Methodology and trends for an intelligent transport system in developing countries

Mfenjou, Martin Luther; Ari, Ado Adamou Abba; Abdou, Wahabou; Spies, François; Kolyang,

doi:10.1016/j.suscom.2018.08.002

Cited by 33 publications

(25 citation statements)

References 19 publications

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“…Los Sistemas Inteligentes de Transporte (en inglés, ITS) corresponden a la aplicación de tecnologías de la información y comunicación (TIC) para la gestión de los sistemas de transporte convencionales, utilizando mejoras tecnológicas destinadas a optimizar la seguridad, eficiencia, accesibilidad y sostenibilidad del transporte público, sin aumentar la infraestructura existente (Mfenjou et al, 2018). El Ministerio de Transporte (2015) establece que un sistema inteligente de transporte es la combinación de distintas áreas de la ingeniería, tal como: transporte, sistemas, financiera, ambiental, telecomunicaciones, entre otras; en búsqueda de mejorar la eficiencia en el transporte, la mitigación de los impactos ambientales, y salvaguardar la vida humana a través de la seguridad vial.…”

Section: Sistemas Inteligentes De Transporteunclassified

Detección de infracciones y matrículas en motocicletas, mediante visión artificial, aplicado a Sistemas Inteligentes de Transporte

Valencia

Ramirez-Guerrero

Castañeda

et al. 2020

risti

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Resumen: El funcionamiento incompleto de los sistemas de transporte ha propiciado el incremento del transporte ilegal de pasajeros mediante motocicletas a nivel mundial, causando altos índices de accidentalidad. En las ciudades intermedias de Colombia, el principal método de control aplicado al transporte informal consiste en imponer multas a los infractores identificados por las autoridades de tránsito. Este artículo propone el desarrollo de una aplicación que, mediante técnicas de visión artificial, sirva como herramienta para los oficiales de tránsito en la detección de tres tipos de infracciones cometidas por motociclistas: no usar casco de protección; circular por zonas prohibidas; transportar parrillero en lugares donde no está permitido. Nuestro caso de estudio fue la ciudad de Valledupar, donde se tomaron 105 imágenes de motociclistas mientras conducían. Los resultados muestran una precisión del 87,5% en la detección de infracciones, mostrando la pertinencia de la aplicación como herramienta auxiliar para desincentivar el transporte informal.

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Section: Sistemas Inteligentes De Transporteunclassified

Detección de infracciones y matrículas en motocicletas, mediante visión artificial, aplicado a Sistemas Inteligentes de Transporte

Valencia

Ramirez-Guerrero

Castañeda

et al. 2020

risti

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“…Some institutions can be monitored in real time by WSNs to prevent possible theft or fire. Another example is the application of sensor networks in intelligent transportation systems for monitoring roads or railways to prevent accidents [50]. In the military domain, these networks are used for surveillance inside and outside the theater of operations and in espionage.…”

Section: Overview Of Wsnsmentioning

confidence: 99%

Big Data Collection in Large-Scale Wireless Sensor Networks

Djedouboum

Ari

Guéroui

et al. 2018

Sensors

104

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Data collection is one of the main operations performed in Wireless Sensor Networks (WSNs). Even if several interesting approaches on data collection have been proposed during the last decade, it remains a research focus in full swing with a number of important challenges. Indeed, the continuous reduction in sensor size and cost, the variety of sensors available on the market, and the tremendous advances in wireless communication technology have potentially broadened the impact of WSNs. The range of application of WSNs now extends from health to the military field through home automation, environmental monitoring and tracking, as well as other areas of human activity. Moreover, the expansion of the Internet of Things (IoT) has resulted in an important amount of heterogeneous data that are produced at an exponential rate. Furthermore, these data are of interest to both industry and in research. This fact makes their collection and analysis imperative for many purposes. In view of the characteristics of these data, we believe that very large-scale and heterogeneous WSNs can be very useful for collecting and processing these Big Data. However, the scaling up of WSNs presents several challenges that are of interest in both network architecture to be proposed, and the design of data-routing protocols. This paper reviews the background and state of the art of Big Data collection in Large-Scale WSNs (LS-WSNs), compares and discusses on challenges of Big Data collection in LS-WSNs, and proposes possible directions for the future.

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“…Moreover Jadaan Khair [2] in their work on a comparative analysis of road safety in developed and developing countries showed that 90% of deadly accidents are caused in developing countries while these countries only have 54% of the global vehicle rate. The emergence of intelligent transportation systems (ITS) together with the new generation of mobile networks contribute to a serious reduction of the death rate on the roads [3][4][5][6]. These systems exploit technological advances of telecommunications to facilitate communication among users, precisely monitor activities in road network [7].…”

Section: Introductionmentioning

confidence: 99%

“…However, these models should consider the infrastructural realities of these countries. Thus, Mfenjou et al [4] proposed a methodology that aims at contextualizing an ITS by taking into account the infrastructural realities. In [12], the authors proposed a monitoring communication architecture for developing countries' inter-urban road networks based on control points.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective evolutionary scheme for control points deployment in intelligent transportation systems

Mfenjou

Ari

Njoya

et al. 2021

IJECE

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One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the non-dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the strength Pareto evolutionary algorithm -II (SPEA-II); and the Pareto envelope based selection algorithm-II (PESA-II). We performed the tests and compared these deployments using Pareto front and performance indicators like the spread and hypervolume and the inverted generational distance (IGD). The results obtained show that the NSGA-II method is the most adequate in the deployment of these control points.

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Methodology and trends for an intelligent transport system in developing countries

Cited by 33 publications

References 19 publications

Detección de infracciones y matrículas en motocicletas, mediante visión artificial, aplicado a Sistemas Inteligentes de Transporte

Detección de infracciones y matrículas en motocicletas, mediante visión artificial, aplicado a Sistemas Inteligentes de Transporte

Big Data Collection in Large-Scale Wireless Sensor Networks

A multi-objective evolutionary scheme for control points deployment in intelligent transportation systems

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