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2017 | Buch

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Smart Cities, Green Technologies, and Intelligent Transport Systems

5th International Conference, SMARTGREENS 2016, and Second International Conference, VEHITS 2016, Rome, Italy, April 23-25, 2016, Revised Selected Papers

herausgegeben von: Markus Helfert, Cornel Klein, Brian Donnellan, Oleg Gusikhin

Verlag: Springer International Publishing

Buchreihe : Communications in Computer and Information Science

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Smart Cities and Green ICT Systems, SMARTGREENS 2016, and the Second International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2016, held in Rome, Italy, in April 2016.
The 11 full papers of SMARTGREENS 2016 presented were carefully reviewed and selected from 72 submissions. VEHITS 2016 received 49 paper submissions from which 5 papers were selected and published in this book. The papers reflect topics such as smart cities, energy-aware systems and technologies, sustainable computing and communications, sustainable transportation and smart mobility.

Inhaltsverzeichnis

Frontmatter

Invited Paper

Frontmatter

About Monitoring in a Service World

Abstract

Monitoring of services is becoming more and more common to ensure the quality of applications and to provide the required level of service. Nowadays, the technology needed for supporting monitoring and, as a consequence, also monitoring data are widely available. On the other hand, new challenges and research issues arise concerning the design of the monitoring infrastructure, to provide the relevant information both to users and service providers, and their use, and in particular the analysis of monitored data. This paper discusses the main aspects of monitoring, and the use of monitoring data, focusing on event identification and the evaluation of the actions and resources needed to maintain the required level of quality of service. Research challenges related to modeling and using monitoring data are discussed.

Barbara Pernici, Pierluigi Plebani, Monica Vitali

Smart Cities and Green ICT Systems

Frontmatter

Analysing the Impact of Storage and Load Shifting on Grey Energy Demand Reduction

Abstract

We present an analysis on the application of load shifting and storage to enhance the use and penetration of green energy while decreasing grey (non-environmentally friendly) energy demand. We use multi-agent-based simulations that are fed with real data to analyse the impact of load shifting and storage on energy consumption as well as energy prices. We show results for scenarios in which storage is placed at different locations. In this way, results suggest that up to \(15\%\) reduction in grey energy consumption is feasible during peak times. Nonetheless, if the percentage of distributed renewable resources grows to \(50\%\), higher reductions can be achieved, i.e. up to \(50\%\). Finally, an important finding suggests that distributed storage helps to keep prices for green energy low.

Iván S. Razo-Zapata, Mihail Mihaylov, Ann Nowé

Enhancing User Comfort in Demand Response Solutions for Water Heaters: User-Centric Hot Water Management

Abstract

Demand Response (DR) solutions for tank electric water heaters (WHs) let residential consumers benefit financially, however, a negative impact of DR on personal comfort may force users to reject them. To facilitate DR implementation in practice, there is a need to consider the end-user’s comfort. Typically, DR for WHs concerns only the user satisfaction with a variable water temperature. This paper extends the conventional control by considering the tap water flow as a variable during water activities. The main contributions of this paper are (i) a model to relate user comfort with the tap water flow rate, (ii) the control mechanism consisting of the pre-heating control and the flow control to maintain the user comfort. Simulations demonstrate that the proposed control coupled with the suggested user interface can inform about available trade-offs between energy consumption and comfort, and thus can help the user to rationally save energy for water heating.

Alexander Belov, Alexandr Vasenev, Nirvana Meratnia, Paul J. M. Havinga

Characterizing Smart Grid Events Using Clustering Methods

Abstract

Phasor Measurement Units (PMUs) are widely used in smart grid to provide high-frequency, real-time measurements of the electrical waves, enabling wide-area monitoring and control. These devices generate a significant amount of data on a daily basis, which presents challenges for grid operators to leverage the useful information contained in this data. In this paper, we present an empirical study of applying unsupervised clustering on PMU data for event characterization on the smart grid. We show that although the PMU data are time series in nature, it is more efficient and robust to apply clustering methods on carefully selected features from the data collected at certain instantaneous moments in time. Experiments have been carried out on real PMU data collected by Bonneville Power Administration in their wide-area monitoring system in the pacific northwest, and the results show that our instantaneous clustering method achieves high homogeneity, which provides great potentials for identifying unknown events in the grid without substantial training data. In addition, we also present our initial effort in cluster-specific classification, which incorporates supervised learning in the process to classify event types within individual clusters.

