Ontology Based Policy Mobility for Pervasive Computing

The array of devices, networks and resources available in pervasive computing environments, or smart spaces, will require effective self-management systems controlled via user-level policies. However, the local nature of smart spaces means that they present a potentially huge increase in the number of and nature of management domains, e.g. representing individual homes, shops, businesses, schools, hospitals etc. However, differences in local domain models and local resource models means that policies relevant to one smart space will often use different semantics for subject and target objects compared to other pervasive computing domains. To allow users to capture personal preferences in terms of policies that can be consistently applied as they roam between smart spaces, the semantic interoperability problem resulting from different models for policy subjects and targets must be overcome. In this paper we present a framework where the use of ontology-based semantics for policy elements allows dynamic ontology mapping capabilities to support policy mobility. We demonstrate its operation with a case study showing policy mobility in a policy-driven smart space management system

Why Geospatial Linked Open Data for Smart Mobility?

While the concept of Smart Cities is gaining momentum around the world and government data are increasingly available and accessible on the World Wide Web, key issues remain about Open Data and data standards for smart cities. A better integration and interoperabilty of data through the World Wide Web is only possible when everyone agrees on the standards for data representation and sharing. Linked Open Data positions itself as a solution for such standardization, being a method of publishing structured data using standard Web technologies. This facilitates the interlinking between datasets, makes them readable by computers, and easily accesible on the World Wide Web. We illustrate this through the example of an evolution from a traditional Content Management System with a geoportal, to a semantic based aproach. The Traffic Safety Monitor was developed in the period of 2012-2015 to monitor the road safety and to support policy development on road safety in Flanders (the northern part of Belgium). The system is built as a Content Management System (CMS), with publication tools to present geospatial indicators on road safety (e.g. the number of accidents with cars and the number of positive alcohol tests) as Web maps using stardardized Open Geospatial Consortium Webservices. The Traffic Safety Monitor is currently further developed towards a Mobility Monitor. Here, the focus is on the development of a business process model for the semantic exchange and publication of spatial data using Linked Open Data principles targeting indicators of sustainable and smart mobility. In the future, the usability of cycling Infrastructure for vehicles such as mobility scooters, bicycle trailers etc. can be assessed using Linked Open Data. The data and metadata is published in Linked open data format, opening the door for their reuse by a wide range of (smart) applications

Adaptive Q-learning-supported Resource Allocation Model in Vehicular Fogs

Urban computing has become a significant driver in supporting the delivery and sharing of services, being a strong ally to intelligent transportation. Smart vehicles present computing and communication capabilities that allow them to enable many autonomous vehicular safety and infotainment applications. Vehicular Cloud Computing (VCC) has already proven to be a technology shifting paradigm harnessing the computation resources from on board units from vehicles to form clustered computing units to solve real world computing problems. However, with the rise of vehicular application use and intermittent network conditions, VCC exhibits many drawbacks. Vehicular Fog computing appears as a new paradigm in enabling and facilitating efficient service and resource sharing in urban environments. Several vehicular resource management works have attempted to deal with the highly dynamic vehicular environment following diverse approaches, e.g. MDP, SMDP, and policy-based greedy techniques. However, the high vehicular mobility causes several challenges compromising consistency, efficiency, and quality of service. RL-enabled adaptive vehicular Fogs can deal with the mobility for properly distributing load and resources over Fogs. Thus, we propose a mobility-based cloudlet dwell time estimation method for accurately estimating vehicular resources in a Fog. Leveraging the CDT estimation model, we devise an adaptive and highly dynamic resource allocation model using mathematical formula for Fog selection, and reinforcement learning for iterative review and feedback mechanism for generating optimal resource allocation policy

