4,149 research outputs found
SymbioCity: Smart Cities for Smarter Networks
The "Smart City" (SC) concept revolves around the idea of embodying
cutting-edge ICT solutions in the very fabric of future cities, in order to
offer new and better services to citizens while lowering the city management
costs, both in monetary, social, and environmental terms. In this framework,
communication technologies are perceived as subservient to the SC services,
providing the means to collect and process the data needed to make the services
function. In this paper, we propose a new vision in which technology and SC
services are designed to take advantage of each other in a symbiotic manner.
According to this new paradigm, which we call "SymbioCity", SC services can
indeed be exploited to improve the performance of the same communication
systems that provide them with data. Suggestive examples of this symbiotic
ecosystem are discussed in the paper. The dissertation is then substantiated in
a proof-of-concept case study, where we show how the traffic monitoring service
provided by the London Smart City initiative can be used to predict the density
of users in a certain zone and optimize the cellular service in that area.Comment: 14 pages, submitted for publication to ETT Transactions on Emerging
Telecommunications Technologie
Travel Time Prediction Model For Public Transport Buses In Qatar Using Artificial Neural Networks
The state of Qatar has experienced rapid population growth over the last few years.
This growth of population has caused authorities to promote the use of public
transportation, by introducing new public transport systems such as transit buses
and metro lines. The existing bus system was introduced in 2004 to the local
community in Qatar. Despite the importance of this system, there are limited studies
that are done to analyze and identify its characteristics. There is not much analysis
of the stop-to-stop travel time or schedule reliability. The objective of this research
is to develop a prediction model for transit route travel time. The model can predict
the travel time of buses using several independent variables that are different for
each transit route. The prediction model can be used as a useful tool to the decision
makers and public transport officials, which can be used for planning, system
reliability and quality control, and real-time advanced travelers’ information
systems.
The data was collected for 12 routes over a period of one year (2015-2016) within
The Greater City of Doha using Automatic Vehicle Location (AVL) system. Transit
travel time data was obtained from Mowasalat records, the sole operator of public
transport buses in Qatar. The collected data include travel time data, route
information, geometric configurations, land use, and traffic data. After systematic
checking of errors in the collected data and elimination of irreverent records, more
than 78,004 trips were analyzed using Artificial Neural Networks (ANN) data
mining technique. Prediction model, with R2 of 0.95 was developed. The results
indicate that the developed model is accurate and reliable in predicting the travel time. The model can be generalized as well to be applied to newly planned routes,
or updating the schedules of existing routes
Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events
This report summarizes current computer simulation capabilities and the availability of near-real-time data sources allowing for a novel approach of analyzing and determining optimized responses during disruptions of complex multi-agency transit system. The authors integrated a number of technologies and data sources to detect disruptive transit system performance issues, analyze the impact on overall system-wide performance, and statistically apply the likely traveler choices and responses. The analysis of unaffected transit resources and the provision of temporary resources are then analyzed and optimized to minimize overall impact of the initiating event
The Critical Role of Public Charging Infrastructure
Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change
CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship
This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship
Book of abstracts of the 24th Euro Working Group on Transportation Meeting
Sem resumo disponĂvel.publishe
Madinat Al Irfane: Is Smart Mobility Feasible?
The goal of this project was to assess the feasibility of incorporating smart technologies into the current transportation systems within Madinat Al Irfane in Rabat, Morocco. Our team worked in collaboration with Dean Essaidi, of l\u27Ecole Nationale Supérieure d\u27Informatique et d\u27Analyse des Systèmes (ENSIAS) to accomplish this goal. Through research, site assessments, surveys, and interviews, our team gauged the publics discontent with the current bus service. After completing our assessment of the existing transportation systems in Madinat Al Irfane, we concluded it is not feasible to implement smart mobility initiatives. In hopes to alleviate prevalent issues the team found in the transit systems, we developed a preliminary design review for a sensor based tracking system for the buses
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