Smart Mobile Research Articles

Artificial Intelligence in Smart Cities—Applications, Barriers, and Future Directions: A Review

As urbanization continues to pose new challenges for cities around the world, the concept of smart cities is a promising solution, with artificial intelligence (AI) playing a central role in this transformation. This paper presents a literature review of AI solutions applied in smart cities, focusing on its six main areas: smart mobility, smart environment, smart governance, smart living, smart economy, and smart people. The analysis covers publications from 2021 to 2024 available on Scopus. This paper examines the application of AI in each area and identifies barriers, advances, and future directions. The authors set the following goals of the analysis: (1) to identify solutions and applications using artificial intelligence in smart cities; (2) to identify the barriers to implementation of artificial intelligence in smart cities; and (3) to explore directions of the usage of artificial intelligence in smart cities.

Exploiting Container-Based Microservices forReliable Smart Mobility Applications

Smart mobility is emerging, addressing heterogeneous scenarios with high impact on technology infrastructures, solutions, and people. Safety and availability are mandatory, forcing the design of new reliable services for localization, health monitoring of the user, maintenance of vehicle, and protection of the environment. This paper proposes a container-based microservice approach to the edge computing in IoT smart mobility scenarios. Since smart mobility backends must manage a large heterogeneity of applications, the proposed approach is promising with respect to the classical solutions (based on "monolithic hardware+software" devices), from the point of view of flexibility, upgradability, security, scalability, and reliability. A demo use case, based on industry-grade hardware and Docker, has been realized and multiple implementations of the same services have been executed in parallel, showing strong independence between them. Moreover, average delays of less than 10 ms are obtained, confirming the usability in several smart mobility (and smart city) applications.

Success factors in smart mobility: a new framework and implications for the EuroMed context from case study of New York, Copenhagen, Singapore, Bari and Barcelona

Success factors in smart mobility: a new framework and implications for the EuroMed context from case study of New York, Copenhagen, Singapore, Bari and Barcelona

From RAG/RAT to SAGE for Social Transportation: A CoT and New Perspective on Smart Logistics and Mobility

From RAG/RAT to SAGE for Social Transportation: A CoT and New Perspective on Smart Logistics and Mobility

Responsiveness and Precision of Digital IMUs under Linear and Curvilinear Motion Conditions for Local Navigation and Positioning in Advanced Smart Mobility.

Sensors based on MEMS technology, in particular Inertial Measurement Units (IMUs), when installed on vehicles, provide a real-time full estimation of vehicles' state vector (e.g., position, velocity, yaw angle, angular rate, acceleration), which is required for the planning and control of cars' trajectories, as well as managing the in-car local navigation and positioning tasks. Moreover, data provided by the IMUs, integrated with the data of multiple inputs from other sensing systems (such as Lidar, cameras, and GPS) within the vehicle, and with the surrounding information exchanged in real time (vehicle to vehicle, vehicle to infrastructure, or vehicle to other entities), can be exploited to actualize the full implementation of "smart mobility" on a large scale. On the other hand, "smart mobility" (which is expected to improve road safety, reduce traffic congestion and environmental burden, and enhance the sustainability of mobility as a whole), to be safe and functional on a large scale, should be supported by highly accurate and trustworthy technologies based on precise and reliable sensors and systems. It is known that the accuracy and precision of data supplied by appropriately in-lab-calibrated IMUs (with respect to the primary or secondary standard in order to provide traceability to the International System of Units) allow guaranteeing high quality, reliable information managed by processing systems, since they are reproducible, repeatable, and traceable. In this work, the effective responsiveness and the related precision of digital IMUs, under sinusoidal linear and curvilinear motion conditions at 5 Hz, 10 Hz, and 20 Hz, are investigated on the basis of metrological approaches in laboratory standard conditions only. As a first step, in-lab calibrations allow one to reduce the variables of uncontrolled boundary conditions (e.g., occurring in vehicles in on-site tests) in order to identify the IMUs' sensitivity in a stable and reproducible environment. For this purpose, a new calibration system, based on an oscillating rotating table was developed to reproduce the dynamic conditions of use in the field, and the results are compared with calibration data obtained on linear calibration benches.

