Big Data GIS Analytics Towards Efficient Waste Management in Stockholm

Shahrokni, Hossein; Heijde, Bram van der; Lazarevic, David; Brandt, Nils

doi:10.2991/ict4s-14.2014.17

Cited by 28 publications

(18 citation statements)

References 17 publications

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“…Such a large amount of data was used to collect and analyze waste management collection data to identify the inefficiencies in waste collection routes within the city. A shared waste management vehicle fleet was recommended as a particularly good policy intervention (Shahrokni et al, 2014).…”

Section: City Of Stockholmmentioning

confidence: 99%

The role of big data in smart city

Hashem

Chang

Anuar

et al. 2016

International Journal of Information Management

871

395

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The expansion of big data and the evolution of Internet of Things (IoT) technologies have played an important role in the feasibility of smart city initiatives. Big data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radiofrequency identification, and Bluetooth in the real-world environment using highly networked services. The combination of the IoT and big data is an unexplored research area that has brought new and interesting challenges for achieving the goal of future smart cities. These new challenges focus primarily on problems related to business and technology that enable cities to actualize the vision, principles, and requirements of the applications of smart cities by realizing the main smart environment characteristics. In this paper, we describe the existing communication technologies and smart-based applications used within the context of smart cities. The visions of big data analytics to support smart cities are discussed by focusing on how big data can fundamentally change urban populations at different levels. Moreover, a future business model that can manage big data for smart cities is proposed, and the business and technological research challenges are identified. This study can serve as a benchmark for researchers and industries for the future progress and development of smart cities in the context of big data.

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Section: City Of Stockholmmentioning

confidence: 99%

The role of big data in smart city

Hashem

Chang

Anuar

et al. 2016

International Journal of Information Management

871

395

View full text Add to dashboard Cite

show abstract

“…Beyond the obvious limitations of climate action planning, following up previous climate action plans may partially be left to guess working given that it is very difficult to answer questions, such as “Why did we not reach our climate goal on energy use in buildings?”, with a snapshot of summary data from a decade ago and another snapshot from the previous year. In order to provide answers based on which effective actions and policies can be developed, the high spatial and temporal resolution of the SUM framework is necessary, which has been confirmed by two sector‐specific studies on energy and waste (Shahrokni et al , ).…”

mentioning

confidence: 99%

Implementing Smart Urban Metabolism in the Stockholm Royal Seaport: Smart City SRS

Shahrokni¹,

Årman

Lazarevic

et al. 2015

J of Industrial Ecology

Self Cite

109

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Summary For half a century, system scientists have relied on urban metabolism (UM) as a pragmatic framework to support the needed transition toward sustainable urban development. It has been suggested that information and communication technology (ICT) and, more specifically, smart cities can be leveraged in this transition. Given the recent advances in smart cities, smart urban metabolism (SUM) is considered a technology‐enabled evolution of the UM framework, overcoming some of its current limitations. Most significantly, the SUM framework works at high temporal (up to real‐time) and spatial (down to household/individual) resolutions. This article presents the first implementation of SUM in the Smart City Stockholm Royal Seaport R&D project; it further analyzes barriers and discusses the potential long‐term implications of the findings. Four key performance indicators (KPIs) are generated in real time based on the integration of heterogeneous, real‐time data sources. These are kilowatt‐hours per square meter, carbon dioxide equivalents per capita, kilowatt‐hours of primary energy per capita, and share of renewables percentage. These KPIs are fed back on three levels (household, building, and district) on four interfaces, developed for different audiences. The most challenging barrier identified was accessing and integrating siloed data from the different data owners (utilities, building owners, and so forth). It is hard to overcome unless a significant value is perceived. A number of long‐term opportunities were described in the SUM context; among those, it is envisioned that SUM could enable a new understanding of the causalities that govern urbanism and allow citizens and city officials to receive feedback on the system consequences of their choices.

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“…We see ICT as a key enabler to help overcome the legislative barriers and urban design choices [15], through the use of big data and spatial analytics to realise smart logistics (e.g. [49]) that can help decision makers understand a more holistic view of the impacts of freight on urban environments.…”

Section: Decision Support and Policy Changementioning

confidence: 99%

“…Data-driven analytics (e.g. Spatial Analytics [49,34]) can be used to develop data driven models, decision support tools [11,50], counter factual futures and scenarios that are useful tools in presenting information to policy makers (cf. [4,51]).…”

Section: Related Workmentioning

confidence: 99%

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ICT for Sustainable Last-Mile Logistics: Data, People and Parcels

Bates¹,

Friday²,

Allen³

et al.

EPiC Series in Computing

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In this paper we present a vision of how ICT can be leveraged to help combat the impact on pollution, congestion and carbon emissions contributed by the parcel delivery sector. This is timely given annual growth in parcel deliveries, especially same-day deliveries, and the need to inform initiatives to clean up our cities such as the sales ban on new petrol and diesel vehicles in the UK by 2040. Our insights are informed by research on parcel logistics in Central London, leveraging a data set of parcel manifests spanning 6 months. To understand the impact of growing e-commerce trends on parcel deliveries we provide a mixed methods case study leveraging data-driven analysis and qualitative fieldwork to demonstrate how ICT can uncover the impact of parcel deliveries on delivery drivers and their delivery rounds during seasonal deliveries (or "the silly season"). We finish by discussing key opportunities for intervention and further research in ICT4S and co-created Smart Cities, connecting our findings with existing research and data as a call to the ICT4S community to help tackle the growth in carbon emissions, pollution and congestion linked to parcel deliveries.

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Big Data GIS Analytics Towards Efficient Waste Management in Stockholm

Cited by 28 publications

References 17 publications

The role of big data in smart city

The role of big data in smart city

Implementing Smart Urban Metabolism in the Stockholm Royal Seaport: Smart City SRS

ICT for Sustainable Last-Mile Logistics: Data, People and Parcels

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