Case of Indonesia

학위논문(박사) -- 서울대학교대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2023. 2. 황준석.The rapid development of digital technology and the use of information in productive processes cause structural changes in the economy in the current situation of Industry 4.0. (Neves et al., 2020) As a result of digital transformation, smart cities emerge as a type of interaction among technological, organizational, and political innovations. Innovation in mobility and transportation as an effect of smart city development, like ride-hailing, car-sharing, car-pooling, Mobility as a Service, electric vehicles, autonomous vehicles, and so on, seems to be a panacea for mobility issues (J. Lee et al., 2020a). Unfortunately, most innovation is not supported by policy and regulation. The public transport authorities frequently may take less time to regulate to enable the smart mobility concept, and like many other public authorities, transport authorities' bureaucracy may slow down the penetration of mobility innovation (Kamargianni & Matyas, 2017a) The overpopulated city will face difficulties in providing adequate transportation in implementing smart mobility agenda, mainly because the lack of public transportation cannot be solved only by expanding the road and building new transportation infrastructure. This study aims to understand the smart mobility characteristic to facilitate a strategic goal in creating public value based on citizen expectations. The study focuses on the case of Indonesia. Two essays were conducted through an in-depth literature review to achieve this objective. The first essay investigated smart mobility characteristics and factors, where expert judgment and opinion were used to categorize the most important criteria. The result is to help government design a strategy to implement smart urban mobility in Indonesia's new capital. At the same time, the second essay focused on the citizen satisfaction expectations for smart mobility. Both results will combine to fill the gap between government and citizens expectations for future urban mobility in the new capital of Indonesia.디지털 테크놀로지의 급속한 발전과 생산적인 프로세스에서의 정보 사용은 산업 4.0의 현재 상황에서 경제의 구조적 변화를 야기합니다. (Neves 등, 2020) 디지털 전환의 결과로, 스마트 시티는 기술, 조직 및 정치적 혁신 사이의 상호작용의 한 형태로 나타납니다. 스마트 시티 개발의 효과로서 승차감, 카셰어링, 카풀링, 서비스로서의 모바일성, 전기차, 오토노마스 차량 등 이동성·교통의 혁신은 이동성 문제의 만병통치약으로 보인다. (J. Lee 등, 2020a) 불행히도 대부분의 혁신은 정책과 규제에 의해 뒷받침되지 않습니다. 대중교통 당국은 스마트 이동성 개념을 활성화하기 위해 규제하는 데 시간이 적게 걸릴 수 있으며, 다른 많은 공공 기관과 마찬가지로 교통 당국의 관료주의는 이동성 혁신의 보급을 지연시킬 수 있다. (카마르지안니 & 마티아스, 2017a) 인구과잉 도시는 스마트 모빌리티 어젠다를 이행하는 데 있어 적절한 교통수단을 제공하는 데 어려움을 겪을 것이다. 그 주된 이유는 도로를 확장하고 새로운 교통 인프라를 구축하는 것만으로 대중교통의 부족을 해결할 수 없기 때문이다. 본 연구는 스마트 모빌리티 특성을 파악하여 시민의 기대치를 바탕으로 공공 가치를 창출하는 전략적 목표를 촉진하는 것을 목적으로 한다. 이 연구는 인도네시아의 사례에 초점을 맞추고 있다. 이 목적을 달성하기 위해 두 편의 에세이가 심층적인 문헌 검토를 통해 수행되었다. 첫 번째 에세이에서는 스마트 모빌리티의 특성과 요인을 조사했으며, 전문가의 판단과 의견이 가장 중요한 기준을 분류하기 위해 사용되었다. 그 결과 정부는 인도네시아의 새로운 수도에서 스마트한 도시 이동성을 구현하기 위한 전략을 설계할 수 있게 되었다. 동시에, 두 번째 에세이는 스마트 모빌리티에 대한 시민 만족 기대에 초점을 맞췄다. 두 결과 모두 새로운 수도 인도네시아의 미래 도시 이동에 대한 정부와 시민들의 기대 차이를 메우기 위해 결합될 것이다.Chapter 1. Introduction 10 1.1 Research Background 10 1.2 Indonesia New Capital Feasibility 12 1.3 Problem Description 16 1.4 Research Objectives 20 1.5 Research Questions 20 1.6 Research Outline 21 1.7 Contribution 22 Chapter 2. Smart City Initiatives Trends and Future Urban Mobility: A Literature Review 25 2.1 Smart City Development 25 2.2 Smart City Concept 26 2.2.1 Smart City Definition 28 2.2.2 Smart City Initiatives Trends 33 2.3 Future Urban Mobility Concept 34 2.3.1 Pedestrian and Walkability 37 2.3.2 Parking Management System 39 2.3.3 Innovative Mobility Services 40 2.3.3.1 Mobility as a Service (MaaS) 40 2.3.3.2 Automated Mobility on Demand (AmoD) 43 2.4 Public Value and Citizen Engagement 45 Chapter 3. Investigating Characteristics and Factors of Smart Mobility Project 48 3.1 Introduction 48 3.2 Literature Review 50 3.3 Research Methodology 59 3.3.1 Methodology Approach 59 3.3.2 Analytical Hierarchy Process (AHP) 60 3.4 Data Collection 62 3.5 Smart Mobility Characteristics 66 3.5.1 Accessibility 66 3.5.2 ICT/Technology 67 3.5.3 Infrastructure Availability 69 3.5.4 Delivery Channel 70 3.6 Smart Mobility Factors 71 3.6.1 Political & Regulatory 71 3.6.2 Socio-Economic 72 3.6.3 Digital Divide 73 3.7 Analysis Results 74 3.7.1 Characteristics Analysis Result 74 3.7.1.1 Characteristics Main Criteria Analysis 74 3.7.1.2 Characteristics Sub-Criteria Analysis 75 3.7.2 Factor Analysis Result 78 3.7.2.1 Factor Main Criteria Analysis 79 3.7.2.2 Factor Sub-Criteria Analysis 79 3.8 Analysis Result Summary and Discussion 81 3.8.1 Analysis Result Summary 81 3.8.2 Discussion 82 Chapter 4. Investigating Citizen Satisfaction Expectation on Future Mobility:Case of Indonesia 85 4.1 Introduction 85 4.2 Model Establishment and Hypothesis Development 89 4.3 Citizen Satisfaction Expectation 94 4.4 Safety and Security 95 4.4.1 Transport & Transit Safety 96 4.4.2 Transport & Transit Security 97 4.5 Comfort & Convenience 97 4.5.1 Public Transport and Density 98 4.5.2 Accessibility 99 4.5.3 Social Equity 99 4.5.4 Information 100 4.5.5 Comfort and Amenities 100 4.6 Government and Citizen Engagement 101 4.6.1 Vision & Strategy 102 4.6.2 Citizen Participation 103 4.6.3 Government Service & Transparency 103 4.7 Research Methodology 104 4.7.1 Structural Equation Model (SEM) 105 4.7.2 Covariance-based SEM (CB-SEM) and Partial Least Square SEM (PLS-SEM) 105 4.8 Survey and Data 107 4.9 Analysis Result 109 4.9.1 Measurement Model – Lower Order Construct 109 4.9.2 Indicator Reliability 110 4.9.3 Collinearity 112 4.9.4 Reliability Analysis 114 4.9.5 Convergent Validity 115 4.9.6 Discriminant Validity 116 4.9.7 Validating Higher Construct 124 4.9.8 Bootstrapping 124 4.9.9 Structural Model 125 4.10 Analysis Result Summary and Discussion 128 Chapter 5. Discussion and Policy Implication 131 5.1 Discussion 131 5.1.1 Availability, Accessibility, and Equity 134 5.1.2 Political and Regulatory Factors 135 5.1.3 The Digital Divide and Citizen Engagement 136 5.2 Policy Implication 137 5.3 Limitation & Future Research 139 Bibliography 141 Appendix 1: Smart Mobility Characteristics Questionnaire 167 Appendix 2: Smart Mobility Factors Questionnaire 177 Appendix 3: Citizen Satisfaction Expectation Questionnaire 184 Abstract (Korean) 191박

