Abstract

This paper systematically reviews the top 200 Google Scholar publications in the area of smart city with the aid of data-driven methods from the fields natural language processing and time series forecasting. Specifically, our algorithm crawls the textual information of the considered articles and uses the created ad-hoc database to identify the most relevant streams “smart infrastructure”, “smart economy & policy”, “smart technology”, “smart sustainability”, and “smart health”. Next, we automatically assign each manuscript into these subject areas by dint of several interdisciplinary scientific methods. Each stream is evaluated in a deep-dive analysis by (i) creating a word cloud to find the most important keywords, (ii) examining the main contributions, and (iii) applying time series methodologies to determine the past and future relevance. Due to our large-scaled literature, an in-depth evaluation of each stream is possible, which ultimately reveals strengths and weaknesses. We hereby acknowledge that smart sustainability will come to the fore in the next years—this fact confirms the current trend, as minimizing the required input of energy, water, food, waste, heat output and air pollution is becoming increasingly important.

Highlights

  • Our algorithm crawls the textual information of the considered articles and uses the created ad-hoc database to identify the most relevant streams “smart infrastructure”, “smart economy & policy”, “smart technology”, “smart sustainability”, and “smart health”

  • The number of articles at Google Scholar is predicted based on a polynomial regression, that is, we model the relationship between the independent variable and the dependent variable as an n’th degree polynomial

  • We find that smart infrastructure is the largest stream with 47 publications, followed by smart economy & policy (46), smart technology (45), smart sustainability (42), and smart health (20)

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Summary

Introduction

The journey of smart cities, for example [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200], dates back to the mid 1970s, when Los Angeles launched the first large-scale urban data project [201]. According to Gartner, the world’s leading research and advisory company, the concept of smart city develops holistic solutions in the field of urban ecosystems using collected data from different types of electronic internet of things (IoT) sources [202]. For this purpose, information about buildings, citizens, devices, and assets are processed to efficiently manage urban flows via real-time responses.

Categorization of Smart City Literature
Smart Infrastructure
Smart Technology
Smart Sustainability
Smart Health
Findings
Conclusions
Full Text
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