company, Incorporated, 1 edition, 2008 [6] A. Kaliszan, M. Gła˛bowski, S. Hanczewski, A didactic platform for testing and developing routing protocols, In Proceedings of the The Eighth Advanced International Conference on Telecommunications (AICT 2012), pages 197-202, Stuttgart, Germany, IARIA, May 2012 [7] A. Kaliszan, M. Gła˛bowski, S. Hanczewski, A new testing method of routing

Open access

Gabriel Deak, Kevin Curran, Joan Condell, Daniel Deak and Piotr Kiedrowski


The holy grail of tracking people indoors is being able to locate them when they are not carrying any wireless tracking devices. The aim is to be able to track people just through their physical body interfering with a standard wireless network that would be in most peoples home. The human body contains about 70% water which attenuates the wireless signal reacting as an absorber. The changes in the signal along with prior fingerprinting of a physical location allow identification of a person’s location. This paper is focused on taking the principle of Device-free Passive Localisation (DfPL) and applying it to be able to actually distinguish if there is more than one person in the environment. In order to solve this problem, we tested a Support Vector Machine (SVM) classifier with kernel functions such as Linear, Quadratic, Polynomial, Gaussian Radial Basis Function (RBF) and Multilayer Perceptron (MLP), and a Probabilistic Neural Network (PNN) in order to detect movement based on changes in the wireless signal strength.

Open access

Sayan Mandal, Samit Biswas, Amit Kumar Das and Bhabatosh Chanda

References [1] Agam, G., Argamon, S., Frieder, O., Grossman, D., Lewis, D. (2006). The Complex Document Image Processing (CDIP) test collection. Illinois Institute of Technology [2] Arai, H., Abe, S., Nagura, M. (1993, October). Intelligent interactive map recognition using neural networks. In Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on IEEE, 922–925 [3] Chaudhuri, B. B., Pal, U. (1997). An OCR system to read two Indian language scripts: Bangla and Devnagari (Hindi). In Document Analysis