Smart Policy Research Articles

Sustainable tourism indicators: what’s new within the smart city/destination approach?

Indicators are a fundamental tool for destinations in their progress towards a more sustainable tourism development. However, the lack of real progress and the accelerated technological change are obliging policy makers to rethink the existing indicator systems. This paper examines the relationship between smart cities and destinations and sustainable tourism indicators by analyzing proposals at different scales. It provides a critical review of international smart city standards and the role that sustainability indicators play within them. Then, it conducts a content analysis of planning instruments applied in smart strategies in Spain, focusing on how sustainability indicators are considered under the smart paradigm. At the regional-local scale, this research compares two sets of indicators and tests the scientific validity of one of them for addressing the imbalance suffered by many indicators between their usefulness for policy makers and their academic rigor. The results show that little progress has been achieved despite the appropriation of the sustainability discourse by smart city and smart destination promoters. These findings reveal the (limited) real contribution made by smart cities/destinations to sustainable tourism development and contribute to identifying weaknesses and opportunities so as to redirect smart policies and projects. A final discussion contextualizes the findings within the novel framework of smart sustainability and highlights the need to reinforce public governance of urban and tourist spaces.

The Search for Smart Governance in Agriculture and Natural Resources

We draw on previous positive political-economic models, which explain the seeming disjointedness of observed agricultural and resource policies to develop prescriptive implications that can be actively pursued by a smart government. Smart governments would design and implement a portfolio of both public-good policies (PERTs) and distortionary, redistributive policies (PESTs). Of particular importance in this process is the structuring of smart PESTs that dynamically complement the introduction and adoption of PERT policies. We emphasize the role of smart policy mixes on asset mobility and diversification, both of which lead to more evenly distributed political-economic power and reduced incentives for future rent-seeking. We examine three illustrative examples where a political-economic, portfolio approach could aid in resolving ‘wicked’ social problems and point toward a portfolio of complementary policy prescriptions for sustainable economic growth. Smart governments design and implement portfolios of complementary public goods and redistributive policies simultaneously. We conclude with the characteristics of a smart government and the core principles of sound policy analyses.

Enabling technologies for low-latency service migration in 5G transport networks [Invited

The fifth generation (5G) mobile communications system is envisioned to serve various mission-critical services such as industrial automation, cloud robotics, and safety-critical vehicular communications. To satisfy the stringent end-to-end latency requirement of these services, fog computing has been regarded as a promising technology to be integrated into 5G networks, in which computing, storage, and network functions are provisioned close to end users, thus significantly reducing the latency caused in transport networks. However, in the context of fog-computing-enabled 5G networks, the high mobility feature of users brings critical challenges to satisfy the stringent quality of service requirements. To address this issue, service migration, which transmits the associated services from the current fog server to the target one to follow the users’ travel trace and keep the service continuity, has been considered. However, service migration cannot always be completed immediately and may lead to a situation where users experience a loss of service access. In this regard, low-latency service migration plays a key role to reduce the negative effects on services being migrated. In this paper, the factors that affect the performance of service migration are analyzed. To enable low-latency service migration, three main enabling technologies are reviewed, including migration strategies, low-latency, and high-capacity mobile backhaul network design, and adaptive resource allocation. Based on a summary of the reviewed technologies, we conclude that dynamic resource allocation is the worthiest one to research. Therefore, we carry out a use case, where reinforcement learning (RL) is adopted for autonomous bandwidth allocation in support of low-latency service migration in a dynamic traffic environment and evaluate its performance compared to two benchmarks. The simulation demonstrates that the RL-based algorithm is able to self-adapt to a dynamic traffic environment and gets converged performance, which has an obviously smaller impact on non-migration traffic than the two benchmarks while keeping the migration success probability high. Meanwhile, unlike the benchmarks, the RL-based method shows performance fluctuations before getting converged, which may cause unstable system performance. It calls for future research on advanced smart policies that can get convergence quickly, particularly for handling the migration of latency-sensitive services in 5G transport networks.

