Real-Time Distributed Pipeline Architecture for Pedestrians' Trajectories

Cities are suffering from traffic accidents. Every one results in significant material or human injuries. According to WHO (World Health Organization), 1.35 million people perish each year as a consequence of road accidents and more end up with serious injuries. One of the most recurrent factors is distracted driving. 16% of pedestrian injuries were triggered by distraction due to phone use, and the amount of pedestrian accidents caused by mobile distraction continues to increase, some writers call Smombie a smartphone zombie. Developing a system to eliminate these incidents, particularly those caused by Smombie, has become a priority for the growth of smart cities. A system that can turn smartphones from being a cause of death to a key player for pedestrians' safety. Therefore, the aim of this paper is to develop a real-time distributed pipeline architecture to capture pedestrians' trajectories. We collect pedestrians' positions in real-time using a GPS tracker mounted in their smart phones. The collected data will be displayed to monitor trajectories and stored for analytical use. To achieve real-time distribution, we are using delta architecture. To enforce this pipeline architecture, we are using open-source technologies such Traccar as GPS tracking Server and Apache Kafka to consume the collected data such as messages, Neo4j to store the increasing data collected for analytical purposes, as we use Spring boot for API development, and finally.