Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun

Integrating big data into a sustainable mobility policy 2.0 planning support system

It is estimated that each of us, on a daily basis, produces a bit more than 1 GB of digital content through our mobile phone and social networks activities, bank card payments, location-based positioning information, online activities, etc. However, the implementation of these large data amounts in city assets planning systems still remains a rather abstract idea for several reasons, including the fact that practical examples are still very strongly services-oriented, and are a largely unexplored and interdisciplinary field; hence, missing the cross-cutting dimension. In this paper, we describe the Policy 2.0 concept and integrate user generated content into Policy 2.0 platform for sustainable mobility planning. By means of a real-life example, we demonstrate the applicability of such a big data integration approach to smart cities planning process. Observed benefits range from improved timeliness of the data and reduced duration of the planning cycle to more informed and agile decision making, on both the citizens and the city planners end. The integration of big data into the planning process, at this stage, does not have uniform impact across all levels of decision making and planning process, therefore it should be performed gradually and with full awareness of existing limitations

M2* - mobility to anywhere, an IoT aggregation service platform

This work addresses the problem of the creation of a central integrated platform to collect and manipulate mobility data and sensor data towards the creation of useful information for users in their mobility process. This is an academic work towards a framework for mobility process, where that manipulate can create useful information for users, public transportation operators and authorities, energy and water real time consumption.info:eu-repo/semantics/acceptedVersio

Smart Mobility: a multimodal services study in the metropolitan area of Lisbon

Citizens’ mobility brings great challenges to the cities and smart city\u27s initiatives. This study main goal is to disclosure the current situation of the metropolitan area of Lisbon regarding smart mobility and multimodal mobility systems. The methodological approach of this study consist of collect data from citizens of the metropolitan area of Lisbon, through a survey. We report here empirical study results on citizen awareness of information systems solutions, and their level of usage in their daily lives. Our study results demonstrated the citizens of the metropolitan area of Lisbon are highly unhappy with the available mobility systems and use mainly the private car as transport mode and the importance of multimodal mobility systems were confirmed

A multimodal services study in the metropolitan area of Lisbon

Bernardo, M. R., de Castro Neto, M., & Aparicio, M. (2019). Smart mobility: A multimodal services study in the metropolitan area of Lisbon. In Atas da Conferencia da Associacao Portuguesa de Sistemas de Informacao 2019: 19ª Conferencia da Associacao Portuguesa de Sistemas de Informacao, CAPSI 2019 [19th Conference of the Portuguese Association for Information Systems, CAPSI 2019], Lisboa; Portugal; 11 October 2019 through 12 October 2019 (pp. 20). Associação Portuguesa de Sistemas de Informação.Citizens’ mobility brings great challenges to the cities and smart city's initiatives. This study main goal is to disclosure the current situation of the metropolitan area of Lisbon regarding smart mobility and multimodal mobility systems. The methodological approach of this study consist of collect data from citizens of the metropolitan area of Lisbon, through a survey. We report here empirical study results on citizen awareness of information systems solutions, and their level of usage in their daily lives. Our study results demonstrated the citizens of the metropolitan area of Lisbon are highly unhappy with the available mobility systems and use mainly the private car as transport mode and the importance of multimodal mobility systems were confirmed.authorsversionpublishe

The Importance Of Open Data Accessibility For Multimodal Travel Improvement*

The dynamic urban network continues to face a number of problems caused by traffic. One of the main problems is the increasing use of personal vehicles (especially for shorter journeys) and an unattractive alternative – public transport. In this context, Intelligent Transport Systems can be defined as a holistic, management and information communication upgrade of the classic transport and traffic system. From the passengers’ point of view, the usage of personal vehicles is still more pronounced compared to public transport. The main reason is that the public transport service quality needs to be improved if compared to the personal vehicles. The concept of multimodal travel is not new, but with the usage of adequate Intelligent Transport Systems services, it is possible to support and encourage modal shift, optimise the use of public space and influence passengers’ behaviour patterns. Multimodal Journey Planners provide travellers with better and more complete information when choosing a mode of transport so they can select the most suitable option for their needs. The open data approach is crucial for defining a system that responds to the end-users’ actual needs and aspirations (personalisation of the service). Another major challenge in providing a high-quality multimodal journey planning service is the availability and accessibility of data. EU directives require each Member State to establish a National Access Point. The National Access Point is a digital interface, a single/unique access point providing all information regarding travel and traffic. In this article, the importance of traffic data collection, acquisition and distribution according to the open data concept is described