Urban planning and building smart cities based on the Internet of Things using Big Data analytics

Rathore, M. Mazhar; Ahmad, Awais; Paul, Anand; Rho, Seungmin

doi:10.1016/j.comnet.2015.12.023

Cited by 775 publications

(373 citation statements)

References 14 publications

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“…'Issues of openness of data (L&E3)' comes next to the list. Rathore et al (2016) identified the issues of openness of data are crucial in the smart city agenda. Enabling openness of real time data will help the government authorities as well as citizens.…”

Section: Gov) -Economic (Eco) -Technology (Tech) -Social (Soc) -Envirmentioning

confidence: 99%

Barriers to the Development of Smart Cities in Indian Context

Luthra²,

et al. 2018

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Smart city development is gaining considerable recognition in the systematic literature and international policies throughout the world. The study aims to identify the key barriers of smart cities from a review of existing literature and views of experts in this area. This work further makes an attempt on the prioritisation of barriers to recognise the most important barrier category and ranking of specific barriers within the categories to the development of smart cities in India. Through the existing literature, this work explored 31 barriers of smart cities development and divided them into six categories. This research work employed fuzzy Analytic Hierarchy Process (AHP) technique to prioritise the selected barriers. Findings reveal that 'Governance' is documented as the most significant category of barriers for smart city development followed by 'Economic; 'Technology'; 'Social'; 'Environmental' and 'Legal and Ethical'. In this work, authors also performed sensitivity analysis to validate the findings of study. This research is useful to the government and policymakers for eradicating the potential interferences in smart city development initiatives in developing countries like India.

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Section: Gov) -Economic (Eco) -Technology (Tech) -Social (Soc) -Envirmentioning

confidence: 99%

Barriers to the Development of Smart Cities in Indian Context

Luthra²,

et al. 2018

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“…Big data analytics is used for both ood information management [238] and long-lead extreme ood forecasting [239]. Rathore et al [240] discussed urban planning and building smart cities using the Internet of Things technology and big data analytics. They analyzed datasets of oods to obtain the thresholds for predicting oods and alerting the public.…”

Section: Big Data and Natural Disastersmentioning

confidence: 99%

Current Efforts for Prediction and Assessment of Natural Disasters: Earthquakes, Tsunamis, Volcanic eruptions, Hurricanes, Tornados, and Floods

2017

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Abstract. This article presents a state-of-the-art review of di erent methods, signal and image processing techniques, and statistical analyses used for prediction and assessment of natural disasters including earthquakes, tsunamis, volcanic eruptions, hurricanes, tornadoes, and oods. Application of the big data paradigm to the aforementioned natural disasters is also discussed. The research for increasingly more sophisticated computational models will continue to achieve more accurate predictions of various natural disasters.

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“…For this reason, cloud computing adopt some data aggregation approaches and techniques to produce high level and sophisticated final outcome. In [25], the authors provide a full data model from sensors nodes to cloud computing environments for a smart city scenario. This model has two main layers which are sensors nodes and cloud computing layers.…”

Section: A Data Aggregationmentioning

confidence: 99%

“…With respect to data aggregation, most related work concentrate to perform data aggregation in cloud environments [19,25]. This option applies most sophisticated data optimization (such as data aggregation, data filtering and so on) at the cloud level.…”

Section: Fog Layermentioning

confidence: 99%

A Novel Architecture for Efficient Fog to Cloud Data Management in Smart Cities

Sinaeepourfard

García

Masip-Bruin

et al. 2017

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)

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Abstract-Smart cities are the current technological solutions to handle the challenges and complexity of the growing urban density. Traditionally, smart city resources are managed with a cloud based solution, where sensors and devices are connected to provide a centralized and rich set of open data. The advantages of cloud based frameworks are their ubiquity, as well as an (almost) unlimited resources capacity. However, accessing data from the cloud implies large network traffic, high latencies usually not appropriate for realtime or critical solutions, as well as higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. It proposes the use of devices at the edge to provide closer computing facilities and, therefore, reducing network traffic, reducing latencies drastically while improving security. In this work, we present a new framework for data management in the context of a smart city through a global fog to cloud resources management architecture. We show this model has the advantages of both, fog and cloud technologies, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. As a first experiment, we estimate the network traffic in this model during data collection and compare it with a traditional real system.

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Urban planning and building smart cities based on the Internet of Things using Big Data analytics

Cited by 775 publications

References 14 publications

Barriers to the Development of Smart Cities in Indian Context

Barriers to the Development of Smart Cities in Indian Context

Current Efforts for Prediction and Assessment of Natural Disasters: Earthquakes, Tsunamis, Volcanic eruptions, Hurricanes, Tornados, and Floods

A Novel Architecture for Efficient Fog to Cloud Data Management in Smart Cities

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