THE REALITY OF DIGITAL TRANSFORMATION ON ALGERIAN MACROECONOMIC VARIABLES: AN ANALYTICAL STUDY

Through this paper, we are clarifying the need to move towards applying digital transformation strategies. Algeria’s indicators and achievements in digitization and their impact on macroeconomic variables, inflation, crude internal output, and balance of payments are effective solutions for developing the economy and moving to a digital and knowledge economy. Digital transformation also depends on various technologies and fields of artificial intelligence in terms of Productivity, competitiveness, leadership, innovation, and other fields. Digital transformation also boosts economic growth and promotes the telecommunications and technology sectors. Thus, this study aims to focus on the digitization of sectors of the Algerian economy, and enhancing them with various artificial intelligence techniques, as the basis for directing economic policies and making strategic decisions that contribute to enhancing the competitiveness of various economic institutions, and improving levels of economic growth and various Algerian macroeconomic indicators. The study found several findings related to the need to develop the infrastructure of the media and communication sector. Enhancing Internet access and improving digital and financial services, promoting production and consumption, improving education and vocational training skills while minimizing the macroeconomic impact on the environment, Dissemination of e-work culture and use of its technologies in all education sectors, health, smart mobility, tourism, etc. And it’s only by relying on the human resource that is the effective link in developing digital transformation strategies through research and innovation.

Urban mobility in the future: text analysis of mobility plans

Sustainable Urban Mobility Plans (SUMPs) or similar documents from 17 European capitals (published between 2010 and 2021) and the European SUMP guidelines have been analysed to understand how cities shape mobility and their transport systems. Text analysis is applied to identify development tendencies in a time- and cost-effective manner, without relying on traditional deep semantic analysis techniques. In addition to traditional statistical indicators, we introduce Category Term Frequency (CTF) as a new measure in text analysis. CTF reveals the number and proportion of words belonging to the same content group, namely specific mobility-related categories. The results indicate that categories describing general aspects such as the future, general transport, environment, and society are more prominently represented compared to more forward-looking categories like automation, electromobility, and sharing. The aggregated CTF of categories describing these emerging aspects is highest in the mobility plans of Copenhagen, Helsinki, Luxembourg, and Vienna, which are considered forerunners in their implementation. In general, the analysis concludes that despite recent technological developments and new business models, the examined mobility plans barely mention terms that would imply radical changes by the 2030s. Strategic documents and, thus, urban mobility developments suggest only a slow transition towards the expected levels of sustainable and smart urban mobility. These findings may contribute to understanding and (re)considering urban and transport development strategies in Europe. Furthermore, this text analysis framework provides planners and other experts with a novel tool to identify the focal areas of mobility-related (or other) documents.

Social Aspects of Smart Urban Mobility

There is a growing interest in sustainable urban transport solutions in cities around the world. These changes, known as “smart urban mobility”, aim to reduce the negative effects of transport on the natural environment and enhance the standard of living for urban dwellers. It should be noted that in addition to this transformation’s technological aspects, modifying the city’s structure and architecture also has a social dimension. The transformation of urban mobility has a significant impact on social relations. Introducing new modes of transport, such as city bikes and electric scooters, creates new ways of moving around the city and can impact social interactions. This can increase social integration and a community’s sense of belonging. At the same time, it is necessary to consider the differences between social groups to ensure equal access to the benefits of these changes in addition to deeper social elements, such as changing the habits and expectations of residents and adapting solutions to the specific needs of each city. This paper aims to look at the social aspects of smart urban mobility, including the impact of these changes on the lives and relationships of city residents.

MoS2-based charge trapping layer enabled triboelectric nanogenerator with assistance of CNN-GRU model for intelligent perception

Self-powered sensing technology and smart perception technology have broad application prospects in flexible and wearable electronics. In this work, a flexible triboelectric nanogenerator (RMP-TENG) based on a room-temperature vulcanized silicone rubber (RTV)@(Molybdenum disulfide (MoS2)/Polyvinyl chloride (PVC)) functional layer is developed using a layer-by-layer self-assembly and material doping strategy. The RTV@(MoS2/PVC) functional layer is divided into a charge-generating layer (RTV/PVC) and a charge-trapping layer (RTV/MoS2). The synergistic effect of PVC and MoS2 has improved the surface roughness and charge transfer efficiency of RMP-TENG, doubling its output performance to 1055 V and 112 μA. In order to further improve the tactile sensing accuracy of RMP-TENG, a deep learning model based on Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) is developed. It predicts the type of contact material based on the features of tactile signals, achieving a prediction accuracy of 93.975%. Additionally, by combining mobile smart terminals, the CNN-GRU model, and RMP-TENG, a wireless access control system based on self-powered tactile sensing and intelligent material recognition is developed. Through the optimization of these experiments and algorithms, RMP-TENG has achieved real-time material recognition capabilities. This demonstrates the broad application prospects of RMP-TENG in wearable energy supply, intelligent sensing, human-computer interaction, and other areas.

