The sensor desert quandary: What does it mean (not) to count in the smart city?

Abstract

As a central component of the smart city, sensor infrastructures locate and measure a wide range of variables in order to characterise the urban environment. Perhaps the most visible expression of the smart city, sensor deployment is a key equity concern. As new sensor technologies and Big Data interact with social processes, they have the potential to reproduce well-documented spatial injustices.Contrary to promises of providing new knowledge and data for cities, they can also create new gaps in understanding about specific urban populations that fall into the interstices of data collectionsensor deserts. Building on emerging data justice debates, specifically considering distributional, recognition, and procedural forms of injustice, we conceptualise and analyse sensor deserts through two case studies, Newcastle's Urban Observatory (UK) and Chicago's Array of Things (USA). Open sensor locations are integrated with small-area, socio-economic data to evidence the demographic configuration and spatialities of sensor deserts across each city. We illustrate how the structural processes via which inequality is reinforced by smart agendas manifest as uneven social and spatial outcomes. In doing so, the paper opens up a new conceptual space in which to consider what it means (not) to count in the smart city, bringing a demographic perspective to critical debates about smart urbanisms.

A Smart Right to the City—Grounding Corporate Storytelling and Questioning Smart Urbanism

“…In this sense, we argue for an in-depth analysis of the (un)collected data in terms of (in)justice, to which we have not given attention in this article. We assume that Big Data and the indicators developed from it reinforce structural sociospatial discrimination and injustices [85][86][87], for the (non)collection of certain data often obscures the underlying algorithmic violence that "works through data-driven planning technologies to depoliticize and leverage power while further entrenching racism and inequality" [88] (p. 200) [89].…”

Estimates of the Ambient Population: Assessing the Utility of Conventional and Novel Data Sources

“…Therefore, it is crucial that the cameras are situated in appropriate locations and that there are sufficient devices to capture footfall in different geographical areas. Ensuring the equitable distribution of footfall cameras is a crucial issue [49]. While sensors are able to produce new data and subsequently new knowledge about urban population, where there is a lack of coverage gaps emerge, resulting in so-called 'sensor deserts' [49].…”

Optimising for equity: Sensor coverage, networks and the responsive city

“…Pablo Bello et al 2017;Hong et al 2019). Moreover, sensors that monitor urban challenges are situated within urban environments that are inherently unequal, and technologies tend to replicate this unevenness (Shelton et al 2015;Dencik et al 2016;Robinson and Franklin 2020). As such, the data they produce rarely includes everyone equally or in a representative way (Shelton et al 2015), typically divided based upon existing forms of social difference (race, income, class, ethnicity, age, disability) (Brannon 2017).…”

“…In practice, this gure is likely to be even lower depending on the quality of the sensor infrastructure and the characteristics of the local built environment. The larger value of 500 metres provides a perhaps more realistic picture of the granularity a decision-maker might attempt to achieve when planning sensor coverage across a large urban conurbation, especially when thinking beyond data quality to consider sensor coverage as an issue of representation (Robinson and Franklin 2020) [1] .…”

“…The spatial distribution of the existing UO network is most closely aligned with the distribution of sensors based on the network optimised for workplace population (illustrated by a higher number of white areas in which coverage difference is zero) (Figure 10). However, there are areas for which existing sensor coverage is sparse, including relatively deprived, post-industrialised areas along the north bank of the River Tyne-what might be termed sensor deserts in the existing network (Robinson and Franklin 2020). Yet the UO network provides a higher level of coverage in the centre of the city, where people across all demographics are likely to congregate and spend much of their time, when compared with each single objective network.…”