Impacts of COVID-19 and fiscal stimuli on global emissions and the Paris Agreement

The global economy is facing a serious recession due to COVID-19, with implications for CO2 emissions. Here, using a global adaptive multiregional input–output model and scenarios of lockdown and fiscal counter measures, we show that global emissions from economic sectors will decrease by 3.9 to 5.6% in 5 years (2020 to 2024) compared with a no-pandemic baseline scenario (business as usual for economic growth and carbon intensity decline). Global economic interdependency via supply chains means that blocking one country’s economic activities causes the emissions of other countries to decrease even without lockdown policies. Supply-chain effects contributed 90.1% of emissions decline from power production in 2020 but only 13.6% of transport sector reductions. Simulations of follow-up fiscal stimuli in 41 major countries increase global 5-yr emissions by −6.6 to 23.2 Gt (−4.7 to 16.4%), depending on the strength and structure of incentives. Therefore, smart policy is needed to turn pandemic-related emission declines into firm climate action. Global emissions could decrease 3.9–5.6% over 5 years due to COVID-19, and the interconnected economy means lockdown-related declines reach beyond borders. As countries look to stimulate their economies, how fiscal incentives are allocated and invested will determine longer-term emission changes.

Discrete event optimization of a vehicle charging station with multiple sockets

The relevance and presence of Electric Vehicles (EVs) are increasing all over the world since they seem an effective way to fight pollution and greenhouse gas emissions, especially in urban areas. One of the main issues related to EVs is the necessity of modifying the existing infrastructure to allow the installation of new charging stations (CSs). In this scenario, one of the most important problems is the definition of smart policies for the sequencing and scheduling of the vehicle charging process. The presence of intermittent energy sources and variable execution times represent just a few of the specific features concerning vehicle charging systems. Even though optimization problems regarding energy systems are usually considered within a discrete time setting, in this paper a discrete event approach is proposed. The fundamental reason for this choice is the necessity of limiting the number of the decision variables, which grows beyond reasonable values when a short time discretization step is chosen. The considered optimization problem regards the charging of a series of vehicles by a CS connected with a renewable energy source, a storage element, and the main grid. The objective function to be minimized results from the weighted sum of the (net) cost for purchasing energy from the external grid, the weighted tardiness of the services provided to the customers, and a cost related to the occupancy of the socket during the charging. The approach is tested on a real case study. The limited computational burden allows also the implementation in real-case applications.

Technological Solutions for Complex Problems: Emerging Electronic Surveillance Regimes in Eurasian Cities

This essay examines ‘smart city’ initiatives rapidly emerging across Eurasia that are aimed at the surveillance of disorderly and criminal behaviour in public spaces. They are a result of both locally driven demand to modernise law enforcement and global pressures to innovate. We specifically compare Kyiv, Almaty, and Bishkek. Each city differs in regard to who initiated smart city policies and under what conditions new technology was purchased from foreign vendors. Our essay contributes to the growing socio-legal literature on Eurasia by analysing how these electronic surveillance projects are used to manufacture an orderly, safe society and achieve modernity without the burden of deeper political change.

Reducing Emissions and Costs with Vehicle-to-Grid

Determining when and how to charge electric vehicles to minimize costs and potential greenhouse gas emissions is a complex optimization problem. Recently in Applied Energy, Brinkel et. al. developed a multi-objective smart charging method that can reduce costs and cut carbon emissions without upgrading existing grid infrastructure in model case scenarios.

Smart City e innovazione sociale: proposta di un framework analitico critico

For over twenty years the term smart city has entered the urban agendas of cities around the world and has established itself as one of the most influential urban paradigms. Although there is no common definition of smart city, the different actors involved in the dedicated poli-cies agree on the definition of a city in which investment in technology and human capital is aimed at improving the quality of life of citisens. However, some empirical evidence and am-biguous definitions raised increasing doubts about the effective equipollence between the so-cial and technological dimensions and the objective of the article is to develop and propose an analytical framework to help the understanding of the real importance of the social dimension in smart policies beyond the mere rhetorical dimension. To do this, the article proposes a sys-tematic review of the literature of urban studies on the smart city. In the conclusions, thanks to this new framework, the article hypothesizes the existence of a relationship between policies for the Smart City and those for Social innovation in Europe.

Information Dissemination From Social Network for Extreme Weather Scenario

The recent trend of dependence on the social network for information abstraction and propagation has a cumulative effect on critical response. The content and reliability of data are substantiated by acquiring data from a network of social site users. It captures the engaged multiple user behavior to formulate and diffuse the connected information across the channel. The objective is to identify a bridge between different data sources for event anomalies. This article proposes a novel approach toward identifying the sublevel anomalies and predictive investigation toward the use of Twitter’s social data during extreme weather scenarios. We performed qualitative analyses by gathering data from social media and weather data websites. Various analysis methods are proposed to aggregate the diffused information from the social network to generate influencing data. The analyses results further identify the connected user acknowledgment for dominant information in the public domain. This information is mapped by applying a convolutional neural network for a physical sensor data set to detect weather anomalies. Moreover, we exploited the reinforcement learning technique to determine smart policy on the influencing data. The results show that our proposed method can predict critical events with high precision during extreme weather emergency scenarios.