Smart medical English pedagogy on a smart teaching platform

The widespread adoption of smart mobile devices has sparked significant innovations in China's smart education landscape in recent years. Smart teaching platforms play a pivotal role in shaping the dynamics of smart teaching. This study aimed to enhance medical English pedagogy by implementing smart teaching on the smart teaching platform (Xuexitong). The researchers divided their 178 nursing-majored students into two control classes and two experimental classes to evaluate the effectiveness of smart teaching. Traditional classroom instruction was adopted in the control classes while smart pedagogy was applied in the experimental classes. After a semester-long teaching experiment, two assessments were conducted: a comparison of exam scores and a course feedback survey. The findings revealed that students in the experimental classes significantly outperformed the control group in these two assessments. This highlights the substantial effectiveness of smart medical English pedagogy demonstrating its ability to enhance students' language proficiency and comprehension in medical contexts far beyond traditional teaching methods. The study concluded that smart teaching can significantly improve teaching outcomes and facilitate pedagogical innovations among new technological advancements. These insights offer valuable guidance for future research to enhance the integration of smart mobile technologies with smart language pedagogy.

Insights into Simulated Smart Mobility on Roundabouts: Achievements, Lessons Learned, and Steps Ahead

This paper explores the domain of intelligent transportation systems, specifically focusing on roundabouts as potential solutions in the context of smart mobility. Roundabouts offer a safer and more efficient driving environment compared to other intersections, thanks to their curvilinear trajectories promoting speed control and lower vehicular speeds for traffic calming. The synthesis review supported the authors in presenting current knowledge and emerging needs in roundabout design and evaluation. A focused examination of the models and methods used to assess safety and operational performance of roundabout systems was necessary. This is particularly relevant in light of new challenges posed by the automotive market and the influence of vehicle-to-vehicle communication on the conceptualization and design of this road infrastructure. Two case studies of roundabouts were analyzed in Aimsun to simulate the increasing market penetration rates of connected and autonomous vehicles (CAVs) and their traffic impacts. Through microscopic traffic simulation, the research evaluated safety and performance efficiency advancements in roundabouts. The paper concludes by outlining areas for further research and evolving perspectives on the role of roundabouts in the transition toward connected and autonomous vehicles and infrastructures.

Systematic Approach to Evaluate the State of Illinois’ Preparedness for Smart Mobility

Connected, automated, shared, and electric (CASE) technologies are shaping Mobility 4.0—a connected, digitized, multimodal, and autonomous system of systems that is challenging past and existing strategic transportation planning practices at state and local levels. A systematic approach is presented to aid transportation agencies in their planning needs to evaluate preparedness for smart mobility. Guided by a set of online surveys, interviews, and workshops conducted among different stakeholders, this paper identifies strengths and opportunities to leverage the state’s public, private, and academic sector resources to prepare agencies in realizing the potential opportunities of Mobility 4.0 technologies, while avoiding possible pitfalls in the process. Seven smart mobility pillars were identified and ranked through a balanced scorecard analysis in this study for Illinois—namely (in decreasing order of importance), alternative fuels, scaling intelligent transportation systems, connected and automated (CA) freight, farm automation, CA logistics, insurance, and urban mobility. Tactical focus areas were also identified for each pillar and prioritized with suggested leads and stakeholders to champion the CASE directives and opportunities. Near-term actions were also suggested that included establishing a central structure for Illinois’ CASE program, enriching the knowledge base and experience, preparing the transportation infrastructure, partnerships with external stakeholders, and expansion of laws, regulations, and policies that will help administer and grow CASE technology deployment and integration.

Assessing the EU Climate and Energy Policy Priorities for Transport and Mobility through the Analysis of User-Generated Social Media Content Based on Text-Mining Techniques

For over three decades, the European Union’s (EU) transport policy has aimed at fostering environmental sustainability and energy efficiency. Since 2015, European policymakers have focused more on three key sustainable development goals: decarbonizing the transport system, promoting low-emission mobility solutions, and transitioning to renewable and alternative fuels. To effectively communicate priorities and engage stakeholders, EU policymakers regularly use social media platforms like Twitter (now known as X). This active discourse involves policymakers, industrial stakeholders, the media, and the public, offering insights into the role of transport policy in addressing climate change and energy transition challenges. The current research endeavors to track and analyze the evolution of user-generated content related to climate change, energy transition, and smart mobility on Twitter from 2011 to 2021. This research uses text-mining and social network analysis techniques to quantitatively and qualitatively assess the dynamics of relevant EU policies and their effects. The study’s findings can be used to establish a robust monitoring and evaluation framework at the EU and national levels. This framework will assess the effectiveness of communicating strategic priorities for sustainable transport development. It also holds potential for application in other sectors, broadening its impact.