Eric Klinginsmith, Richard Barella, Xinghui Zhao, Scott Wallace

The Structural and Kinematical Analyses of a Wired Robotic Mechanism with Three Degrees of Freedom

Abstract

The spreading presence of the industrial robots in environmental friendly manufacturing systems requires developing of a robots’ database. The aim of this material is to present a fundamental model of the mechanism acted with wires. This fact is needed because the literature data from the field of the robotic mechanisms operated through wires is relatively, poor. The paper presents the fundamental model of this type of robots and one of its applications.

Nicolae Bercan, Mihaiela Iliescu, Cristian Matran

Electric-Motion Infrastructure in Romania - Research on Machining Processes of Mechanical Components of e-Motion Charging Station

Abstract

Aspects of electric vehicles specific infrastructure in Romania are evidenced by this paper. The focus is on charging station and fast charging stations designed and installed by the first Romanian company dedicated 100% to e-mobility, E-Motion Electric. Research on machining processes, milling and drilling, of the mechanical components of these stations is also presented. A system for measuring the values of machining forces, data acquisition and processing, as well as real time control scheme does also represent innovation in this paper. The regression models, determined by statistical data processing, should be applied in optimization of machining process.

Mihaiela Iliescu, Luige Vlădăreanu, Nicolae Bercan, Alexandru Rogojinaru

Modelling the Diagnosis of Industry Internet of Things

Abstract

We consider necessary to discuss on a scientific article about the diagnosis of Internet of Things (IoT) for industry applications, e.g. controlled flexible manufacturing systems (FMS). In order to analyse and diagnose the main characteristics of these systems we focus on models realized with Markov chains of FMS with stochastic and not equal throughput rates. Discrete-event models assume that FMS is decomposed, and we study the following events: an Internet server fails, an Internet server is repaired, an Internet server memory buffer fills up, an Internet server memory buffer empties. The IoT diagnosis is performed with by calculating the time to absorption in Markov model of the IoT controlled FMS. Future developments of IoT diagnosis of FMS are also discussed in this work.

Calin Ciufudean, Corneliu Buzduga

Monitoring Data Reduction in Data Centers: A Correlation-Based Approach

Abstract

Monitoring data are collected and stored in a wide range of domains, especially in data centers, which integrate myriads of services and massive data. To handle the inevitable challenges brought by increasing volume of monitoring data, this paper proposes a correlation-based reduction method for streaming data that derives quantitative formulas between correlated indicators, and reduces the sampling rate of some indicators by replacing them with formulas predictions. This approach also revises formulas through iterations of the reduction process to find an adaptive solution in dynamic environments of data centers. One highlight of this work is the ability to work on upstream side, i.e., it can reduce volume requirements for data collection of monitoring systems. This work also tests the approach with both simulated and real data, showing that our approach is capable of data reduction in complex data centers.

Xuesong Peng, Barbara Pernici

Adopting DDS to Smart Grids: Towards Reliable Data Communication

Abstract

The rapid growth of technologies in smart grid (SG) enables reliable data communication. SG involves many sub-domains each of which involves various types of components and devices which require significant data communication in an efficient manner. Thus, a key success factor for SG lies in reliable data exchange between components and domains. Data Distribution Service (DDS) is a standard for data-centric communication based on a publish-subscribe protocol for distributed applications. DDS enables reliable data communication supported by various features such as quality-of-service (QoS). In this paper, we describe the potential of DDS for SG for reliable and efficient data communication. We first give an overview of DDS and discuss its benefits for SG. We then describe communication requirements and constraints in SG. Finally, we discuss how DDS can be tailored to SG with respect to the requirements and constraints.

Alaa Alaerjan, Dae-Kyoo Kim

The Surveillance Society: Which Factors Form Public Acceptance of Surveillance Technologies?

Abstract

Currently, surveillance technologies are increasingly used to give people a sense of safety in medical as well as crime surveillance contexts. On the one hand, perceived safety can be supported by adequate surveillance technologies (e.g., cameras), however, the systematic use of surveillance technologies undermines individual privacy needs on the other hand. In this empirical study, we explore users’ perceptions on safety and privacy in the context of surveillance systems. In order to understand if the acceptance of surveillance depends on usage contexts, surveillance technologies in the urban were compared to the medical context. Using an online survey, 119 users were requested to indicate their acceptance regarding different types of surveillance contexts and technologies, differentiating perceived benefits and barriers as well as safety and privacy needs. We investigate acceptance differences towards surveillance technologies at various locations (private and public) as well. In this paper, we especially explore the impact of different surveillance contexts, locations and individual perceived crime threat on the acceptance of surveillance technologies and on the needs for privacy and safety.

Julia van Heek, Katrin Arning, Martina Ziefle

A Smarter Sidewalk-Based Route Planner for Wheelchair Users: An Approach with Open Data

Abstract

In this chapter we describe an approach to integrate GIS maps (endorsed by discrete features, such as points, lines, polygons), in order to develop a route planner for wheelchair users. We integrate public available data and an approach with free software with a novel model for route planning, based on sidewalks, crosswalks and curb ramps, as opposed to traditional street-based approaches. We show that our sidewalk-based model is more suitable than available route planning services under mobility constraints, using a case study in Curitiba, Brazil.

Nádia P. Kozievitch, Leonelo D. A. Almeida, Ricardo Dutra da Silva, Rodrigo Minetto

A Simplified Methodological Approach Towards the Net Zero Energy District

Abstract

Zero energy conceptual framework is attracting increasing interest in European target policies aiming at more sustainable and liveable urban and built environments. Despite its compelling context in scientific literature and practical applications, the commonly used approach is principally adopted on the aspect of an individual building. Cases with zero energy concept are few in literature. The aim of this paper is the development of a methodological approach to extend the ‘zero energy building’ to the ‘zero energy district’ by taking into account two challenges: (1) the impact of urban structure (typo-morphology) on the actual energy needs and (2) the location. It proposes a simplified methodology within three strategic axes through the systemic approach of the district and thereby opens and addresses future research perspective to be widely investigated to develop ‘smart’ districts with operational and long-term context by introducing the notion of ‘smart ground’.

Sesil Koutra, Vincent Becue, Christos S. Ioakimidis

Vehicle Technology and Intelligent Transport Systems

Frontmatter

Optimal Strategies for Adaptive Cruise Control

Abstract

In addition to providing good tracking capability and reducing fuel consumption, an Adaptive Cruise Control (ACC) system is required to be very comfortable. Although several appealing ACC policies have been introduced so far, a few of which are currently in use, it is still difficult in general to find an ACC policy that is able to optimally combine requirements such as high safety, low fuel consumption and satisfactory comfort level. Additionally, no systematic methods are available for the optimization of a control policy performance. This chapter addresses these problems by comparing different ACC policies and developing an optimization method based on a multi-objective Pareto criterion, finalized at designing policies with an all-around performance. Furthermore, the designed optimal policy is tested in view of its application on real vehicles via simulations.