Recalibrating global data center energy-use estimates.

Growth in energy use has slowed owing to efficiency gains that smart policies can help maintain in the near term

Introduction: Smart Spaces and Places

Smart technologies have advanced rapidly throughout our society and across geographic spaces and places. The “smart” developments have presented unprecedented challenges and opportunities for the discipline of geography. This special issue of the Annals of the American Association of Geographers focuses on the theme of smart spaces and places from a wide range of perspectives. The collection of twenty-one articles included in this special issue offers stimulating discussion on emerging theories, conceptual frameworks, methodologies, and observations to address spaces, places, and smartness. The articles roughly belong to four topical categories: (1) spaces, places, and smartness; (2) analytical smartness; (3) critical smartness; and (4) smart sustainability and policy. Insights gained from the discussion will advance our discipline.

The Effect of International Travel on the Spread of COVID-19 in the U.S.

We examine the relationship between incoming international passengers and COVID-19 case or death counts during the first wave of the pandemic in the U.S. We find passengers from Italy, but not China, were an important source of exposure, and thus increased the early spread of COVID-19 in the U.S. These results suggest stopping travel from Europe earlier likely would have had greater impact on reducing the spread of the virus in the US, compared to the earlier ban on travel from China. Further, banning travel from pandemic hotspots may be smart policy, depending on the specific characteristics of the virus.

Policies and Programs Critical for Greater Energy Efficiency

In 2018 businesses, households and government enterprises throughout the global economy spent an estimated €7.4 trillion to meet the many demands for various energy services. Current projec­tions suggest that the present scale of annual expenditures may increase by more than 60 per­cent to €12.0 trillion by 2050 (with all costs expressed in real 2018 values). Although the global economy derives important benefits from the purchase of many energy services, the inefficient use of energy also creates an array of costs and constraints that burden our social and economic well-being. Among these costs or constraints are increased health costs, air pollution, climate change and a less productive economy—especially over the long term. Yet there is good news within the countless energy markets throughout the global economy. Whether improved lighting in homes and schools, transporting people and goods more efficiently, or powering the many industrial processes within any given nation, there are huge opportunities to improve the productive use of energy in ways that reduce total economic costs. And those same energy efficiency upgrades can also reduce greenhouse gas emissions that drive climate change, as well as lessen other impacts on both people and the global environment. However, as this manuscript suggests, it will take an adequately funded set of smart policies and effective programs, including a skilled work force, to drive the optimal scale of energy efficiency investments.

A Smart Framework for Fine-Grained Microphone Acoustic Permission Management

Microphones attracted a lot of attentions from attackers due to the sensitivity of voice data: attackers may control devices through abusing their microphones, fingerprint devices by measuring their microphones, or directly monitor the microphone readings to steal users’ private data. Nevertheless, OS developers failed to address the severe consequences. While the current security mechanism only offers a coarse-grained access control over the usage of microphones: recording all sound or shutting off, it is necessary to redesign the microphone security mechanism to enforce fine-grained restrictions over the usage of microphones. In this article, we propose a fine-grained microphone access control scheme on Android platform, referred to as FMC (Finer Microphone Controller). In our scheme, microphone acoustic permissions are granted with three finer policies: treble policy , timbre policy and exclusion policy , with which most of the attacks mentioned above can be defended against. In addition, to ease user’s policy management, we employ a smart policy recommendation method, avoiding additional manual policy approvals. The results in our experiments show that a negligible 1.06 percent performance overhead is incurred during policy enforcement. Besides, the policy recommendation system in FMC promises an accuracy of 82.82 percent averagely. We believe that our work is a practical defense scheme against attacks exploiting microphone acoustic permissions and should be employed by OS developers.

Smart Policies for Multi-Source Inventory Systems and General Tandem Queues with Order Tracking and Expediting

We study an inventory system with multiple supply sources and expediting options. The replenishment lead times from each supply source are stochastic, representing congestion and disruption. We construct a family of smart ordering and expediting policies that utilize real-time supply information. Such dynamic policies are generally difficult to evaluate, because the corresponding supply system is a tandem queue with state-dependent arrivals and routing, whose queue-length steady-state distribution is usually not in product form. Our main result is to identify two appealing special cases of the general policy, Policy-M and Policy-E, which possess simple product-form solutions and lead to closed-form performance measures. Policy-M retains full sourcing flexibility but ignores upstream congestion in making expediting decisions. Policy-E only orders from the normal, farthest source but makes expediting decisions based on both upstream and downstream information. A numerical study shows that the best Policy-M leads to a lower average cost than the best Policy-E in almost all cases. Also, implementing the best Policy-M parameters, the general policy only performs slightly better than Policy-M. These observations reveal the value of combining sourcing flexibility with some, but limited, dynamic expediting. Our findings are equally applicable to the equivalent tandem queue. They thus may aid dynamic routing and expediting decisions for online retailers and logistics providers, among others.

