Special issue on ambient systems, networks and technologies

attracted a good number of scientific papers that contributed to the state-of-the-art in the areas of these conferences' themes. All the papers selected for this special issue have been extended from their original versions and underwent two rounds of rigorous peer-review process. Based on the reviewers' feedback , as well as the evaluations of the Guest Co-editors, 21 papers were selected for this special issue from 35 invited submissions. The accepted papers cover forthcoming development and emerging research along the lines of big data analytics, agent-based systems, IoT, WSNs and information systems. One of the papers is by Igor et al. [1] entitled BHolonification Model for a Multilevel Agent-Based System. Application to Road Traffic^. The authors of this paper presents a novel density approach to cluster and hierarchize population in order to build the initial holarchy. The proposal extends DBSCAN algorithm. Moreover, multilevel indicators based on standard deviation are proposed in order to evaluate the consistency of the holonification process. The proposed model is tested in a road traffic modeling in order to build the initial holarchy. The paper presents also the main research direction toward the control of internal and external stimuli of traffic over time. Another paper is by Ahmed et al. [2] entitled BEstimating pro-environmental potential for the development of mobility-based informational intervention: a data-driven algorithm^. This paper provides a methodological framework and describes the development of a computational algorithm that helps to identify soft changes in the travel behavior. The algorithm is based on a variety of different data sources such as activity-travel diaries and related constraint information, meteorological conditions, bicycle and public transport supply data, and emissions and air pollutant concentrations data. A variety of rules that are part of the algorithm are derived from the transport modeling literature, where constraints and factors were examined for activity-travel decisions. Three major aspects of activity-travel behavior, such as reduced car use, cold start of car engines, and participation in non-mandatory outdoor activities are considered in assessing pro-environmental potential. The algorithm is applied to collected small datasets from citizens of Hasselt (Belgium), Bologna (Italy), and Guildford (UK). A significant replaceable potential for car trips within 3 km to cycling and car trips to public transport has been found. The replaceable potential of excessive cold starts and participation in non-mandatory outdoor activities were also found, to some extent, to bring positive changes in the environment. In future research, these identified potentials are reported back to individuals with their consequence as part of a mobility-based informational intervention. Another paper is by Jabeur et al. [3] entitled BA comprehensive reputation assessment framework for volunteered geographic information in crowdsensing applications^. The authors provide as main contributions: (i) a multi-layer architecture for VGI which supports a process of reputation evaluation ; (ii) a new comprehensive model for computing reputation scores for both VGI data and contributors, based on direct and indirect evaluations expressed by users, and including the * Ansar-Ul-Haque Yasar

Jaar van publicatie:2019

Toegankelijkheid:Closed