Page 7 - Unlocking the potential of trust-based AI for city science and smarter cities

1. Introduction

1.1 Background

With the rising economy and social opportunities that urban areas have to offer, people have been
moving from countryside to cities, resulting in the largest wave of urbanization throughout the
world in our history. By 2030, the urban population is estimated to reach 5 billion (about 60 percent
of the world population), which produces massive opportunities for the economic and social
development of cities [1]. Due to the ever-growing demands of local residents, the development of
fundamental infrastructure and policies are lacking behind. Moreover, this unplanned and overly
fast urban growth is amplifying some of the greatest urban challenges that cities are already facing,
including climate change, growing energy demands and consumption, environment degradation,
and human health.

To mitigate the challenges of rapid urbanization, it is imperative to improve governance and service
delivery, offer swift and seamless mobility, facilitate easily assessible urban public facilities, access
to affordable housing, quality healthcare, education etc [2]. A special spotlight is needed, covering
urbanization trends in innovative management of urban operations and delivering a variety of
“smart” services to local residents, visitors, and the government to satisfy the ever increasing and
diverse demands [3].

As an emerging paradigm, the smart city leverages a variety of promising technologies, such as the
Internet of Things (IoT), cyber-physical systems, big data analysis, and real-time control, to enable
intelligent services and provide comfortable life for local residents [4]. It integrates ubiquitous
sensing components, heterogeneous network infrastructure, and powerful computing systems
to sense the physical changes from cities and feed back to the physical world. Specifically, RFID
devices, sensors, and versatile wearable devices are promoted to offer real-time monitoring and
ubiquitous sensing, from energy to environments, from road traffic to healthcare, from home area
to public venues, and so on. Then this sensing information is transmitted to a control center via
heterogeneous networks. This control center takes comparative advantage of powerful computing
systems, such as cloud servers, to process and analyze the collected data.

Fueled by human intelligence, the control center makes optimal decisions and manipulates the
urban operations via feedback components, such as actuators [3]. Having the advanced information,
communication, and control technologies as backbones, a smart city can offer various applications,
including intelligent transportation, smart energy, intelligent healthcare, and smart homes. Not only
can this up-and-coming connected city quickly identify the demands of people and a city, but it can
also manipulate urban operations to improve urban living quality in an intelligent and sustainable
way. It is expected that the global smart city market will exceed US$1200 billion by 2020, which is
almost triple that in 2014 [1].

When cities become smarter, people may suffer from a series of security and privacy threats due
to the vulnerabilities of smart city applications [5]. For example, malicious attackers may generate
false data to manipulate sensing results such that services, decisions, and control in a smart city
are influenced and not “intelligent” enough. Moreover, these malicious attackers could also launch

Unlocking the potential of trust-based AI for city science and smarter cities - October 2019 1