A Framework for Integrating Transportation Into Smart Cities

In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities. This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities

Integrating big data into a sustainable mobility policy 2.0 planning support system

It is estimated that each of us, on a daily basis, produces a bit more than 1 GB of digital content through our mobile phone and social networks activities, bank card payments, location-based positioning information, online activities, etc. However, the implementation of these large data amounts in city assets planning systems still remains a rather abstract idea for several reasons, including the fact that practical examples are still very strongly services-oriented, and are a largely unexplored and interdisciplinary field; hence, missing the cross-cutting dimension. In this paper, we describe the Policy 2.0 concept and integrate user generated content into Policy 2.0 platform for sustainable mobility planning. By means of a real-life example, we demonstrate the applicability of such a big data integration approach to smart cities planning process. Observed benefits range from improved timeliness of the data and reduced duration of the planning cycle to more informed and agile decision making, on both the citizens and the city planners end. The integration of big data into the planning process, at this stage, does not have uniform impact across all levels of decision making and planning process, therefore it should be performed gradually and with full awareness of existing limitations

Mobility management architecture in different RATs based network slicing

© 2018 IEEE. Network slicing is an architectural solution that enables the future 5G network to offer a high data traffic capacity and efficient network connectivity. Moreover, software defined network (SDN) and network functions virtualization (NFV) empower this architecture to visualize the physical network resources. The network slicing identified as a multiple logical network, where each network slice dedicates as an end-to-end network and works independently with other slices on a common physical network resources. Most user devices have more than one smart wireless interfaces to connect to different radio access technologies (RATs) such as WiFi and LTE, thereby network operators utilize this facility to offload mobile data traffic. Therefore, it is important to enable a network slicing to manage different RATs on the same logical network as a way to mitigate the spectrum scarcity problem and enables a slice to control its users mobility across different access networks. In this paper, we propose a mobility management architecture based network slicing where each slice manages its users across heterogeneous radio access technologies such as WiFi, LTE and 5G networks. In this architecture, each slice has a different mobility demands and these demands are governed by a network slice configuration and service characteristics. Therefore, our mobility management architecture follows a modular approach where each slice has individual module to handle the mobility demands and enforce the slice policy for mobility management. The advantages of applying our proposed architecture include: i) Sharing network resources between different network slices; ii) creating logical platform to unify different RATs resources and allowing all slices to share them; iii) satisfying slice mobility demands

