Data as Infrastructure for Smart Cities

Suzuki, Larissa; Finkelstein, Anthony

doi:10.1049/pbpc023e

Cited by 7 publications

(4 citation statements)

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“…In the smart city, infrastructure is not only the pipes and roads, but also the data that undergirds the life of the city. Practitioners are abuzz about data infrastructures and data as infrastructure of the smart city (Suzuki and Finkelstein, 2019) but such notions have not entered the critical lexicon. But why not?…”

Section: Data As Infrastructurementioning

confidence: 99%

Squeaky wheels: Missing data, disability, and power in the smart city

2021

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Data about the accessibility of United States municipalities is infrastructure in the smart city. What is counted and how, reflects the sociotechnical imaginary (norms and values) of a time or place. In this paper we focus on features identified by people with disabilities as promoting or hindering safe pedestrian travel. We use a regionally stratified sample of 178 cities across the United States. The municipalities were scored on two factors: their open data practices (or lack thereof), and the degree to which they cataloged the environmental features that persons with disabilities deemed critical for safe movement through urban spaces. In contradiction to the dominating narrative of too much data and not enough analyses, we find that when it comes to data points that might be useful to persons with disabilities, data are lacking. This data gap has consequences both politically and materially—on one hand data could help enforce compliance with the Americans with Disabilities Act, on the other they would allow for safe route planning. We find that reading these data formats and collection patterns from the perspective of critical disability studies—particularly those whose work disrupts notions of “normal” —helps answer questions about potential benefits and harms of data practices. This lens has the potential to promote analysis that is as disruptive to injustices as it is practical.

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Section: Data As Infrastructurementioning

confidence: 99%

Squeaky wheels: Missing data, disability, and power in the smart city

2021

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“…To deal with the challenges in current urban perception systems, such as information fragmentation and islanding problems (Suzuki, 2015;Priano et al, 2016), the trend is towards building a multidimensional intelligent perception and reasoning engine, which is called 'iEye' in this article. Specifically, based on the collected massive image and video data in an urban scale, and through associative analyzing and synthesis reasoning, the iEye system is expected to have features that include big capacity, large view-angles, big data, and excellent service.…”

Section: Ieye: Towards Urban Omnidirectional Intelligent Perception Amentioning

confidence: 99%

Towards human-like and transhuman perception in AI 2.0: a review

Chen

Xiong

et al. 2017

Frontiers Inf Technol Electronic Eng

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Perception is the interaction interface between an intelligent system and the real world. Without sophisticated and flexible perceptual capabilities, it is impossible to create advanced artificial intelligence (AI) systems. For the next-generation AI, called 'AI 2.0', one of the most significant features will be that AI is empowered with intelligent perceptual capabilities, which can simulate human brain's mechanisms and are likely to surpass human brain in terms of performance. In this paper, we briefly review the state-of-the-art advances across different areas of perception, including visual perception, auditory perception, speech perception, and perceptual information processing and learning engines. On this basis, we envision several R&D trends in intelligent perception for the forthcoming era of AI 2.0, including: (1) human-like and transhuman active vision; (2) auditory perception and computation in an actual auditory setting; (3) speech perception and computation in a natural interaction setting; (4) autonomous learning of perceptual information; (5) large-scale perceptual information processing and learning platforms; and (6) urban omnidirectional intelligent perception and reasoning engines. We believe these research directions should be highlighted in the future plans for AI 2.0.

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“…City public data resources are an important foundation for the construction of smart cities and an indispensable information infrastructure [1]. However, due to the limitations of many factors such as management mode and technical means, it has been very difficult for data resources to be shared among different departments and regions.…”

Section: Introductionmentioning

confidence: 99%

Innovation Research in City Public Management Based on a Data Resource Sharing Exchange Platform

Hui

McLernon

Zaidi

2018

Proceedings of the 8th International Conference on Information Communication and Management

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In order to solve the common needs of shared basic data resources in different industries, different departments and different regions in a city, this paper has designed a Data Resource Sharing and Exchange Platform (DRSEP) to solve the demand for comprehensive data of City Public Management (CPM). Firstly, we analyze the basic functional requirements of the platform. Secondly, we study the characteristics of the DRSEP from three aspects: data type, data volume and data transmission/application methods. Thirdly, we provide the overall technical architecture of the DRSEP, which includes: the data resource layer, the resource site layer, the resource integration layer, the resource service layer and the resource application layer. In particular, we devise a Data Organization System (DOS) based on a Data Resource Directory (DRD), a Public Basic Database (PBcDB) and a Public Business Database (PBuDB). The DRD is the metadata standard and resource directory of the platform. Through this directory, the authority, accuracy and unity of the data resources can be ensured. The PBcDB consists of four types of databases: a population database, a corporation database, a macroeconomic database and a geospatial database. The PBuDB includes a video database, an environmental safety supervision database, a building database, a government affairs and emergency database, a credit database and a comprehensive human resources database. Finally, the DRSEP is deployed, tested, applied and evaluated in a city with a population of 2.19 million in western China. Moreover, the test evaluation results show that the platform exhibits an outstanding performance in the integration technology of multi-source heterogeneous data and the reliable transmission technology of massive data.

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Data as Infrastructure for Smart Cities

Cited by 7 publications

References 0 publications

Squeaky wheels: Missing data, disability, and power in the smart city

Squeaky wheels: Missing data, disability, and power in the smart city

Towards human-like and transhuman perception in AI 2.0: a review

Innovation Research in City Public Management Based on a Data Resource Sharing Exchange Platform

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