Context-aware multi-modal route selection service for urban computing scenarios

The rapid urban population growth introduces novel challenges to urban mobility scenarios, requiring innovative and connected solutions to relieve traffic congestion and enhance transportation efficiency, using unusual roads and public transportation modals. For instance, multi-modal routes allow more flexible modal combinations to offer smart multi-modal mobility. In this context, the route selection service must rely on different context information, such as criminality, accidents, air quality, and others, where Internet of Things technologies introduce active and ubiquitous sensing of many contexts along the urban scenario, providing data for statistical analysis to offer a safer and healthier urban reality. However, designing an efficient multi-modal route selection service that considers different context information to offer personalized routes is important. In this article, we describe a context-aware route selection service that considers adequate contextual information to provide routes according to the user’s preference. The multi-modal route selection service applies a multi-criteria method to give different degrees of importance to each criterion based on the user profile (i.e., Worker, Green, Safe, and Tourist). We present extensive evaluation results from applying our multi-modal route selection approach to a London dataset. The approach successfully enables user-preferred transportation choices using four balanced selection profiles and ten route features. The proposed multi-modal route selection service demonstrates better performance in terms of economic, ecological, and time-saving metrics for each user profile compared to a greedy selection manner.

From RAG/RAT to SAGE: Parallel Driving for Smart Mobility

From RAG/RAT to SAGE: Parallel Driving for Smart Mobility

AoI-Guaranteed Incentive Mechanism for Mobile Crowdsensing With Freshness Concerns

With the explosive spread of smart mobile devices, Mobile CrowdSensing (MCS) has been becoming a promising paradigm, by which a platform can coordinate a group of workers to complete large-scale data collection tasks using their mobile devices. In this paper, we investigate the incentive mechanism design in MCS systems, taking the freshness of collected data and social benefits into consideration. First, the Age of Information (AoI) metric is introduced to measure the freshness of data. Then, we model the incentive mechanism design with AoI guarantees as an incomplete information two-stage Stackelberg game with multiple constraints. Next, we consider the scenario that all participants share the public utility function parameters of the Stackelberg game. By deriving the optimal remuneration paid by the platform and the optimal data update frequency for each worker, and proving the existence of a unique Stackelberg equilibrium, we propose an AoI-guaranteed Incentive Mechanism (AIM) that enables the platform and all workers to maximize their utilities simultaneously. Furthermore, we extend AIM to a general scenario where each participant has no prior knowledge of the utility function parameters of the game. By resorting to the Deep Reinforcement Learning (DRL) technique and modeling the two-stage Stackelberg game as a Markov decision process, we propose a DRL-based Incentive Mechanism (DIM) with AoI guarantees, which makes each participant effectively seek its optimal strategy through trial and error. Meanwhile, the system can guarantee that the AoI values of all data uploaded to the platform are not larger than a given threshold. Finally, numerical experiments on real-world traces are conducted to validate the efficacy and efficiency of AIM and DIM.

Classification of Smart and Sustainable Urban Mobility

The main purpose of this article is to identify and classify smart and sustainable urban mobility solutions in the context of three narratives for sustainable mobility: electromobility, collective transport 2.0 and low-mobility societies. The research process of this study included the following methods: review of the literature, namely, strategic European documents, sustainable urban mobility plans in chosen cities and scientific publications addressing smart and sustainable mobility, case studies of selected cities in Europe and technology mapping to visualize the study results. The main result of this study is the review of various smart and sustainable urban solutions (SSUM) and their classification within the three narratives of electromobility, collective transport 2.0 and low-mobility societies. This article expands the concept of the three narratives for sustainable mobility with the aspect of smart mobility enriched with the variety of example solutions, case studies and good practices within mobility strategies in European cities. The study results can be useful for different stakeholders engaged in developing and introducing the sustainable mobility strategies in cities. Based on the catalogue of SSUM solutions, presented case studies and good practices, they may gain the necessary knowledge, consider the possible initiatives towards green transformation in cities and finally adjust them to the citizens’ need.