Public entities driven robotic innovation in urban areas

Cities present new challenges and needs to satisfy and improve lifestyle for their citizens under the concept “Smart City”. In order to achieve this goal in a global manner, new technologies are required as the robotic one. But Public entities unknown the possibilities offered by this technology to get solutions to their needs. In this paper the development of the Innovative Public Procurement instruments is explained, specifically the process PDTI (Public end Users Driven Technological Innovation) as a driving force of robotic research and development and offering a list of robotic urban challenges proposed by European cities that have participated in such a process. In the next phases of the procedure, this fact will provide novel robotic solutions addressed to public demand that are an example to be followed by other Smart Cities.Peer ReviewedPostprint (author's final draft

Governance in niche development for a transition to a new mobility regime

Urban mobility is a difficult sustainability challenge; measures to reduce transport impacts produce only marginal reductions in overall energy use and CO2 emissions. Even fuel switch to electric vehicles and measures to manage traffic produce insufficient improvements. Seeking transport sustainability within the existing socio-technical regime involves policy approaches for dense cities to provide high-capacity, corridor-based public transport, expecting people to arrange their lives around such transport systems. Yet this socio-technical regime ill-fits modern mobility needs. The reluctance to use public transport stems much from this 150 year old regime configuration. The social-technical landscape has shifted significantly: travel patterns are increasingly dispersed in space and time – not funnelled into traditional corridor peak-hour movements. The key is not getting people to return to travel patterns of 100 years ago, but in a transition to a socio-technical transport regime that delivers sustainability compatible with the 21st century social-technical landscape. An opportunity may be emerging for socio-technical configurations in niche environments to effect transitions to alternate mobility futures. Autonomous vehicles are rapidly approaching market application. Since 2011, small autonomous pods have operated on segregated tracks at Heathrow Airport. In 2014 a similar system opened at the Suncheon Bay tourist area in South Korea. Since 2011 there have been public street trials of autonomous vehicles in the USA and in 2015 they became street legal in the UK. The Milton Keynes (MK) ‘Pathfinder’ project focuses on two-seat pods which do not need segregated tracks, but will run on cycleways and footpaths, mixing with cyclists and pedestrians. Trials will start in 2015, on short distance links from the railway station to destinations in Central Milton Keynes. This project forms part of the wider Milton Keynes Future Cities Programme and Open University-led MK:Smart project. This paper draws on these trials in MK to show through case study research how autonomous vehicles applications are moving beyond protected niches and, along with other developments, hold the potential to stimulate a major transition in public transport systems. The vehicles are small and each journey is individual to the passenger(s). Services do not run along corridor routes, like buses and trams, but are based on alternate rule-sets to the existing regime with individual journeys customised for each user. Such developments may therefore stimulate transition to totally different sorts of public transport systems and ultimately, socio-technical mobility regimes, by offering much more to users than any corridor system can provide. Rather than people adjusting their behaviour to bus routes, schedules and operating times, they travel directly, whenever they want, on services running 24/7. Thus these new regimes could be more compatible with lifestyle and economic trends that comprise 21st century socio-technical landscapes. As such, they provide credible alternatives to the private car, and so hold potential to deliver major sustainability gains. But such transitions face major challenges from entrenched actors within the existing regime. Taxis, minicabs and bus operators would be threatened. If the Uber cab app is being blocked by incumbent actors, they look likely to be powerful opponents of autonomous vehicle based cab services. However, MK provides an interesting innovation context where there are several overlapping smart transport niches in different stages of development. As well as autonomous pods, demand responsive minibuses are planned and inductive changed electric buses are in service. If these projects build links to each other (niche accumulation), demonstrate economic value and reproduced beyond their original experimental spaces (niche proliferation), there is potential for them to overcome incumbent resistance. In Milton Keynes, these processes could be getting close to reaching critical mass, opening up the possibility of moving closer to radical regime transitions

Review of Literature and Curricula in Smart Supply Chain & Transportation

This study provides a review of existing smart supply chain management (SCM) literature and current course offerings in order to identify unexplored implications of smart SCM. Specifically, the study focuses on curricula within the state of California to derive potential opportunities for the relevant practitioners in the Bay Area. In addition, the study further extends curriculum review to other well-recognized SCM programs around the U.S. By exploring current relevant course offerings from different academic institutions for higher education (i.e., universities), this research aims to deliver general ideas useful to knowledge practitioners in fields concerning SCM. Finally, the research illustrates a conceptual framework aimed at fostering familiarity with the necessary research topics for the evolving smart SCM