Towards a Fog-Enabled Intelligent Transportation System to Reduce Traffic Jam.

Frustrations, monetary losses, lost time, high fuel consumption and CO 2 emissions are some of the problems caused by traffic jams in urban centers. In an attempt to solve this problem, this article proposes a traffic service to control congestion, named FOXS-Fast Offset Xpath Service. FOXS aims to reduce the problems generated by a traffic jam in a distributed way through roads classification and the suggestion of new routes to vehicles.

Exploiting Vehicular Social Networks and Dynamic Clustering to Enhance Urban Mobility Management.

Transport authorities are employing advanced traffic management system (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the abovementioned ones, such as vehicular networks and 5G.

An Interest-Based Approach for Reducing Network Contentions in Vehicular Transportation Systems.

Traffic management systems (TMS) are the key for dealing with mobility issues. Moreover, 5G and vehicular networking are expected to play an important role in supporting TMSs for providing a smarter, safer and faster transportation. In this way, several infrastructure-based TMSs have been proposed to improve vehicular traffic mobility.

Cooperative UAV Scheme for Enhancing Video Transmission and Global Network Energy Efficiency.

Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to set up a Flying Ad Hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapid deployable systems. The user experience on watching videos transmitted over FANETs should always be satisfactory even under influence of topology changes caused by the energy consumption of UAVs. In addition, the FANET must keep the UAVs cooperating as much as possible during a mission.

An Integrated Dead Reckoning with Cooperative Positioning Solution to Assist GPS NLOS Using Vehicular Communications.

In Intelligent Transportation Systems (ITS), the Vehicular Ad Hoc Networks (VANETs) paradigm based on the WAVE IEEE 802.11p standard is the main alternative for inter-vehicle communications. Recently, many protocols, applications, and services have been developed with a wide range of objectives, ranging from comfort to security.

Distributed Egocentric Betweenness Measure as a Vehicle Selection Mechanism in VANETs: A Performance Evaluation Study.

In the traditional approach for centrality measures, also known as sociocentric, a network node usually requires global knowledge of the network topology in order to evaluate its importance. Therefore, it becomes difficult to deploy such an approach in large-scale or highly dynamic networks. For this reason, another concept known as egocentric has been introduced, which analyses the social environment surrounding individuals (through the ego-network).

Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments.

Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services for passengers. Traffic congestion is an urban mobility problem, which causes stress to drivers and economic losses. In this context, this work proposes a solution for the detection, dissemination and control of congested roads based on inter-vehicle communication, called INCIDEnT.

NodePM: a remote monitoring alert system for energy consumption using probabilistic techniques.

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN).