1,720,998 research outputs found
Innovative Services for Electric Mobility Based on Virtual Sensors and Petri Nets
No full textAbout 60% of emissions into the earth's atmosphere are produced by the transport sector, caused by exhaust gases from conventional internal combustion engines. An effective solution to this problem is electric mobility, which significantly reduces the rate of urban pollution. The use of electric vehicles (EVs) has to be encouraged and facilitated by new information and communication technology (ICT) tools. To help achieve this goal, this paper proposes innovative services for electric vehicle users aimed at improving travel and charging experience. The goal is to provide a smart service to allow drivers to find the most appropriate charging solutions during a trip based on information such as the vehicle's current position, battery type, state of charge, nearby charge point availability, and compatibility. In particular, the drivers are supported so that they can find and book the preferred charge option according to time availability and the final cost of the charge points (CPs). To this purpose, two virtual sensors (VSs) are designed, modeled and simulated in order to provide the users with an innovative service for smart CP searching and booking. In particular, the first VS is devoted to locate and find available CPs in a preferred area, whereas the second VS calculates the charging cost for the EV and supports the driver in the booking phase. A UML activity diagram describes VSs operations and cooperation, while a UML sequence diagram highlights data exchange between the VSs and other electromobility ecosystem actors (CP operator, EV manufacturer, etc.). Furthermore, two timed Petri Nets (TPNs) are designed to model the proposed VSs, functioning and interactions as discrete event systems. The Petri Nets are synchronized by a single larger TPN that is simulated in different use cases and scenarios to demonstrate the effectiveness of the proposed VSs
Goods relocation management in city fashion retailers with an incentive system
Get PDFThe goods relocation among fashion retailers located in the same city is a daily activity carried out by trucks. The related transport externalities in the urban area have a significant weight for the citizen quality of life. The reduction in the use of heavy and polluting vehicles through innovative sharing strategies is one of the most promising strategies to minimize externalities in urban areas. In this paper a goods relocation management approach for city fashion retailers involving customers is presented. The idea is to propose to loyal customers a voucher to be spent in the store as a reward (prize in the following) for the package delivery from one shop to another; this system can be developed by an app. In the case that no customer accepts, the company trucks will perform the service. This method allows having a double advantage: customer loyalty and externalities reduction caused by moving the trucks in the city. To this aim, an integer linear programming problem is formalized to manage the involve users in the goods relocation process by the proposed prizes. A simulation is presented to show the application of the methodology in the fashion retailers
A District Energy Management Based on Thermal Comfort Satisfaction and Real-Time Power Balancing
Get PDFThis paper presents a district energy management strategy devoted to monitor and control the district power consumption in a twofold human-centered perspective: the respect of user’s comfort preferences and the minimization of the power consumption and costs. The presented district energy management system forwards the power profile determined the day ahead to each building energy management system that, in turn, minimizes its real-time power consumption and costs (based on rewards and penalties), respecting the comfort preferences. Successively, the power is redistributed among the district buildings in order to minimize the penalties by applying two approaches: a centralized approach for public buildings and a distributed methodology for private buildings. Such optimization problems are formalized by defining some linear programming problems: two case studies are solved to show the applicability of the proposed management strategies
Smart District Energy Management with Cooperative Microgrids
Get PDFThis paper faces the energy management problem of cooperative microgrids in a smart energy district. In particular, the aim of the research work is to propose an innovative optimization model to solve the problem of energy management in a district composed of several microgrids, taking into account uncertainties of key parameters. In this context, the objective of the paper is threefold: i) maximize the use of energy purchased at the day-ahead market; ii) minimize the need of additional and expensive energy in real-time iii) optimize the integration of renewable energy sources (RES), energy storage systems (ESS) and electric vehicle (EV) batteries in the microgrid. To these goals, the District Energy Management System (DEMS), i.e. the central controller of the district, must balance the microgrids energy demand with the optimal integration of RES, ESS and the batteries of EVs that are seen as movable storage devices shared among buildings. Moreover, the energy surplus can be sold back to the main power grid. The DEMS problem is solved by two approaches. In the first approach, the energy demand, the RES production and the costs are known and a linear programming problem is formalized and solved by the DEMS. In addition, a second approach is proposed in order to address the parameters uncertainty and is formalized as a stochastic linear programming problem. The optimization problems solutions provide the optimal strategy to schedule the charging and discharging operations of the storage systems and the electric vehicle batteries. A simulation case study demonstrates the benefits of the proposed approaches for the smart district
Heart Disease Diagnosis Using Machine Learning
No full textThe growing impact of heart disease on global health requires to improve diagnostic techniques for more timely and accurate diagnosis. Machine Learning (ML) has demonstrated significant potential in supporting the identification and classification of heart diseases, thanks to its ability to analyze large volumes of data and learn complex patterns. The aim of this work is to explore the application of ML algorithms for heart disease diagnosis, using two datasets ‘Heart Disease Cleveland’ and ‘Heart Failure Prediction Dataset’ available on the web. Each dataset is enriched with 1000 synthetic instances, generated by a designed Generative Adversarial Network model. Different ML-based classification models including Random Forest, Logistic Regression, Stochastic Gradient Descent and XGBoost are compared based on standard performance metrics. In addition, a stacking model as an ensemble method based on the combination of the above four models has been developed and tested. The obtained results show the effectiveness of ML models in the diagnosis of cardiac diseases, with the stacking model standing out for its superior performance according to the majority of metrics
