Big Data & IoT: The Source of Smart City Transportation

It is estimated that by 2030 the world’s population will be around 5 billion, located around major metropolitans worldwide. The urbanization development (where we left off in a previous column, “City Growth, Urbanization and Supply Chain Developments”) along capital suburbs is picking up the pace in noteworthy ways. Consequentially, ineffective and unsustainable processes that come with such population expansion increases the likelihood of unnecessarily depleting both natural resources and man-made infrastructures required to coup with everyday living. Technology, nonetheless, saves the day by facilitating innovations that are key to resolving daily problems amongst these growing communities, efficiently and effectively, whether it be the use of Cloud Computing or Big Data processing to analyze causes and solutions. Advanced technology allows better traffic conditions and transits for regular commuters and minimizes unfeasible practices that come with expanding population and infrastructure requirements, as well.

No one likes being stranded on city roads every day – it takes a toll on health, eventually. The stress from traffic jam can cause high blood pressure and gained weight. Evident in America; regular motorway commuters are stuck in traffic for over 42 hours per year, 37 hours longer compared to year 2000, and increasing. In developing countries, not only are populations noticeably moving to and developing new cities, they are increasing consumption of consumer goods, luxury products and transportation vehicles. In 2015, over 172 million Chinese owns a car resulting in China being ranked first among top 50 cities in the world for traffic congestion, for example. One obvious trend is, as cities struggle to reduce traffic congestion, every solution revolves around Big Data and a computing Cloud.

A myriad of information can be compiled from traffic systems during congestions, from people roaming the streets, to the time they reach their destination and peak hour density. For city planning and development to be data-driven and as accurate as possible, though, traffic systems need to be connected in a meaningful way with regards to troubleshooting and solution designing. That said, how much data is required to yield meaningful patterns from the mostly generic information?

The city of San Francisco has reached a promising answer with a Smart Parking System, an experiment conducted using advance parking mechanisms with interconnected sensors mounted along street parking spots in the city. The sensoring system sends data to the application that notifies drivers in real time of available spots, where they are and the street direction leading to it. As a direct effect, drivers use less time find parking and road congestion is significantly reduced, obviously, since loops around the blocks are minimized. Meaningless to say, so are fights over parking spots, as well.

Another attempt to reduce traffic congestion took place in China in 2013, in Fujian, a coastal county in the southeast of China, which launched a municipal scale Smart City Transportation strategy developed by the University in Fujian. The system transformed data collection and analysation processies to a real time Big Data Platform which allows accurate image data across the county to be administered in synchronization through Cloud Computing. GPS capabilities will be installed in Fujian county where data update takes place every 30 seconds to handle over 120,000 public car parks. Data is also transmitted through CCTV cameras and traffic lights along various intersections. Such mechanism also includes GPS route tracking and analysation of most popular routes, too.

A tremendous amount of information will be used for analytical and designing of traffic solutions, including drafting the transportation policy and the role of public transport services while the number of motor vehicles on the road increase with significance. However, acquisition of data that cannot be processed is a bridge to nowhere. Many companies are looking for partners with the potential to provide Cloud-based Storage Space to make the most out of cultivating and handling data. Ultimately, the processing of traffic data by seamless integration of Big Data and Cloud computing only serves as an alternative that aids customers’ decision making in the form of refined itineraries, such as best routes and directions to destination and back, best times to travel, and etc. all of which makes urban life easier for the long term in the context of population expansion. 

Compiled by BLOG.SCGLogistics

References and Pictures by forbes.com, dell.com, pexel.com, pixabay.com (account :suyashdixit)

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