Survey of various data collection ways for smart transportation domain of smart city

Shukla, Sumit N; Champaneria, Tushar

doi:10.1109/i-smac.2017.8058265

Cited by 25 publications

(7 citation statements)

References 4 publications

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“…An autonomous drone delivery within the radius of 10 kms is beneficial to save a lot of valuable time for carrying parcels. The manual delivery on the other hand takes a lot of time [15].…”

Section: A the Vision Van Of Mercedes-benzmentioning

confidence: 99%

Internet of Things (Iot) Technologies for Shimla City-a Case Study

Kalia

Rana

Sood

et al. 2022

IJARCS

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The large deployment of Internet of Things (IoT) is actually enabling Smart City projects and initiatives all over the world. Objects used in daily life are being equipped with electronic devices and protocol suites in order to make them interconnected and connected to the Internet. According to a recent Gartner study, 50 billion connected objects have been deployed in smart cities by 2020. These connected objects will make our cities smart. However, they will also open up risks and privacy issues. As various smart city initiatives and projects have been launched in recent years, we have witnessed not only the expected benefits but the risks introduced. The current and future trends of smart city with respect to IoT have been described. It also discussed the interaction between smart cities and IoT. The drivers behind the evolution & development of IoT and smart cities have been explained. Finally, the IoT weaknesses and how they can be addressed when used for smart cities has been discussed

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“…An autonomous drone delivery within the radius of 10 kms is beneficial to save a lot of valuable time for carrying parcels. The manual delivery on the other hand takes a lot of time [15].…”

Section: A the Vision Van Of Mercedes-benzmentioning

confidence: 99%

Internet of Things (Iot) Technologies for Shimla City-a Case Study

Kalia

Rana

Sood

et al. 2022

IJARCS

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“…As data is of key importance to perform analytic, Shukla and Champaneria () present different ways to collect data in order to provide better transportation management. For counting the number of devices entering or exiting the road, different technologies are presented including pneumatic tubes, inductive loops and vehicle's detection via video.…”

Section: Big Data Analytics In Smart Citiesmentioning

confidence: 99%

Smart city big data analytics: An advanced review

Soomro

Bhutta

Khan

et al. 2019

WIREs Data Min & Knowl

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With the increasing role of ICT in enabling and supporting smart cities, the demand for big data analytics solutions is increasing. Various artificial intelligence, data mining, machine learning and statistical analysis-based solutions have been successfully applied in thematic domains like climate science, energy management, transport, air quality management and weather pattern analysis. In this paper, we present a systematic review of the literature on smart city big data analytics. We have searched a number of different repositories using specific keywords and followed a structured data mining methodology for selecting material for the review. We have also performed a technological and thematic analysis of the shortlisted literature, identified various data mining/machine learning techniques and presented the results. Based on this analysis we also present a classification model that studies four aspects of research in this domain. These include data models, computing models, security and privacy aspects and major market drivers in the smart cities domain. Moreover, we present a gap analysis and identify future directions for research. For the thematic analysis we identified the themes smart city governance, economy, environment, transport and energy. We present the major challenges in these themes, the major research work done in the field of data analytics to address these challenges and future research directions.

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“…The Inter Packet Interval (IPI) between the generation of application packets has been varied from 1 s (high traffic) up to 60 s (low traffic) which are typical values in smart cities applications [10]. The bar plot shows the median values for each scenario over the 50 repetitions and the confidence intervals of 95%.…”

Section: Lifetimementioning

confidence: 99%

LoBaPS: Load Balancing Parent Selection for RPL Using Wake-Up Radios

Sampayo

Montavont

Noël

2019

2019 IEEE Symposium on Computers and Communications (ISCC)

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In an effort to extend the lifetime and reliability of multihop wireless sensor networks we recently presented LoBaPS, a protocol to select opportunistic parents and achieve load balancing. This algorithm takes advantage of the wake-up radio for its ultra-low power consumption and always-on feature. Moreover, it overcomes an open problem in the routing layer: achieving both stability and efficient parent selection at the same time. However, the random load balancing strategy and the energy wastage in listening mode still limits the network lifetime. In this article, we present eLoBaPS, a significant modification of LoBaPS that distributes better the energy among the parents improving around 17% the lifetime of the network towards the ideal case. In a nutshell, the next hop is selected in a decentralized way and it is the parent that issues a shorter back-off period before attempting to retransmit. In addition, the nodes overhear all the traffic in the wake-up radio channel and adapt the protocol parameters to the current state of the battery of the neighbors. We perform simulations with a network of ContikiOS nodes running eLoBaPS, LoBaPS and W-MAC, a reference protocol that uses the wakeup radio.

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Survey of various data collection ways for smart transportation domain of smart city

Cited by 25 publications

References 4 publications

Internet of Things (Iot) Technologies for Shimla City-a Case Study

Internet of Things (Iot) Technologies for Shimla City-a Case Study

Smart city big data analytics: An advanced review

LoBaPS: Load Balancing Parent Selection for RPL Using Wake-Up Radios

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