# Traffic Congestion Detection System through Connected Vehicles and Big Data
## 2 Related Work  
Today, the Internet is an indispensable tool for billions of people as it enables them to overcome many communication barriers (space, time, distance), as well as help them simplify many everyday activities. However, this was not always the case. In the past 50 years, the Internet's evolution has been unprecedented as it evolved from being a small research network, consisting of a small number of nodes, to a huge global network that supplies services around the world [15]. It continues to grow at an incredible pace, expanding to other areas, devices and contexts of everyday life, due greatly to the advances and integration of Micro-Electro-Mechanical Systems (MEMS) and wireless communication technologies. These important advances have led to the development of increasingly smaller devices with monitoring, computing and wireless communications capabilities, all of which contribute to the Internet of Things (IoT) [16]. The relatively new discipline of ubiquitous computing, whose aim is to integrate technology into the activities or things used in everyday life, or to monitor the behavior of the world around us, was first conceived of in the late 1980s. Given the precedents of the Internet and ubiquitous computing, the IoT refers to the integration of devices with monitoring, actuation, computing and communication capabilities into everyday activities, using devices that can identify behavior in the physical world and use the infrastructure, tools and cyber space services to make decisions [17]. By 2020, it is estimated there will be more than 20 billion devices involved in the Internet of Things, in large part due to the expansion of the world's telecommunications infrastructure, a figure 30% higher than the items/devices that currently exist [18]. With the growth of the Internet's infrastructure, along with increased user growth and more integrated IoT devices, it is estimated that between 2005 and 2020, the volume of data worldwide will grow from 130 exabytes to 40,000 exabytes. Considering the challenges imposed by the increasing volume of data worldwide, the term \"big data\" was coined, which not only solves the paradigm of storing large amounts of data, which is seen as the new oil of the 21 st century, but also considers processing schemes, using technologies and techniques to extract valuable and relevant information [19]. IoT and big data have been identified as two critical emerging technologies in the field of IT as shown in the IT Gartner Hype Cycle, shown in Figure 1. A Hype Cycle, is a study that can represent the novelty, adaptation, maturity and impact of specific technological applications. According to the study of emerging technologies [20], IoT and big data technologies will become technologies that are conventionally embedded in many everyday products in the next five to ten years. Although large-scale adoption of big data technologies will take another 5 to 10 years, this time could be significantly reduced if big data challenges can be solved quickly. The complexity of data integration, real-time data handling, existing data warehouse architectures, data security and privacy represent some of the major challenges that restrict the adoption of big data technologies [21]. In response, several researchers have proposed new approaches and strategies based on scheme mapping, record linkage and data fusion, to reduce the complexity of data integration [22; 23; 24]. Additionally, some investigations have proposed novel architectures to process or analyze data in real-time big data applications [25; 26; 27]. Research along these lines is important as existing data warehouse technologies cannot currently handle the additional demands of new dynamic data sources and analytic workloads that users actually demand. For these reasons, tools are presently being developed to assist existing infrastructure migrate to new big data schemes [28].