{'fraction_non_alphanumeric': 0.017366136034732273, 'fraction_numerical': 0.0, 'mean_word_length': 5.0701754385964914, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Localization in Ad-Hoc networks

Localization is an inevitable challenge when dealing with wireless sensor nodes and a problem that has been studied for many years. Nodes can be equipped with a Global Positioning System (GPS), but this is a costly solution in terms of volume, money and power consumption. The algorithm presented here in relies on range measurements between pairs of nodes and a priori coordinates of sparsely located anchor nodes. In this paper, we discuss a robust and distributed RSSI-based estimation algorithm for wireless sensor network. A neural network is trained with precise localized nodes coordinate training set and localizes any unknown node physical location.