Challenge of Renewable Energy Transition towards Krabi’s Sustainable Energy City

This paper is a review article collecting relevant data and information for developing a transition model towards a sustainable energy city: a case study of Krabi Province, Thailand. An expanding tourism sector in Krabi is increasing energy demand, which continues to grow year after year. Meanwhile, the energy supply of the province relies on the centralization of the southern and central regional energy system to the national grid transmission system. According to the 2018 National Power Development Plan, Krabi is projected to shift to regional grid decentralization; coupled with increasing its power generation from renewable energy with affordability and community participation. Therefore, Krabi Vision 2020, which is a provincial master plan, would lead the direction of Krabi’s plan towards energy transition. Increasing renewable energy investment and disruptive technology to secure the potential of solar, biomass, biogas, wind and mini-hydro is paving the way to shift Krabi to a sustainable energy future. The implementation of a sustainable energy transition across the province, would bring benefits for the local economy, environmental conservation, and energy security. To achieve this energy transition, Krabi requires coordination of smart policy, local and government participation, and sound planning. This review study suggests that the transition towards a sustainable energy future depends on identifying the political barriers, and the adoption of effective management practices.

Public health principles to inform testing and build trust in automated vehicles

Highly publicised crashes involving self-driving or autonomous vehicles (AVs) have raised questions about safety and eroded public trust in the technology. In this State of the Art Review, we draw...

French Policy in the Sphere of Tourism

In this paper we present the current situation of France in the field of tourism and describe the main state organizations that carry on business in the sphere of tourism development in the French Republic. We also give examples of the main events delivered by these institutions for the sustainable development of the tourism industry in France. Today in France there are several state structural units that are full of vitality in this direction. Of these, the following departments and organizations were considered: Ministry of Foreign Affairs and International Development; Ministry of Commerce and Finance; Interagency Committee on Tourism, Tourism Promotion Council, Atout France, etc.
 
 Thanks to the active work carried out at the state level, France today holds one of the leading positions among the countries to be most frequently visited by tourists. Moreover, the results of this smart policy are the annual income from the development of the tourism industry in France, which, in turn, significantly affects the economic welfare of the country.
 
 Thus, a carefully thought-out state policy in the field of tourism has a favorable effect on the socio-economic condition of the country as a whole.

Performance optimization of LoRa nodes for the future smart city/industry

The application of long-range communication technologies such as LoRa to certain environments like smart cities/industries is a natural step forward towards the future IoT. However, the strict limitations imposed in some countries on the duty cycle of ISM bands can jeopardize this technological progress. To overcome this and, at the same time, improve IoT nodes’ transmission and power efficiency, a novel mathematical model has been derived. Its numerical analysis leads to a closed-form formula that characterizes node performance in terms of its transmission policy. The maximization of this formula—required to increase node performance—is then posed as an optimization problem whose solution yields smart transmission policies that maximize throughput while limiting energy consumption. The results achieved under this approach are compared to those obtained using the ADR algorithm (the most extended mechanism for choosing transmission parameters in LoRaWAN networks) and to random/conservative policies to further highlight the benefits of the proposal. Results reveal that the proposed method outperforms ADR by 33.20%, the conservative policy by 91.81%, and the random policy by 238.8%.

Optimal pooling of renewable energy sources with a risk-averse approach: Implications for US energy portfolio

Tapping into a large amount of renewable generation considering the inherent variability of renewable energy sources (RES) can greatly increase the risk of supply and demand imbalances in electric power delivery. One of the major components of this risk is the intermittency of both wind and solar power generation. In this paper, we show that by strategically planning for geographical and technological diversification of renewable generation capacity it is possible to reduce such risk in a RES-only US energy portfolio. We consider wind and solar as the sole sources of generation and use risk-averse stochastic optimization with Conditional Value-at-Risk (CVaR) to optimize energy generation locations and capacities in an idealized case study. The optimal RES portfolios demonstrate a significant improvement in generation profile compared to non-pooled or non-optimized alternatives. This confirms that with smart policy planning one can push the limits of the risk of imbalances in RES-only portfolios within continental United States, and highlights the need for system-wide thinking when designing a large-scale energy portfolio.