Towards a Multi-cluster Analytical Engine for Transportation Data

Shtern, Mark; Mian, Rizwan; Litoiu, Marin; Zareian, Saeed; Abdelgawad, Hossam; Tizghadam, Ali

doi:10.1109/iccac.2014.37

Cited by 15 publications

(4 citation statements)

References 16 publications

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“…Similarly, VSPs have been reported in one-off construction projects [41], transportation [42], and others. This paper focuses on HSPs, particularly Berkeley Data Analytics Stack (BDAS) and Hadoop.…”

Section: Big Data Engineering (Bde)mentioning

confidence: 54%

“…In construction, HSPs have been used for waste management [25], profitability performance [39], smart road construction, and others [40]. Similarly, VSPs have been reported in one-off construction projects [41], transportation [42], and others. This paper focuses on HSPs, particularly Berkeley Data Analytics Stack (BDAS) and Hadoop.…”

Section: Big Data Engineering (Bde)mentioning

confidence: 99%

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Big Data in Construction: Current Applications and Future Opportunities

Munawar

Ullah

Qayyum

et al. 2022

BDCC

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Big data have become an integral part of various research fields due to the rapid advancements in the digital technologies available for dealing with data. The construction industry is no exception and has seen a spike in the data being generated due to the introduction of various digital disruptive technologies. However, despite the availability of data and the introduction of such technologies, the construction industry is lagging in harnessing big data. This paper critically explores literature published since 2010 to identify the data trends and how the construction industry can benefit from big data. The presence of tools such as computer-aided drawing (CAD) and building information modelling (BIM) provide a great opportunity for researchers in the construction industry to further improve how infrastructure can be developed, monitored, or improved in the future. The gaps in the existing research data have been explored and a detailed analysis was carried out to identify the different ways in which big data analysis and storage work in relevance to the construction industry. Big data engineering (BDE) and statistics are among the most crucial steps for integrating big data technology in construction. The results of this study suggest that while the existing research studies have set the stage for improving big data research, the integration of the associated digital technologies into the construction industry is not very clear. Among the future opportunities, big data research into construction safety, site management, heritage conservation, and project waste minimization and quality improvements are key areas.

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Section: Big Data Engineering (Bde)mentioning

confidence: 54%

Section: Big Data Engineering (Bde)mentioning

confidence: 99%

Big Data in Construction: Current Applications and Future Opportunities

Munawar

Ullah

Qayyum

et al. 2022

BDCC

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show abstract

“…The sensors in the handheld devices, on the roads and on vehicles helps to detect real time traffic in-formation in the road. The data obtained from the sensors are helpful for the traffic authorities to enhance their work in all possible ways to change the routes in the current time or in near future [6].…”

Section: B Uses Of Big Data Analyticsmentioning

confidence: 99%

Classification of Metabric Clinical Dataset using Naive Bayes Classifier

Sweetlin*¹,

Ponraj²

2019

IJITEE

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 Abstract: The rapid growth of the internet and its applications makes data grow to huge volumes. The Relational Database Management Systems are inefficient to handle huge volumes of data and so nowadays, Big Data technology is being used by many organizations such as Facebook, Twitter etc. Big Data technology is very useful for organizations to take proper decisions to attain their goals and in mounting themselves organization to full fledge. The use of this technology is broadly widened across all fields of Science, Medicine, Technology, and Business, so it is mandatory to acquire knowledge about Big Data concepts. Thus, acquiring knowledge on the technological revolution from traditional Database Management System to Big Data is significant. In this paper, we have discussed about big data and its evolution, characteristics, data sources, formats, Stages of Big Data process. A huge volume of clinical dataset has been considered and it is analyzed using Naive Bayes Classifier.

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“…However, BusViz results rely on the assumption that every passenger correctly taps their EZ-Link card when boarding and alighting. Other transportation data analytics platforms designed or developed in recent years include the traffic big data platform by Mian et al (2014), the Sipresk (Khazaei et al 2015), and the conceptual platform Godzilla (Shtern et Understanding Transit System Performance Using AVL-APC Data: An Analytics Platform with Case Studies for the Pittsburgh Region al. 2014), which were designed for general traffic data or highway traffic data.…”

Section: Introductionmentioning

confidence: 99%