SMART START: The Roots of Future Cities

What are ‘Smart Cities’ truly made out of? What does a city have to be in order to become one? More importantly, what drives this strong desire to be smart? As cities continue to evolve as they urbanize and conurbate, we find ourselves living in and moving around spaces that rapidly change their behavioral patterns and systems faster–and more intelligently–than its citizens.

Adaptively, we succumb to these transformations in order to reach our common goal of achieving a better quality of life–the driving force for any urban dweller whose lifeways are constantly altered by imposed changes in the urban environment.  To survive–and be able to adjust to new norms–city dwellers learn to adhere to policies turned into actions following well-conceived urban plans and frameworks produced by the city’s think-tanks.

While it is safe to assume that cities are normally driven by the quest for primacy and fame, they are usually triggered by mundane concerns that affect the life of each citizen–regardless which societal category or unit they belong to.

As we adapt to alterations in our daily lives, we become smart in the process.

VERDICT and the History of Smart Cities:Timeline

Verdict is a UK-based online platform that is powered by data and smart visualisation techniques and covers topics surrounding global technology, business and innovation with speed, accuracy and intelligence. In their July 6, 2020 article entitled History of Smart Cities: Timeline, Verdict traversed the journey of smart cities as it traced the ambitious beginnings of the IoT (Internet of Things) as seen through how major cities from around the world manifested their mission to become “smart”–in technological terms, that which we often refer to as being intelligent, advanced, networked.  From this insightful timeline, we focus on how this exciting journey began and take a deep dive into its surrounding stories.

The First Urban Big Data Project: A Cluster Analysis of Los Angeles 1974

Boom California, is a ‘free refereed online media publication dedicated to inspiring lively and significant conversations about the vital social and cultural issues of our time in California and the world beyond’.  It is published by the University of California Press and it showcases journalists, writers, academics, artists, photographers, and students as they engage and initiate vibrant conversations about the most relevant issues confronting the State of California and beyond.  In their June 16, 2015 printed article Uncovering the Early History of Big Data and the Smart City in LA, we [re]discover the accounts of how this ambition came about: its vision as well as its lapses.

While the 1974 Cluster Analysis of Los Angeles Report may be regarded as the first urban undertaking related to Big Data, the City of L.A. (as the abbreviated Los Angeles), is not new to the idea of utilizing computer-assisted data in their policy formulation, analysis, and implementation.  They have been operating within this frame of mind for decades prior to this through the efforts of its Community Analysis Bureau since the late 1960s and through the most part of the decade that followed.  The present day Los Angeles City Planning  has much attribution to the initiatives that had been laid out and there is much to learn from the city’s wealth of experience in the use of data.  These came in the form of an extensive utilization of:

  • Computer Databases
  • Cluster Analyses
  • Aerial Photography

What were these used for? These big data sets were essential as the city collected and analyzed information in their pursuit to produce reports on:

  • Housing Quality
  • Neighborhood Demographics
  • Resource Management

More interestingly, what motivated them to employ such systems? What prompted them to embark on this ambitious, massive undertaking of clustering the largest city in the state? Two major urban issues primarily stand out: blight and poverty.  As drivers of change, the intent to eradicate these two urgent concerns prompted the city government of L.A. to deal with them head on.

The British travel writer Jan Morris wrote a 1976 essay describing L.A. as “The Know-How City” borrowing the vogue words know-how from the 1940s and 1950s–reflecting the “whole climate and tone of American thought in the years of supreme American optimism”.  She explained what this meant as her lines read: “the certainty that America’s particular genius–the genius for applied logic, for systems, for devices–was inexorably the herald of progress”.  With this essay, she put Los Angeles on the pedestal when she acclaimed it as the lone city “where the lost American faith in machines and materialism built its own astonishing monument”. 

The key to understanding the know-how of data is to treat it the same way as how L.A. was the key to the era’s techno-optimism.  It was well-planned and proudly boasted of its intricately-networked systems: its streetcars, freeways, flood control, and water–all modernized infrastructure upon which the city life depended.  Apart from these, Los Angeles had a thriving entertainment industry.  Indeed, the city became a ‘temple of progress’ and was considered as ‘the international symbol of the City of the Future”–this is how its 1970 mayor put it when he introduced the 1970 Community Analysis Bureau report.

It was an era of redevelopment as evidenced by L.A’s alarming maps created by its health, housing, and building departments.  In its report, Los Angeles was not classified using conventional categories but named its clusters quite uniquely.  Some cluster names used were deemed as more appropriate for marketing than is customarily used in the nomenclature of planning:

  • The suburbs from the fifties
  • Richest of the poor
  • The singles of Los Angeles
  • Gracious living

The cluster analysis correlated data and social outcomes as the set included sixty-six types of data to identify which locations had the worst poverty and blight.  In the end, they realized that the most accurate indicators for the manifestations of these two major issues–those being socioeconomic disadvantage and housing decline–could be brought down to just three:

  • Birth weight of infants
  • Sixth-grade reading scores
  • Age of housing

The potent combination of computer analysis and aerial photography (which was largely used and conceived for warfare) proved to be very instrumental in the success of these cluster analyses.  Along with this, climate control was already data-driven as the city regulated every aspect of how they operated and managed affairs from traffic to unemployment and even crime rates.  Their studies have highlighted the fact that addressing only the physical problems–the traditional approach to urban renewal–was not adequate.  They recognized the need to deal with urban decay more holistically–that is, to also cover the social and economic nature of this problem.

The bureau did not fully realize its vision of achieving a ‘smart city’ as we define it today.  This was partly due to the fact that the technology back in the 1970s was perceived as having been too unhatched and immature for it to “allow real-time data to flow to decision makers who could adjust policies and practices on the fly”.  Beyond the oversights, we takeaway lessons learned by Los Angeles for our contemporary approaches to the use and application of computer analyses on urban challenges confronted by those who aspire to become smart cities.

These takeaways underline the need to judge data generated by and for smart cities on the basis of what the city, the academia, and the private sector should harness:

  • Social relevance
  • Volume of data made known to the public
  • Processing power and analysis 

However, fundamental questions persist to this day: 

  • Could this form of digital urbanism really help narrow the gap between the city’s affluent and marginalized sectors?
  • Will smart cities truly aid us in our fight against climate change?
  • How will we honestly and genuinely achieve a better quality of [city] life?

If the cities of the future–as we imagine them to be smart and intelligent–along with open data can push forward and advance efficiency, knowledge, sustainability, and equity, are we to anticipate new ways in analyzing our cities in order for us to fulfill the dream that started at that time and place?

cover image sourced from Pexels as captured by Sergio Souza

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