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Electric Vehicles (EVs) are gaining momentum due to several factors, including the price reduction as well as the climate and environmental awareness. This paper reviews the advances of EVs regarding battery technology trends, charging methods, as well as new research challenges and open opportunities. More specifically, an analysis of the worldwide market situation of EVs and their future prospects is carried out. Given that one of the fundamental aspects in EVs is the battery, the paper presents a thorough review of the battery technologies—from the Lead-acid batteries to the Lithium-ion. Moreover, we review the different standards that are available for EVs charging process, as well as the power control and battery energy management proposals. Finally, we conclude our work by presenting our vision about what is expected in the near future within this field, as well as the research aspects that are still open for both industry and academic communities.

Wireless technologies are making the development of new applications and services in vehicular environments possible since they enable mobile communication between vehicles (V2V), as well as communication between vehicles and infrastructure nodes (V2I). Usually, V2V communications are dedicated to the transmission of small messages mainly focused on improving traffic safety. Instead, V2I communications allow users to access the Internet and benefit from higher level applications. The combination of both V2V and V2I, known as V2X communications, can increase the benefits even further, thereby making intelligent transportation systems (ITS) a reality. In this paper, we introduce V2X-d, a novel architecture specially designed to estimate traffic density on the road. In particular, V2X-d exploits the combination of V2V and V2I communications. Our approach is based on the information gathered by sensors (i.e., vehicles and road side units (RSUs)) and the characteristics of the roadmap topology to accurately make an estimation of the instant vehicle density. The combination of both mechanisms improves the accuracy and coverage area of the data gathered, while increasing the robustness and fault tolerance of the overall approach, e.g., using the information offered by V2V communications to provide additional density information in areas where RSUs are scarce or malfunctioning. By using our collaborative sensing scheme, future ITS solutions will be able to establish adequate dissemination protocols or to apply more efficient traffic congestion reduction policies, since they will be aware of the instantaneous density of vehicles.

In Vehicular Networks, communication success usually depends on the density of vehicles, since a higher density allows having shorter and more reliable wireless links. Thus, knowing the density of vehicles in a vehicular communications environment is important, as better opportunities for wireless communication can show up. However, vehicle density is highly variable in time and space. This paper deals with the importance of predicting the density of vehicles in vehicular environments to take decisions for enhancing the dissemination of warning messages between vehicles. We propose a novel mechanism to estimate the vehicular density in urban environments. Our mechanism uses as input parameters the number of beacons received per vehicle, and the topological characteristics of the environment where the vehicles are located. Simulation results indicate that, unlike previous proposals solely based on the number of beacons received, our approach is able to accurately estimate the vehicular density, and therefore it could support more efficient dissemination protocols for vehicular environments, as well as improve previously proposed schemes.

In recent years, new architectures and technologies have been proposed for Vehicular Ad Hoc networks (VANETs). Due to the cost and complexity of deploying such networks, most of these proposals rely on simulation. However, we find that most of the experiments made to validate these proposals tend to overlook the most important and representative factors. Moreover, the scenarios simulated tend to be very simplistic (highways or Manhattan-based layouts), which could seriously affect the validity of the obtained results. In this paper, we present a statistical analysis based on the 2k factorial methodology to determine the most representative factors affecting traffic safety applications under real roadmaps. Our purpose is to determine which are the key factors affecting Warning Message Dissemination in order to concentrate research tests on such parameters, thus avoiding unnecessary simulations and reducing the amount of simulation time required. Simulation results show that the key factors affecting warning messages delivery are the density of vehicles and the roadmap used. Based on this statistical analysis, we consider that VANET researchers must evaluate the benefits of their proposals using different vehicle densities and city scenarios, to obtain a broad perspective on the effectiveness of their solution. Finally, since city maps can be quite heterogeneous, we propose a roadmap profile classification to further reduce the number of cities evaluated.

