Rapid Precedent-Aware Pedestrian and Car Classification on Constrained IoT Platforms

Danner, Jay; Wills, Linda M.; Ruiz, Elbert M.; Lerner, Lee W.

doi:10.1145/2993452.2993562

Cited by 12 publications

(6 citation statements)

References 12 publications

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“…Various software and hardware Internet platforms are also being developed to assist the driver. For example, the work [94] integrates methods of combining data from former routes, sensors, image recognition and analysis to identify pedestrians and other transport systems on the road. The work [95] provides a cloud-based smart parking system that analyzes and interprets existing geographic location, car parking facilities, traffic flow and parking space reservation information.…”

Section: Iot Standards Applicability In Itsmentioning

confidence: 99%

Review of V2X–IoT Standards and Frameworks for ITS Applications

et al. 2020

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The intelligent transport system (ITS) has become one of the most globally researched topics with a lot of investment and development resources being dedicated into it due to its foreseen impact on the economic growth of the transport sector. Currently there are two main vehicle-to-everything (V2X) technologies, whose primary application is focused on ITS, backed up by the key players of various automotive, telecommunication and transport industries: dedicated short-range communications (DSRC) and cellular vehicle-to-everything (C-V2X), respectively based on IEEE 802.11p and 3GPP LTE/5G NR. While DSRC already has deployments, C-V2X is expected to see larger scale trails and deployments in 2020. In this work, the authors provide insight and review into two main V2X technologies, DSRC and C-V2X, their core parameters, shortcomings and limitations, and explore the need for integration of IoT-based technologies into modern ITS solutions. A comprehensive overview and analysis of currently commercially available V2X products, their sub-blocks and features is provided.

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Section: Iot Standards Applicability In Itsmentioning

confidence: 99%

Review of V2X–IoT Standards and Frameworks for ITS Applications

et al. 2020

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“…Another set of applications is for intelligent vehicles to assist the driver. Danner et al [47] introduce their Precedent-Aware Classification (PAC) technique which combines information from previously traveled routes and minimal classification features from sensors to computer vision analytics for pedestrian and car detection on constrained IoT platforms. Jara et al [99] derive insights about human dynamics by analysing the correlation between traffic, temperature and time using IoT sensor data from the SmartSantander smart city testbed [176].…”

Section: Transport: Traffic Control and Routing Pedestrian Detectionmentioning

confidence: 99%

Analytics for the Internet of Things

2018

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The Internet of Things (IoT) envisions a world-wide, interconnected network of smart physical entities. These physical entities generate a large amount of data in operation and as the IoT gains momentum in terms of deployment, the combined scale of those data seems destined to continue to grow. Increasingly, applications for the IoT involve analytics. Data analytics is the process of deriving knowledge from data, generating value like actionable insights from them. This article reviews work in the IoT and big data analytics from the perspective of their utility in creating efficient, effective and innovative applications and services for a wide spectrum of domains. We review the broad vision for the IoT as it is shaped in various communities, examine the application of data analytics across IoT domains, provide a categorisation of analytic approaches and propose a layered taxonomy from IoT data to analytics. This taxonomy provides us with insights on the appropriateness of analytical techniques, which in turn shapes a survey of enabling technology and infrastructure for IoT analytics. Finally, we look at some tradeoffs for analytics in the IoT that can shape future research.

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“…Permasalahan transportasi dapat diminimalisir dengen penerapan IoT diantaranya untuk pengelolaan parker dan deteksi kendaraan jumlah kendaraan. [26]. Pengaturan untuk lampu lalu lintas di perkotaan dapat menerapkan IoT [17], adanya sistem ini dapat mengurangi tingkat kemacetan.…”

Section: Nounclassified

“…Kedua hal ini berperan signifikan pada pengambilan keputusan. Permasalahan waktu merupakan komponen penting dalam decision making [26]. Yang kedua adalah Data-driven faktor yang terdiri dari jumlah data yang besar (scalable) dan keheterogen data dan objek obsevasi.…”

Section: Gambar 4 Framework Decision Making In Iotunclassified

Decision Making in Internet of Things (IoT) : A Systematic Literature Review

Yomeldi

2020

ITEJ

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Today’s internet technologies support everything that human do. By using integrated technologies the things that connected to internet can provide data. The Internet of Things (IoT) is the new paradigm in provide the data without human communicated. The IoT system support machine to machine communication that can be used to develop smart services that can generate a lot of data. This exponential data can support a decision making. The decision making system depend on availability and reliability of data. This study focus to how the Internet of Thing support decision making system. With a survey of literature to understand the trends, models and factors of decision making in IoT based on previous research. This survey following step by conduct the research question (RQ), then search and observation the previous research from database journal. Based on reviewing 26 articles, this study conclude that the trends of decision making in IoT are implemented on Manufacturing and Industry, Healthcare, Agriculture and Transportation. Besides that the decision model that can support by IoT used Fog Computing, Fuzzy, Game Theoritic, Clustering Based on Multimodal Data Correlation, etc. Meanwhile the decision making factors that influenced by IoT like Latency, data-driven, security, data reliability and accurate. The integrated of model and point of interest on decision making in IoT should be improved. It will be the opportunities and challenge in IoT to support decision making in future.

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Rapid Precedent-Aware Pedestrian and Car Classification on Constrained IoT Platforms

Cited by 12 publications

References 12 publications

Review of V2X–IoT Standards and Frameworks for ITS Applications

Review of V2X–IoT Standards and Frameworks for ITS Applications

Analytics for the Internet of Things

Decision Making in Internet of Things (IoT) : A Systematic Literature Review

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