An Integrated Framework for Binary Sensor Placement and Inhabitants Location Tracking
No full textThis correspondence paper deals with the sensor placement optimization problem in the context of indoor multiple inhabitants location tracking to solve ambient assisted living problems. Binary sensors, like passive infrared (PIR) sensors, are used to guaranty specific coverage requirements and allow privacy respecting. Moreover, within real home environments, different kinds of obstacles (like walls, high furniture, etc.) can affect the detection capacity of PIR sensors. This paper proposes an integrated framework devoted to optimize the placement of sensors and PIR sensors in smart homes by taking into account physical topologies and coverage precision constraints. An integer linear programming problem is formalized and a case study illustrates the applicability of the proposed approach and the scalability of the optimization method
A simulation and control model for building energy management
Get PDFThis paper deals with the energy consumption management problem in buildings by modeling and controlling the main electric appliances. Renewable energies are taken into account by considering the production schedules of both wind and solar sources. Each appliance is described by modular mathematical models by means of the Matlab/Simulink software. A simulator is designed that models the load energy consumptions and helps to recognize how they contribute to peak demand. Moreover, a controller to manage the load usage is designed in a Petri Net framework. In the proposed control strategy, the comfort conditions are respected for each appliances on the basis of the user preferences. Finally, a real case study validates and tests the effectiveness of the simulator applied to the considered appliances
A Review of Last Mile Logistics Innovations in an Externalities Cost Reduction Vision
Get PDFIn this paper, a review of the recent scientific literature contributions on innovative strategies for last mile logistics, focusing on externalities cost reduction, is presented. Transport is causing problems in urban areas, in particular in freight transport: modern cities need solutions to reduce externalities costs such as congestion, pollution and others, which have increased in the last few years, especially due to the growth of goods delivery. Online sales and globalization lead to new trends in freight transport, and moreover, a larger quantity of goods is expected to be delivered in the next future. In this context, most of the delivered goods end up in the city centers. Last mile logistics is the least efficient stage of the supply chain and comprises up to 28% of the total delivery cost. Therefore, the improvement of last mile logistics and a significant externalities reduction are very important challenges for researchers. New technologies and transport means, innovative techniques and organizational strategies allow handling in a more effective way the last mile delivery in urban areas. Based on the Systematic Literature Review (SLR) method, recent papers that significantly contributed, with original proposals, to the reduction of externalities in urban logistics are identified and analyzed in this work. Furthermore, a classification of the papers dealing with the externality reduction problem is presented. It is consistent with a general formulation proposed to evaluate external costs in urban area. The innovative contributions are classified into five main categories: innovative vehicles, proximity stations or points, collaborative and cooperative urban logistics, optimization of transport management and routing, innovations in public policies and infrastructures. The new paradigm of smart logistics is based on the combination of these concepts and on the proposed innovations
A Review of Digital Twin Technology for Electric and Autonomous Vehicles
No full textIn the era of technological transformation, mobility and transportation systems are becoming more intelligent and greener. Thanks to powerful technologies and tools, electric and autonomous vehicles are spreading worldwide, substituting internal combustion engine vehicles and revolutionizing the way to drive. In this context, this paper is an extended version of the paper “Digital Twin in Intelligent Transportation Systems: a Review published in 2020 7th International Conference on Control, Decision and Information Technologies (CoDIT)”. The aim of this paper is to provide a comprehensive review of the literature from the last five years on the use of digital twin (DT) technology for Intelligent Transportation Systems (ITSs), focusing on electric and autonomous vehicles. In particular, with respect to the previous work, the focus has been expanded to include DT integration with other cutting-edge technologies, such as the Internet of Things (IoT), Big Data, artificial intelligence (AI), machine learning (ML), and 5G for ITS. Moreover, this paper presents a broad perspective on challenges in EV applications, including tracking, monitoring, battery and charge management, connectivity, security, and privacy. In addition, this paper discusses how DT can be used to effectively address the current issues in electric vehicle services, such as tracking, monitoring, battery and charge management, connectivity, security, and privacy
Hydrogen Fuel for Future Mobility: Challenges and Future Aspects
Get PDFNowadays, the combustion of fossil fuels for transportation has a major negative impact on the environment. All nations are concerned with environmental safety and the regulation of pollution, motivating researchers across the world to find an alternate transportation fuel. The transition of the transportation sector towards sustainability for environmental safety can be achieved by the manifestation and commercialization of clean hydrogen fuel. Hydrogen fuel for sustainable mobility has its own effectiveness in terms of its generation and refueling processes. As the fuel requirement of vehicles cannot be anticipated because it depends on its utilization, choosing hydrogen refueling and onboard generation can be a point of major concern. This review article describes the present status of hydrogen fuel utilization with a particular focus on the transportation industry. The advantages of onboard hydrogen generation and refueling hydrogen for internal combustion are discussed. In terms of performance, affordability, and lifetime, onboard hydrogen-generating subsystems must compete with what automobile manufacturers and consumers have seen in modern vehicles to date. In internal combustion engines, hydrogen has various benefits in terms of combustive properties, but it needs a careful engine design to avoid anomalous combustion, which is a major difficulty with hydrogen engines. Automobile makers and buyers will not invest in fuel cell technology until the technologies that make up the various components of a fuel cell automobile have advanced to acceptable levels of cost, performance, reliability, durability, and safety. Above all, a substantial advancement in the fuel cell stack is required
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