Carbon, Particulate Matter, and Heavy Metal Human Toxicity Footprint of IoT-based Micro Electric Vehicle (EV) Sharing for Urban Mobility

Purpose : The purpose of this study is to calculate and compare carbon footprint, particulate matter footprint, and heavy metal human toxicity footprint with operation data of IoT-based Micro Electric Vehicle (EV) Sharing for Urban Mobility, which was conducted in Chungbuk Innovation City (Jinchen Ducksaneup, Eumsung Mangdongmyun), Ochangeup (Cheongju), Osongeup(Cheongju) as a MOLIT Smart City Challenge Project, with petrol and diesel vehicles.Methods : In the assessment area, ten new Micro Electric Vehicles were used within the ‘TAYOU’ platform, which is an IoT-based micro electric vehicle sharing platform for smart mobility. These vehicles were operated for two months (1,021 times and 1,996 km). Data including vehicle numbers, charging start and end times, operating durations, return times, distances traveled (km), user information (name, driver's license, telephone number), and more were collected. Using this data, the carbon, particulate matter, and heavy metal human toxicity footprint were calculated and compared with those of petrol and diesel vehicles.Results and Discussion : The carbon footprints were 188.74 kg CO<sub>2</sub> eqv., 409.67 kg CO<sub>2</sub> eqv., 389.55 kg CO<sub>2</sub> eqv., in IoT-based Micro Electric Vehicle (EV), and petrol and diesel vehicle, respectively. The particulate matter footprint was 263.36 gPM<sub>2.5</sub> eqv., 21.37 gPM<sub>2.5</sub> eqv., and 439.47 gPM<sub>2.5</sub> eqv., respectively. The heavy metal human toxicity footprint was calculated at 0.029 g1.4 DCB eqv., 8.26 g1.4 DCB eqv., and 7.42 g1.4 DCB eqv., respectively; even though the pilot project was completed in just two months, the results showed a meaningful reduction in carbon, particulate matter, and heavy metals. If the service system can be extended, we can expect a more significant decrease in all environmental footprints. In the transition period from petrol and diesel vehicles to electric vehicles for carbon neutrality in road transportation systems, these results showed that electric vehicles can contribute significantly to reducing carbon, particulate matter, and heavy metals.Result : Carbon, particulate matter, and heavy metals reduction efforts are continuously needed in transportation. This study calculated and compared carbon, particulate matter, and heavy metal human toxicity footprints with electric, petrol, and diesel vehicles. As a result, in the future, this new small electric mobility (“TAYOU” Smart mobility vehicle) sharing service system can support and contribute to reducing carbon, particulate matter, and heavy metals emissions and footprints.

Smart and Resilient Mobility Services Platform for Managing Traffic Disruptive Events

This article aims to develop a smart mobility solution to enhance the travel experience of individuals facing traffic disruptive events. Unlike prior research focusing on isolated solutions for managing these events, this study takes a holistic approach combining real-time monitoring, predictive modeling, route guidance, and effective communication to create efficient traffic disruption management. The study introduces the Smart and Resilient Mobility Services Platform (SRMS), specifically designed to address mobility restrictions as a form of disruptive events in the Palestinian territories, West Bank. SRMS empowers users to make well-informed decisions by providing services such as real-time mapping of mobility restrictions, a prompt notification system, informal route mapping, and alternative path suggestions. Moreover, it aims to enhance engagement among travelers and citizens by adopting spatial crowdsourcing as the primary data source for potential restrictions and embracing the User-Centered Design (UCD) approach to enrich users’ interaction with the developed solution. The methodology involves presenting the architectural layering system of the SRMS platform, and detailing the prototyping and design development considering the UCD approach. Results present the practical implementation of the SRMS tailored to the Palestinian context and adopted UCD.

Flexible and Stretchable Thermoresponsive Display for Multifunctional Device Applications

Metal–organic frameworks (MOFs) have been recognized vastly as stimuli‐responsive materials owing to their extreme sensitivity toward the stimuli that make them flawless nominees for multifunctional device applications. However, MOFs are often oversensitive toward moisture, which significantly affects their stable responses and reproducibility. Herein, a MOF–polymer display (i.e., copper‐based MOF with polydimethylsiloxane) is developed that exhibits high sensitivity toward temperature changes without getting affected by moisture. In response to the thermal gradient, the display exhibits the change in color from sky blue to dark blue when the temperature varies from 30 to 100 ºC, which is attributed to the second‐order phase transition within the time interval 40 s and reversible in 60 s. To provide insights on the mechanism, ex situ UV–vis and temperature‐dependent operando X‐day diffraction are conducted, which unveils that the color change in the display is associated with reversible contraction/expansion of the unit cell parameters. In addition to that, the thermoresponse of the display remains unaffected under mechanical deformations, which indicates that the color display is mechanically and thermally stable. The as‐developed color display is mechanically robust and highly sensitive toward temperature change; it can be utilized as the color indicator in signaling temperature rise in smart mobiles or laptops during discharging to keep the user safe or applications in augmented intelligence.