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\chapter{Research Description}  This chapter presents an overview of the current state of technology on data collection for Vehicular Traffic. The researchers will discuss the various techniques that are currently used on other studies and how significant the research of finding a low cost technique is to aid in traffic data collection within a developing country.   \section{Overview of the Current State of Technology}  Traffic Congestion is a dire problem that the Philippines experiences, especially in Metro Manila. It is brought about by the migration of population, urban growth and infrastructural constraints (Mathew, Xavier, 2014). Unpredictable commute times,   environmental pollution and fuel waste are just some of the negative effects that traffic congestion mainly creates which results to losses in resources such as time and money.These remain to be a problem for developing cities and countries around the world due to poorly road network planning and traffic management (Jain, Sharma, Subramanian, 2012). Presently, there are many different techniques in detecting traffic density such as RF-Id tags, Wireless Sensor Networks (WSN), Vehicular Ad-hoc Networks (VANET), Infrared System, Bluetooth, Zigbe, Multi-Agent Systems, Cameras, GPS and the use of mobile signals including 2G, 3G and LBS Systems (Mathew, Xavier, 2014).  However, with numerous sensors, telemetry and telematics devices and other on-line traffic and mobility data collection tools utilized for monitoring traffic, most of them are more usable in developed countries. According to a study of road traffic conducted in India (Sen,2013), developing countries and developed countries have roads with different characteristics such as high heterogeneity of vehicles and traffic roads without lanes or road markings. These roads are packed with the same heterogeneous vehicles altogether to utilize the available road space. This makes it impossible for traditional sensors to be efficiently useful without careful modification and correct sensor placement (Sen,2013).  The Philippines currently has Metro Traffic Live! application for mobile phones that is a part of the web application, Metro Manila Traffic Navigator (TNAV). Additionally, the MMDA Traffic Mirror, which is a real-time and online video feed of the current road situation, is the latest CCTV monitoring technology collaborated with InterAksyon.com, the online news portal of TV5 to allow motorists to monitor on the road traffic virtually.However, the video stream are not as reliable when the 100 HD cameras installed are not working properly. On the other hand, the development of the application, Metro Traffic Live! and TNAV, made a significant impact on informing the motorists the latest traffic status along the major roads, and thus would be the best platform to build through for improving the ICT in transportation management by collecting additional traffic data that is reliable and low cost at the same time.   In order to do this, the researchers explored references that compares the differences in terms of advantage and disadvantages of existing and newly studied sensors such as acoustic, gas technology and laser sensing in accounting for road traffic density to prove a low cost mean to produce real-time, reliable data.  Many techniques and resources are presented in the statements above to collectively gain data on traffic for traffic management purposes. Among the potential solutions that are presented, not all are applicable to a current developing countries such as the Philippines. This study will find a low cost but reliable real-time traffic data collection that can be used additionally aid the data collection source of existing systems that the government has initiated already and for other future purposes.   \section{Research Objectives}  \subsection{General Objective}  With not much vehicular traffic data source in the country, the research aims to produce a low cost but reliable alternative in collecting traffic data through the use of existing resources on the road. This includes noise pollution and/or carbon gas emissions to detect the density of traffic.   \subsection{Specific Objectives}  \begin{enumerate}   \item To find and utilize a low cost but reliable sensor fit to detect traffic density.  \item To practice data cleaning techniques on sensor outputs.  \item To determine a method/s to check the accuracy and reliability of the resulting collected traffic data.  \item To use available techniques/tools in order to determine the best location to place the sensors.  \item To analyze how a network of sensors can generate reliable traffic data for road segment reports.  \end{enumerate}  \section{Scope and Limitations of the Research}  \begin{enumerate}   \item Limitations of the sensors in terms of range and susceptibility to environment.  \item The researchers will use a data cleaning techniques fit for the sensor technology to be used with as minimal errors as possible.  \item Comparative tools to check against the data collected from the sensors are limited to Waze, Google Live Traffic and the likes.  \item The researchers are limited to a number of sensors in a certain road segment.  \item Overall road traffic analysis is limited to certain road segments.  \end{enumerate}  The study's scope does not concern itself with other road activities such as pedestrians, weather disasters and/or other events in great focus.   \section{Significance of the Research}  Since the country is a developing society, the need for a low cost but reliable data collecting technique should be made available to continually progress the ICT trends in traffic management and monitoring. Finding a solution to address this matter without disrupting the existing day-to-day activities of the motorists must be made available through utilizing the current resources that are around the area/subject of concern.  This study will be able to contribute in strengthening the existing projects that the government has currently initiated. If the government can no longer expedite larger funds to support data collection on traffic, this study can be an alternative for cost effective researches in the future. At the same time, data collected can be used for a wider range of purposes such as in the advancement of smarter cities in the country.   The study will be useful for future researchers in Computer Science who would be interested in the branch of Traffic Management Engineering that consists the need for a broader knowledge in terms of expert systems, applications and network implementations.