LoRa has proven to be an ideal solution for Internet of Things networks and applications that require long‐distance communications, such as those related to smart cities or precision agriculture. Its low cost combined with the wide availability of LoRa‐compatible devices make it possible to easily deploy a large number of sensors capable of collecting and transmitting key information for new services and applications. However, the process of adding new devices into a Long Range Wide Area Network (LoRaWAN) network represents a significant challenge on a large scale, as each device must be individually configured and manually registered to join the network. This manual approach is costly and impractical when it comes to deploying a very large number of devices. To address this problem, this paper proposes two deployment strategies (semi‐automatic and automatic) to simplify and streamline the process of activating and registering LoRaWAN devices. These strategies facilitate the deployment of large‐scale devices in smart cities, and their adoption can significantly enhance the deployment of LoRaWAN devices. Experimental results clearly demonstrate the benefits of our solution. Specifically, for 500 devices, the semi‐automatic deployment is 3.75 times more efficient, and the automatic deployment is an impressive 394.87 times faster than the manual deployment. This paper proposes two deployment strategies (semi‐automatic and automatic) to simplify and streamline the process of activating and registering LoRaWAN devices in IoT networks. These strategies facilitate the deployment of large‐scale devices in smart cities, and their adoption can significantly enhance the deployment of LoRaWAN devices.

Proprietary systems used to modernize Industry 4.0 usually involve high financial costs. Consequently, using low-cost devices with the same functionalities, capable of replacing these proprietary systems but at a lower cost, has become an incipient trend. However, these low-cost devices usually come with electromagnetic interference problems as they are encapsulated in electrical panels, sitting alongside electromechanical devices. In this article, we present Mode Binary Search, an algorithm specifically designed for use in a low-cost automated-industrial-productivity-data-collection system. Specifically, productivity data are obtained from the availability and sealing signals of the thermoplastic sealing machines in production lines belonging to the agri-food industry. Mode Binary Search was designed to cluster sealing signals, thus enabling us to identify which products have been made. Furthermore, the algorithm determines when the manufacturing of each product starts and ends, in other words, the exact moment a product change occurs and all this without the need for operator supervision or intervention. Finally, we compared our algorithm, based on binary search, with three clustering mechanisms: k-means, k-rms and x-means. Out of all the cases we analyzed, the maximum error committed by Mode Binary Search is limited to 2.69%, thereby outperforming all others.

Internet of Things (IoT) is expected to become a driver in an emerging era of interconnected world through the advanced connectivity of smart devices, systems, and services. IoT goes beyond a broad range of Machine-to-Machine (M2M) communication technologies and covers a wide variety of networking protocols. There exist solutions like MQTT or SIP collecting data from sensors, CoAP for constrained devices and networks, or XMPP for interconnecting devices and people. Also there is a plethora of standards and frameworks (OSGi, AllJoyn) bringing closer the paradigm of IoT vision. However, the main constraint of most existing platforms is their limited mutual interoperability. To this end, we provide a comprehensive description of protocols suitable to support the IoT vision. Further, we advocate an alternative approach to already known principles and employ the SIP protocol as a container for M2M data. We provide description of data structures and practical implementation principles of the proposed structures (JSON and Protocol Buffers are discussed in detail) transmitted by SIP as a promising enabler for efficient M2M communication in the IoT world. Our reported findings are based on extensive hands-on experience collected after the development of advanced M2M smart home gateway in cooperation with the operator Telekom Austria Group.

Next, we will introduce a teaching experience about the development and application of a support tool for the practical lessons of the Database I subject at the Escuela Universitaria Politécnica de Teruel. ANACON is a query analyzer based on SQL (Structured Query Language), which allows pupils to learn quickly and intuitively this language without having to know the complex aspects and the special features that usually show the query analyzers built-in the DBMS (Database Management Systems). In this article we describe the tool, just as the obtained results after making use of it, related on the one hand to the presented number over registered number and on the other hand, to the pupil marks obtained during the academic course 2004/2005. In spite of the fact that it can be soon to make conclusions, the results encourage us to improve some application features, and to carry on with the tool in the practical lessons of the subject. [PUBLICATION ABSTRACT]

Reference management software is a well-known tool for scientific research work. Since the 1980s, it has been the subject of reviews and evaluations in library and information science literature. This paper presents a systematic review of published studies that evaluate reference management software with a comparative approach. The objective is to identify the types, models, and evaluation criteria that authors have adopted, in order to determine whether the methods used provide adequate methodological rigor and useful contributions to the field of study.