Using Big Data Analytics and Visualization to Create IoT-enabled Science Park Smart Governance Platform

Abstract

Science parks are important industrial clusters in the development of Taiwan’s technology industry. Nearly 280,000 employees commute to the science parks on a daily basis. Thus, traffic congestion not only wastes the time of and creates extra fuel costs for the road users, but also leads the vehicles to release more pollutants in the environment. With the rise of Internet of Things technology, the science park administration has established multiple IoT-enabled systems since 2017, in order to collect data and monitor traffic flow and air quality in a more accurate manner. However, it is still a question that how emerging technology should be applied to provide accurate and timely information to assist administration to observe the historical trends and current status of traffic congestion and air quality, so as to formulate traffic control and air pollution prevention strategies. To that end, there are two purposes in this paper: (1) to establish a Science Park Smart Governance Platform to collect data collected from the IoT devices, and (2) to design and develop data visualization functions for the smart management of traffic and air quality. The research garners three results from the smart traffic monitoring service: (1) helping administration check the traffic status in real time, in order to facilitate traffic control; (2) presenting the historical trends of traffic flow on a typical day, month, and year, and allowing administration to understand in what intersections and at what periods traffic congestion is more prone to take place; (3) creating a predictive model of how traffic flow and weather can influence the traffic volume interactively to predict traffic flow for every intersection in the following 10 min, so that administration can operate the traffic lights in order to reduce traffic congestion. Besides the aforementioned results, three other results from the smart air quality monitoring service are presented in the study: (1) allowing administration to monitor real-time air quality status in various areas of the science parks; (2) presenting a historical trend of air quality, and allowing administration to understand in what month/time air pollution is occurring; (3) when the concentration of certain air pollutant exceeds a particular threshold, the smart environmental monitoring Chabot service will push warning messages to the managers.