Smart Cities, Volume 3, Issue 1 (March 2020) – 8 articles

With the rapid increase of vehicles in use worldwide, the need for efficient traffic monitoring systems has arisen. This work proposes a low-cost vehicular traffic monitoring system using IoT devices and fog computing. The system is based on a three-tiered architecture which is composed of (i) the mobile tracking system that records the positions of the vehicles using GPS technologies; (ii) the information gathering system which gathers all the data collected by the mobile tracking system; and (iii) the fog devices that process the data collected and extract the information needed. The system is tested in the town of Corfu during a period of increased tourism when the traffic is considered to be relatively dense. The mobile tracking system devices are placed on taxis and with the help of professional taxi drivers the accuracy of the data collected is evaluated. The system is able to record the movement of the vehicles accurately using its own independent data. The results can be remotely accessed by utilizing fog and cloud computing infrastructure established to process the data and upload it on a server. The system is used to give a better understanding of the speed variance in the center of the town during different dates and hours. In conclusion the system presented in this study can be utilized to monitor the traffic and provide vital information about its behavior in relation to time. Full article

Discussions on “smart cities” are gaining in popularity in the past two decades and has shown potential in tackling the cities’ environmental, social, and economic challenges. Smart cities are known as a system of physical infrastructure, the information and communications technology (ICT) infrastructure, and the social infrastructure that exchange information that flows between its many different subsystems. The “smart cities” concept has been introduced with various dimensions, among those, the embedded ICT infrastructure in smart cities is playing a decisive role between the functions of the system. One of the important derivatives of ICT is the new communication mediums known as social network services (SNSs), which is emergent and introduces additional functionalities to “smart cities”. This paper seeks to advance the understanding of SNSs in smart cities to evaluate the effects on the innovation and entrepreneurial ecosystem. This agenda has been tackled by a rigorous methodological approach in order to capture and evaluate the presence of entrepreneurially concerned discussions in a popular SNS intermediate (Twitter). Beyond the methodological contribution on handling big data in SNSs for gaining insights on innovation and entrepreneurial aspects in smart cities, the findings distinguished the influence of a certain category of content generators (professionals) that drive the biggest motives of the interactions in SNSs. Full article

Modern object recognition algorithms have very high precision. At the same time, they require high computational power. Thus, widely used low-power IoT devices, which gather a substantial amount of data, cannot directly apply the corresponding machine learning algorithms to process it due to the lack of local computational resources. A method for fast detection and classification of moving objects for low-power single-board computers is shown in this paper. The developed algorithm uses geometric parameters of an object as well as scene-related parameters as features for classification. The extraction and classification of these features is a relatively simple process which can be executed by low-power IoT devices. The algorithm aims to recognize the most common objects in the street environment, e.g., pedestrians, cyclists, and cars. The algorithm can be applied in the dark environment by processing images from a near-infrared camera. The method has been tested on both synthetic virtual scenes and real-world data. The research showed that a low-performance computing system, such as a Raspberry Pi 3, is able to classify objects with acceptable frame rate and accuracy. Full article

During the course of ubiquitous data monitoring in the underwater environment, achieving sustainable communication links among the sensor nodes with astute link quality seems an ordeal challenge. Energy utilization has a direct impact because all active devices are battery dependent and no charging or replacement actions can be made when cost- effective data packet delivery has been set as the benchmark. Hop link inspection and the selection of a Shrewd link through a resurrecting link factor have been nothing short of a bleak challenge, and only possible after meticulous research to develop a shrewd underwater routing synergy using extra porous energy shells (SURS-PES) which has never been conducted before. After broadcasting packets, the sensor node conducts a link inspection phase, thereby, if any link is found to be less than or equal to 50% shaky, the destination receiving node adds its residual energy status and returns it to the source node which adds some unusable energy porous shell to strengthen the link from 5% to a maximum of 90% and sends it only to the targeted node, therefore, an unaltered data packet delivery is anticipated. Performance evaluation was carried out using an NS2 simulator and the obtained results were compared with depth-based routing (DBR) and energy efficient DBR (EEDBR) to observe the outcomes with results that confirmed the previously mentioned direction for research in this area. Full article

