A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems

Abstract

W e are currently witnessing the fourth industrial revolution 1 . Technological innovations have altered the way in which economies operate and how people interact with built, social and natural environments. One area of transformation is the emergence of robotics and autonomous systems (RAS), defined as technologies that can sense, analyse, interact with and manipulate their physical environment 2 . RAS include unmanned aerial vehicles (drones), self-driving cars, robots able to repair infrastructure, and wireless sensor networks used for monitoring. RAS therefore have a large range of potential applications, such as autonomous transport, waste collection, infrastructure maintenance and repair, policing 2,3 and precision agriculture 4 (Fig. 1). RAS have already revolutionized how environmental data are collected 5 and how species populations are monitored for conservation 6 and/or control 7 . Globally, the RAS market is projected to grow from $6.2 billion in 2018 to $17.7 billion in 2026 8 .Concurrent with this technological revolution, urbanization continues at an unprecedented rate. By 2030, an additional 1.2 million km 2 of the planet's surface will be covered by towns and cities, with ~90% of this development happening in Africa and

Valuing the Role of Time in Urban Ecology

“…Stochasticity has been considered in some ecological studies looking for instance at biological control of invasive species in the wild (Evans et al, 2012) and community ecology (Ning et al, 2019;Shoemaker et al, 2020). To date, however, little effort has been placed toward evaluating how stochastic vs. deterministic processes in cities can affect biological communities and urban ecology (Caruso et al, 2017;Goddard et al, 2021). Recent research shows, however, that specialist insect herbivore populations in cities might be governed more by stochastic events rather than deterministic drivers (Herrmann et al, 2012).…”

Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

“…On the other hand, autonomous vehicles-in the form of private autonomous cars-could increase mobility and urban sprawl, and thus increase transport carbon emissions [23]. Issues similar to these bring up the need for technological innovation in the context of cities, or in other words urban innovation, to become responsible for maximizing the desired outcomes and positive impacts for all and minimizing the unwanted ones [24][25][26].…”

Deploying digitalisation and artificial intelligence in sustainable development research

“…Despite the attempts that try to tackle sustainability problems by adopting a more systemic and interdisciplinary perspective, several other studies address the AI and digitalisation related methods to advance specific SD challenges such as urban water management (Goralski & Tan, 2020 ; Xiang et al, 2021 ), disaster detection (Al Qundus et al, 2020 ; Alizadeh & Nikoo, 2018 ; Sublime & Kalinicheva, 2019 ), recycling and waste sorting (Bircanoğlu et al, 2018 ), poverty assessment and monitoring (Alsharkawi et al, 2021 ; Jean et al, 2016 ), food consumption and sustainability (Abdella et al, 2020 ), sustainable cities/urban ecosystems (Goddard et al, 2021 ; Ilieva & McPhearson, 2018 ; Majumdar et al, 2021 ; Vinuesa et al, 2020 ), threat to biodiversity (Jensen et al, 2020 ), health-related issues (Pirouz et al, 2020 ), smart sustainable agriculture (Alreshidi, 2019 ; Boev et al, 2020 ), climate action (Balogun et al, 2020 ; Fuso Nerini, Slob, et al, 2019 ; Fuso Nerini, Sovacool, et al, 2019 ; Huntingford et al, 2019 ), environmental evaluation (Liu et al, 2021 ), and enterprise management for SD (Kościelniak et al, 2019 ).…”

“…First, of all systems associated with AI, machine learning tends to be one of the most promising in the context of SD research (Abdella et al, 2020 ; Alsharkawi et al, 2021 ; Huntingford et al, 2019 ; Jean et al, 2016 ; Jensen et al, 2020 ; Majumdar et al, 2021 ). Second, substantial agreement exists to suggest that AI and digitalisation have clear applications to the study of smart grids (Aly, 2020 ; Kotsiopoulos et al, 2021 ; Liang et al, 2020 ; Qadir et al, 2021 ; Shi et al, 2020 ; Talaat et al, 2020 ) and smart and low-carbon cities (Fuso Nerini, Slob, et al, 2019 ; Fuso Nerini, Sovacool, et al, 2019 ; Goddard et al, 2021 ; Ilieva & McPhearson, 2018 ; Majumdar et al, 2021 ). Third, concerns about the need for regulatory oversight and the effective enforcement of transparency, safety, and ethical standards resonated widely among both survey participants and authors of related scholarship (Vinuesa et al, 2020 ).…”