Big Data Analytics and Internet of Things for Urban Transportation: A Case of Pune City, Maharashtra, India

Big Data Analytics and Internet of Things for Urban Transportation: A Case of Pune City, Maharashtra, India

Jyoti Chandiramani (Symbiosis International University (Deemed), India) and Sushma Nayak (Symbiosis International University (Deemed), India)
Copyright: © 2019 |Pages: 34
DOI: 10.4018/978-1-5225-6207-8.ch011

Abstract

The idea of smart city has assumed popularity in numerous countries across the globe. In 2015, the Government of India embarked on a mission of creating 100 smart cities to sustain the burgeoning urban population. While a wide-ranging set of fundamentals has a key role in enhancing the quality of life of citizens, the chapter revolves around transportation issues and traffic management concerns in one of India's smart cities, Pune. Transport is one of the few areas where Pune lags behind compared to its urban counterparts in the country. Public transportation in the city has been ineffectual, and auto rickshaws have been unyielding and pricey, thus making it imperative to possess personal vehicles or resort to app-based cab services. A palpable outcome of this has been traffic congestion that leads to slower travelling speeds, extended trip times, and amplified vehicular queuing. Big data and IoT can make a considerable impact in realizing the smart city objectives for efficient transportation in Pune by serving as complementary measures to supply-side policies.
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Introduction

The idea of smart city – an urban region where information and communications technology (ICT) is the fundamental infrastructure for offering essential services to citizens – has assumed popularity in numerous countries across the globe. The smart city transformation is fueled by technology advancements. A smart city is known to efficiently leverage technology, transportation, communications, amenities, government policies and citizen involvement for designing an urban setting that reinforces modernism, progress, productivity, and sustainability. It is a concept that primarily considers the needs of citizens to draw up plans for meeting their requirements in real time. A smart city makes us envision a host of conveniences. For instance, streetlights would turn up or turn off depending upon the movement of people and vehicles. Trash would be cleared as soon the garbage container gets crammed with the waste. Notification on traffic and air pollution could be received on mobile phones with respect to the intended travel destination. Availability of parking spaces could be learnt through mobile apps. Eateries and cafés would put forward menus suiting popular tastes and preferences. Billboards and hoardings would flash advertisements in conformity with the bystanders’ latest purchase patterns. Such services are deemed to improve livability for city dwellers.

A smart city, although, is not just about infusion of technology into the life of people, but a lot more. It is also about smart governance and smart citizenry (Khanna, 2015), wherein the benefactors and the beneficiaries are expected to be committed towards fulfillment of their obligations for the realization of smart city initiatives. Smart cities are “places where information technology is combined with infrastructure, architecture, everyday objects, and our own bodies to address social, economic, and environmental problems” (Townsend, 2014).

The concept of smart city has not originated today but has prevailed since several years in different epithets and forms. The introduction of programmed traffic lights in Houston, Texas, in the early 1920s, was categorically a smart initiative (Poole, 2014). However, the model that typifies the present-day smart cities and those likely to emerge in the future has undergone massive transformation in recent decades to reflect sizeable concepts upheld by advocates and stakeholders. Likewise, the significance of various terminologies has altered over time, contingent upon the ideas forwarded by academia, entrepreneurs, political groups and civil society (Eremia, Toma & Sanduleac, 2017). A major development in this regard happened in 2008 when the American multinational IBM commenced working for a ‘Smarter Planet’ vision to come up with intelligent systems that were far more advanced and user-oriented than ever before (Puri, 2014).

One of the contemporary ways having enormous potential to advance smart city services is big data analytics (Al Nuaimi, Al Neyadi, Mohamed & Al-Jaroodi, 2015). Big data implies extensive datasets which were not within the realm of perception, acquisition, organization, and processing of conventional information technology and software/hardware tools within a suitable time dimension (Chen, Mao, & Liu, 2014). The vastness of big data is evident from five Vs – Volume, Veracity, Variety, Value and Velocity (Yin & Kaynak, 2015). The progression of big data and the development of Internet of Things (IoT) technologies have played a crucial role in the viability of smart city initiatives. Big data extends the potential for cities to get hold of meaningful insights from copious datasets gathered through a range of sources; likewise, IoT permits the adaptation of sensors, Radio-Frequency Identification (RFID), and Bluetooth in the real-world setting by means of highly networked services (Hashem et al., 2016). With the technical support from big data and IoT, a smart city thus leans on a triad – being instrumented (mechanized), being interconnected (unified) and being intelligent (smart, automatic and self-regulating).

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