Internet of Things Interpreting a Myth: Internally Displaced Persons Transform Cities of Hardship Into Chaos Cities

Internet of Things Interpreting a Myth: Internally Displaced Persons Transform Cities of Hardship Into Chaos Cities

Hisham Abusaada (Housing and Building National Research Center (HBRC), Egypt) and Abeer Elshater (Ain Shams University, Egypt)
DOI: 10.4018/978-1-5225-9238-9.ch004

Abstract

The livability standard still has not considered the chaos city that may stem from or lead to cities of hardship. This chapter rectifies this by making the phenomena of chaos and hardship the centerpiece of the analysis. It depends on the internally displaced persons (IDPs) to display the characteristics of liability and the hardship of living and be the indicators of chaos city. This chapter addresses the non-perceptible processes of the IDPs from outside and inside Cairo in Egypt. This internal displacement supposes the lead-in to chaotic changes in the lifestyles of the cities; it can even be said that they become cities of hardship. The theoretical reading depends on conventional and digital methods (content analysis and the internet of things) to follow these changes, which occur not only due to migrations but also due to ignoring decentralization. The outcomes provide an action plan to create cities free from hardship, displacement, and chaos.
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Introduction

Over the last four decades of the twentieth century, Western literature discussed the issues of the “liveable cities” (Lash, 1976; Lennard & Lennard, 1995; Casselati, 1997; Hahlweg, 1997; Salzano, 1997; Vuchic, 1999) and the “quality of life” (Pacione, 1990; Ley & Newton, 2010; Okulicz-Kozaryn, 2013; Kraftl, 2014; European Environmental Agency (EEA), 2009; Mohit & Iyanda, 2016). At the beginning of the 2000s, the terms “material hardship” and “chaos city” have referred to the opposing nature of liveability and quality of life. The first focuses on inequality in the provision of minimum goods to all citizens to achieve a decent living; it leads to extreme poverty (Allen & Browne, 2010; Pilkauska, Currie, & Garfinkel, 2012; Nelson, 2011). The second indicates to city-life systems (Robinson J., 2000; Pulsellic, Ratti, & Tiezzi, 2011).

Urban chaos and visual or spatial chaos are supposed to cause cities of hardship, which seem difficult to live in (Mumford, 1938; Lynch, 1960; Jacobs, 1961). They have been characterised by the deterioration of the societal situation economically and socially and of the politics of many traditional cities in the developing world. The hardship of living remains one of the main reasons that people are disadvantaged economically and lack the equality needed to flee from their cities, which do not provide a good standard of living, particularly in economic and socio-cultural terms, so they try to settle in other cities located in the same country. In addition, the hardship makes them move from one place to another within the same city to provide a better standard of living. Those people, known as the IDPs, not only become part of the cities’ poverty belts (Carrillo, 2009, p. 546) but may also lead to chaos city, which is increasing the hardship of living. Now, the questions are as follow: Does the hardship of living cause chaos city or vice-versa? Is there a real role for the IDPs in influencing all these phenomena? Is there a relationship between hardship, chaos and the concepts of Liveability?

The fundamental problem that faces us is the chaos displaced persons cause in the city; few studies claim that the displaced persons in the host communities cause chaos (Fan, 1999; Fielden, 2008; Carrillo, 2009). Some scholars believe that urban chaos occurs for two reasons (Abusaada, 2016; Abusaada & Elshater, 2017; Abusaada & Elshater, 2019). The first reason is the policies of governmental centralisation that chooses projects that generate substantial economic returns in the capital and large cities, depriving the smaller towns of these projects1. These policies produced cities of hardship, and consequently, forced some citizens to be displaced from their primary cities (Downing, 2002; World Economic Forum, 2017, pp. 16-17). The second reason is the non-enforcement of laws in large cities, mainly in traffic congestion2, particularly non-adherence to traffic regulations and traffic mismanagement (Kiunsi, 2013, p. 95; Frances Agyapong, 2018, p. 87), as well as the street children, street vendors and marginalised people (Sande-Friedman, 2013; Abusaada & Elshater, 2019). To the best of our knowledge, no study has yielded actual results linking the three causes of the three elements of the problem (cities of hardship, the IDPs, chaos city). To illuminate this undiscovered area, we investigate this issue in the Egyptian context by using content analysis and the Internet of Things (IoT) to interpret the big data analysis on the internet.

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