Clement U. Mba, Carlo Novara

An Automatic Traffic Congestion Identification Algorithm Based on Mixture of Linear Regressions

Abstract

One innovative solution to traffic congestion is to use real-time data and Intelligent Transportation Systems (ITSs) to optimize the existing transportation system. To address this need, we propose an algorithm for real-time automatic congestion identification that uses speed probe data and the corresponding weather and visibility to build a unified model. Based on traffic flow theory, the algorithm assumes three traffic states: congestion, speed-at-capacity, and free-flow. Our algorithm assumes that speed is drawn from a mixture of three components, whose means are functions of weather and visibility and defined using a linear regression of their predictors. The parameters of the model were estimated using three empirical datasets from Virginia, California, and Texas. The fitted model was used to calculate the speed cut-off between congestion and speed-at-capacity by minimizing either the Bayesian classification error or the false positive (congestion) rate. The test results showed promising congestion identification performance.

Mohammed Elhenawy, Hesham Rakha, Hao Chen

Dos and Don’ts of Datasharing in V2X-Technology

User Diverse Perspectives in Different Traffic Scenarios

Abstract

Currently, the trust in V2X-technology is naturally expected. To share private data with novel technologies is not a new phenomenon today, but data security and privacy are worldwide topics, which are constantly gaining importance. Therefore, the present paper will show influential user factors for technology acceptance and the willingness to share data like prior experience with driver assistance systems. Also technical affinity and frequency of car usage are investigated user requirements. By focusing different traffic scenarios, results show also an undeniable reluctance towards sharing private data with other traffic participants or companies. Traffic management such as police or the infrastructure itself are however entrusted with various personal information and data. Further, it was possible to identify different user profiles in data sharing behavior.

Teresa Schmidt, Ralf Philipsen, Martina Ziefle

ICT for Urban Area Logistics with Electric Vehicles Compared Within Simulated and Real Environments

Abstract

ICT-systems for electric vehicles (EVs), e.g. planing, monitoring and analysing for urban area logistics, can become complex and difficult to use. Evaluating them within acceptance tests requires a lot of experimentees as well as a lot of equipment. Unfortunately, mostly more than available within the project. The following approach within the research project Smart City Logistik (SCL), funded by the German Federal Ministry for Economic Affairs and Energy (BMWi), tries to use the ICT-system as it is and connects those system through a dynamicly and proceduraly generated simulation environment, based on real road and terrain data. Finally, the results will be compaired to real environments by using EVs.

Volkmar Schau, Sebastian Apel, Kai Gebhardt, Johannes Kretzschmar, Christian Stolcis, Marianne Mauch, Johan Buchholz

Analysis and Possible Mitigation of Interferences Between Present and Next-Generation Marine Radars

Abstract

The maritime traffic is significantly increasing in the recent decades due to its advantageous features related to costs, delivery rate and environmental compatibility. For this reasons it requires a high degree of control and an adequate assistance to the navigation. The related systems are the Vessel Traffic System (VTS), mainly using radar and the Automatic Identification System (AIS). In the recent years a new generation of marine radars with a lower cost of maintenance is being developed. They are based on the solid-state transmitter technology and uses coded “long pulse” in transmission, i.e. high “duty-cycle”, with “pulse compression” in reception. The main drawbacks of these apparatuses are the interference effects that they might cause on existing marine radars, becoming critical when the traffic density increases. The AIS data (identity, location, intention and so on) can be useful to estimate the mutual distances among ships and the mean number of surroundings vessels, that is the number of marine radars in visibility. Using suitable models it is shown that the high duty-cycle of solid-state marine radars can generate severe interference to all marine radar sets in visibility with a significant reduction, well below the international regulations, of their detection capability. The mitigation of these damaging effects, not an easy task, can be achieved by changing the radar waveforms, i.e. resorting to Noise Radar Technology.

Gaspare Galati, Gabriele Pavan, Francesco De Palo

Backmatter

Titel: Smart Cities, Green Technologies, and Intelligent Transport Systems
herausgegeben von: Markus Helfert
Cornel Klein
Brian Donnellan
Oleg Gusikhin
Verlag: Springer International Publishing
Electronic ISBN: 978-3-319-63712-9
Print ISBN: 978-3-319-63711-2
DOI: https://doi.org/10.1007/978-3-319-63712-9