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Delineation of connected buses and smart bus shelter by employing IoT and Machine Learning

机译:通过物联网和机器学习来描述互联巴士和智能巴士候车亭

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In this world, one of the major IT (Information Technology) hub is located in Bengaluru, Karnataka, in the developing country of India and hence technological effectuation is expected. Many people are availing the state bus transport facility for their day to day life activities. This research focuses on the concept of smart bus shelter under smart city mission. It promotes the idea of a bus shelter and connected buses. The former is equipped with IoT technologies like smart lights and information kiosk, for the benefit of both stakeholders and commuters. The latter deals with bus schedule information wherein the passengers are made aware of the bus schedule, thereby minimizing the waiting time in the shelter which in turn will lead to the minimization of the crowd density in shelters and as well as buses. The bus shelter is equipped with Zigbee Receiver, Raspberry Pi and other IoT modules which sends data to a cloud periodically. The data is then analysed against the bus schedule for the ease of operations in real-time. Machine learning (ML) algorithm is applied to predict the crowd density well in advance. In addition to all this, an android mobile application and a website have been developed for educating the commuters on bus information and crowd density and help them plan their travel accordingly.
机译:在这个世界上,主要的IT(信息技术)中心之一位于印度发展中国家的卡纳塔克邦班加罗尔,因此有望实现技术。许多人正在利用国家公共汽车运输设施进行日常活动。本研究着重于智慧城市使命下的智能公交候车亭概念。它提倡了公交车候车亭和连接的公交车的想法。前者配备了智能照明和信息亭等物联网技术,以使利益相关者和通勤者受益。后者处理公共汽车时刻表信息,其中使乘客知道公共汽车时刻表,从而最小化在避难所中的等待时间,这又将导致在避难所和公共汽车中的人群密度最小化。公交候车亭配备了Zigbee接收器,Raspberry Pi和其他IoT模块,这些模块定期将数据发送到云中。然后根据总线时间表对数据进行分析,以简化实时操作。应用机器学习(ML)算法来提前很好地预测人群密度。除此之外,还开发了一个android移动应用程序和一个网站,用于对通勤者进行公交信息和人群密度的教育,并帮助他们相应地计划出行。

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