The smart city notion provides an integrated and systematic answer to challenges facing cities today. Smart city policy makers and technology vendors are increasingly stating their interest in human-centered smart cities. On the other hand, in many studies smart city policies bring forward a one-size-fits-all type of recommendation for all areas in question instead of location-specific ones. Based on the above considerations, this paper illustrates that smart citizen characteristics, alongside local urban challenges, are paving the way towards more effective efforts in smart city policy decision making. Our main presumption is that the development level of human-centered indicators of smart cities varies locally. The scientific objective of this paper is to find a simple, understandable link between human smart characteristics and local determinants in Limassol city, Cyprus. The data set consists of seven indicators defined as human smart characteristics and seven which determine local urban challenges consisting of demographic dynamics and built infrastructure attributes based on housing. Correlations of the 14 above indicators are examined in entirety and separately, as the study area was divided into three spatial sub-groups (high, moderate, and low coverage areas) depending on dispersed urbanization, as the main challenge of the study area. The data were obtained mainly from the most recent population census in 2011 and categorized in sub-groups by triggering CLC 2012. Analyzing the statistics using principal component analysis (PCA), we identify significant relationships between human smart city characteristics, demographic dynamics and built infrastructure attributes which can be used in local policy decision making. Spatial variations based on the dispersed urbanization are also observed regarding the above-mentioned relationships. Full article

In large-scale civil emergencies such as floods, earthquakes, and extreme weather conditions, extended geographic areas and a great number of people may be affected by the unfortunate events. The wireless internet and the widespread diffusion of smart-phones and mobile devices make it possible to introduce new systems for emergency management. These systems could improve the efficiency of the interventions by transferring information between affected areas and a central decision support system. Information on the state of the infrastructures, on people displacement, and on every other important and urgent issue can be gathered in the disaster area. The central system can manage all the received information and communicate decisions back to people and also facilitate the exchange of information for different people that are still in the disaster area. This paper presents a requirement analysis for these kinds of systems. The presented analysis allows better tailoring of the features of these systems with the aim to meet the real need of emergency management operators and citizens. Full article

An in-vehicle controller area network (CAN) bus is vulnerable because of increased sharing among modern autonomous vehicles and the weak protocol design principle. Spoofing attacks on a CAN bus can be difficult to detect and have the potential to enable devastating attacks. To effectively identify spoofing attacks, we propose the authentication of sender identities using a recurrent neural network with long short-term memory units (RNN-LSTM) based on the features of a fingerprint signal. We also present a way to generate the analog fingerprint signals of electronic control units (ECUs) to train the proposed RNN-LSTM classifier. The proposed RNN-LSTM model is accelerated on embedded Field-Programmable Gate Arrays (FPGA) to allow for real-time detection despite high computational complexity. A comparison of experimental results with the latest studies demonstrates the capability of the proposed RNN-LSTM model and its potential as a solution to in-vehicle CAN bus security. Full article

Over the past decade, the process of urbanization in Vietnam has taken place rapidly, leading to strong social disturbances and causing cities to face many problems. All these challenges have put pressure on urban planning and governance to make adjustments to allow cities to become livable. Moreover, the quality of urbanization is reflected not only in growth but also in harmonious development in all aspects. The urban development process must accordingly be handled by more smart solutions. Smart city development is becoming a trend not only in urban areas all over the world but also in Vietnam. The paper aims to assess the initial phases of the smart city development process in Dalat City. It first evaluated a four-dimensional smart city’s strategic elements of city vision and transformation known as Strengths-Weaknesses-Opportunities-Threats. Then, based on these analytical characteristics, an adaptive model for development is suggested. This paper extends the previous research on smart cities and draws attention to further study on smart city development in Vietnam. Full article