{'fraction_non_alphanumeric': 0.018950437317784258, 'fraction_numerical': 0.0058309037900874635, 'mean_word_length': 4.995633187772926, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Smartphone-Based Passenger Assistant for Public Bus Commute in Developing Countries

Although public transport vehicles such as buses have always been an economical means of commuting in the cities of many developing countries, it is always considered as a secondary mode of transport owing to poor infrastructure, chaotic and reckless driving habits, and absence of any proper information system in buses. Based on rigorous experiments carried out over a period of two years and multiple surveys, we have tried to learn the problems faced by bus commuters. As a solution, in this article, we develop a novel energy-efficient system which would help commuters navigate through their journey safely. Along with making them aware of any upcoming points of concerns (PoCs) such as sudden bumps, sharp turns, and bad roads, we also inform commuters about the expected time of arrival at the destination. The system makes use of several landmarks such as speed breakers, turns, and bus stops on a trail stored in a specialized data structure, the probabilistic timed automata. We conducted extensive experiments using 25 volunteers over 50 trails. The system showed an average localization error of only 50 m and mean estimated time of arrival (ETA) error of 2.5 mins and a fairly high alert prediction accuracy while consuming significantly less energy when compared to GPS.