Evidence map›Paper›PMID 32781671›Full record

ArticleSensors (Basel, Switzerland)2020

Understanding Sensor Cities: Insights from Technology Giant Company Driven Smart Urbanism Practices.

Gaspare D'Amico, Pasqua L'Abbate, Wenjie Liao, Tan Yigitcanlar, Giuseppe Ioppolo

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gaspare D'AmicoDepartment of Economics, University of Messina, Via dei Verdi, 75, 98122 Messina, Italy.ORCID 0000-0002-9114-8961
Pasqua L'AbbateDepartment of Civil, Environmental, Building Engineering and Chemistry, Polytechnic of Bari, 70125 Bari, BA, Italy.
Wenjie LiaoInstitute of New Energy and Low-Carbon Technology, Sichuan University, Chengdu 610065, China.ORCID 0000-0002-5333-2717
Tan YigitcanlarSchool of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia.ORCID 0000-0001-7262-7118
Giuseppe IoppoloDepartment of Economics, University of Messina, Via dei Verdi, 75, 98122 Messina, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The data-driven approach to sustainable urban development is becoming increasingly popular among the cities across the world. This is due to cities' attention in supporting smart and sustainable urbanism practices. In an era of digitalization of urban services and processes, which is upon us, platform urbanism is becoming a fundamental tool to support smart urban governance, and helping in the formation of a new version of cities-i.e., City 4.0. This new version utilizes urban dashboards and platforms in its operations and management tasks of its complex urban metabolism. These intelligent systems help in maintaining the robustness of our cities, integrating various sensors (e.g., internet-of-things) and big data analysis technologies (e.g., artificial intelligence) with the aim of optimizing urban infrastructures and services (e.g., water, waste, energy), and turning the urban system into a smart one. The study generates insights from the sensor city best practices by placing some of renowned projects, implemented by Huawei, Cisco, Google, Ericsson, Microsoft, and Alibaba, under the microscope. The investigation findings reveal that the sensor city approach: (a) Has the potential to increase the smartness and sustainability level of cities; (b) Manages to engage citizens and companies in the process of planning, monitoring and analyzing urban processes; (c) Raises awareness on the local environmental, social and economic issues, and; (d) Provides a novel city blueprint for urban administrators, managers and planners. Nonetheless, the use of advanced technologies-e.g., real-time monitoring stations, cloud computing, surveillance cameras-poses a multitude of challenges related to: (a) Quality of the data used; (b) Level of protection of traditional and cybernetic urban security; (c) Necessary integration between the various urban infrastructure, and; (d) Ability to transform feedback from stakeholders into innovative urban policies.

Indexed as

City 4.0disruptive urban transitionInternet-of-Things (IoT)sensor citysensorssmart citysmart governancesmart urbanismsustainable urban developmenttechnology giants

Identifiers

PMID32781671
PMCPMC7472013

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.