Smart Mobility Implementation in Smart Cities: A Comprehensive Review on State-of-art Technologies

Savithramma, R M; Ashwini, B; Sumathi, R.

doi:10.1109/icssit53264.2022.9716288

Cited by 32 publications

(7 citation statements)

References 72 publications

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“…As the above research indicates, selecting IoT technology is critical for creating smart mobility systems [40,41]. However, the security provided by IoT devices is not guaranteed.…”

Section: Cyber Threats or Attacksmentioning

confidence: 99%

An Overview of Cyber Threats, Attacks and Countermeasures on the Primary Domains of Smart Cities

Demertzi

Demertzis

2023

Applied Sciences

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A smart city is where existing facilities and services are enhanced by digital technology to benefit people and companies. The most critical infrastructures in this city are interconnected. Increased data exchange across municipal domains aims to manage the essential assets, leading to more automation in city governance and optimization of the dynamic offered services. However, no clear guideline or standard exists for modeling these data flows. As a result, operators, municipalities, policymakers, manufacturers, solution providers, and vendors are forced to accept systems with limited scalability and varying needs. Nonetheless, it is critical to raise awareness about smart-city cybersecurity and implement suitable measures to safeguard citizens’ privacy and security because cyber threats seem to be well-organized, diverse, and sophisticated. This study aims to present an overview of cyber threats, attacks, and countermeasures on the primary domains of smart cities (smart government, smart mobility, smart environment, smart living, smart healthcare, smart economy, and smart people). It aims to present information extracted from the state of the art so policymakers can perceive the critical situation and simultaneously be a valuable resource for the scientific community. It also seeks to offer a structural reference model that may guide the architectural design and implementation of infrastructure upgrades linked to smart city networks.

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“…As the above research indicates, selecting IoT technology is critical for creating smart mobility systems [40,41]. However, the security provided by IoT devices is not guaranteed.…”

Section: Cyber Threats or Attacksmentioning

confidence: 99%

An Overview of Cyber Threats, Attacks and Countermeasures on the Primary Domains of Smart Cities

Demertzi

Demertzis

2023

Applied Sciences

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“…In this same review paper, machine learning solutions to handle several other ride-hailing services challenges are enlisted such as individual mobility patterns, On-line ride-hailing services-order matching, and vehicle dispatching [136]. Smart mobility applications consist of wide research scope, therefore, several existing discussions on future research directions for smart mobility are discussed by Savithramma et al [137]. In this research paper reviews of several smart mobility applications such as smart streets, smart parking, pedestrian management system, traffic management systems, navigation system, etc.…”

Section: Research Directionsmentioning

confidence: 99%

Next Generation of Multi-Agent Driven Smart City Applications and Research Paradigms

Arora,

Jain,

Yadav

et al. 2023

IEEE Open J. Commun. Soc.

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Smart City has seen a growing interest among government, researchers, and industrialists. Smart cities use digital technologies to enhance the quality of life for residents while promoting sustainability and efficient resource management. By integrating various technologies such as ICT, AI, and IoT, smart cities can improve the delivery of public services, optimize transportation systems, reduce energy consumption, and enhance public safety, among other benefits. The goal of smart cities is to create a more livable, efficient, and sustainable urban environment for residents, businesses, and visitors. The smart city focuses on automating different disciplines, including smart environment, smart home, smart economy, smart mobility, and, smart governance. Due to that Multi-Agent driven Smart city has received tremendous attention from the research community to get an intelligent solution to complex problems from different disciplines by subdividing responsibilities into multiple agents and empowering agents through AI. In this regard, it is vital to explore the usage of Multi-Agent in different critical application areas of smart cities to achieve an end-to-end intelligent urban area. In this paper, a detailed description of the Multi-Agent process for Smart city application areas is provided along with resources and future research directions. Four different application areas-Smart Home, Smart Governance, Smart Environment, and Smart Mobility are discussed in detail.

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“…From the above discussion, it is clear that characterizing travel time and speed is one of the essential tasks for any travel-related analysis. An insightful analysis of travel time can lead to various applications such as public transit information systems [27] to provide a cohesive schedule and dynamic information of the arrival of the buses at bus stops.…”

Section: Introductionmentioning

confidence: 99%

Public Transit Bus Travel Time Variability Analysis Using Limited Datasets: A Case Study

Ashwini Bukanakere Prakash,

Sumathi,

Satyanarayana Sudhira

2024

Curr. Appl. Sci. Technol.

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Public transit service is a sustainable and eco-friendly alternative for commuting, and promoting its usage is the need of the day. An understanding of the variability of travel time can aid service operators to improve the reliability and ridership of public transport. Gaining insights into the variability of travel time is a data-intensive task, and most of the existing studies utilize multiple traffic-related datasets. However, most cities lack the infrastructure to collect multiple data sets, hence in the current study, the location data of public transit buses were used for the analysis. The study was conducted in Tumakuru city, India at two spatial levels, namely route and segment, and further at temporal levels such as the day-of-the-week and departure time window. Wilcoxon signed-rank test was applied to identify similar spatial-temporal aggregations, and a few aggregations demonstrated similarity. Consistent with the existing literature, six statistical distributions were selected to fit the data through the Kolmogorov-Smirnov test. The results emphasized that the Logistic distribution is the best fit at all spatial-temporal aggregation levels, and the lognormal and GEV distributions offered better fit for a few aggregation levels. Logistic distribution is recommended for operations planners and researchers to conduct reliability analysis and travel time forecasting in the future.

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Smart Mobility Implementation in Smart Cities: A Comprehensive Review on State-of-art Technologies

Cited by 32 publications

References 72 publications

An Overview of Cyber Threats, Attacks and Countermeasures on the Primary Domains of Smart Cities

An Overview of Cyber Threats, Attacks and Countermeasures on the Primary Domains of Smart Cities

Next Generation of Multi-Agent Driven Smart City Applications and Research Paradigms

Public Transit Bus Travel Time Variability Analysis Using Limited Datasets: A Case Study

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