Abstract

When people need help with day-to-day tasks they turn to family, friends or neighbours to help them out. Finding someone to help out can be a stressful waste of time. Despite an increasingly networked world, technology falls short in supporting such daily irritations. uHelp provides a platform for building a community of helpful people and supports them in finding help for day-to-day tasks. 

We present uHelp, a platform for building a community of helpful people and supporting community members find the appropriate help within their social network. Lately, applications that focus on finding volunteers have started to appear, such as Helpin or Facebook's Community Help. However, what distinguishes uHelp from existing applications is its trust-based intelligent search for volunteers. Although trust is crucial to these innovative social applications, none of them have seriously achieved yet a trust-building solution such as that of uHelp. uHelp's intelligent search for volunteers is based on a number of AI technologies: (1) a novel trust-based flooding algorithm that navigates one's social network looking for appropriate trustworthy volunteers; (2) a novel trust model that maintains the trustworthiness of peers by learning from their similar past experiences; and (3) a semantic similarity model that assesses the similarity of experiences. 

uHelp has been designed for the more sensitive and urgent tasks, where one might not be interested in broadcasting a request, nor will it have the time to handpick its trusted friends for a given sensitive request, such as finding a volunteer to picking up one's child from school in half an hour. Instead, the user will simply state its request, specify the rules of who can be trusted for this specific request, and press the help button. Searching for trusted potential volunteers then relies on one's social network, constructed from people's contact lists.

Abstract

Two smartphone applications were developed with the aim of harvesting insights of vulnerable road user accidents. The apps require a backend database with software tools for generating and managing questionnaires, etc. Such a system was developed using a MySQL database where a user-friendly platform has been developed in CakePHP. The backend system has been successfully developed and been used to handle more than 11,000 participants. The original idea was to monitor VRU via apps to detect when they may have been involved in an accident as pedestrian or cyclist based on the motion patterns from the smartphone’s motion sensors (accelerometer, gyroscope) and collect as much information as possible regarding the accident automatically (e.g. time and location of the accident). If an accident was detected, the road user should receive a questionnaire to provide detailed information of the accident (e.g. road surface conditions, lighting conditions, other road users involved). This app was used by more than 400 participants resulting in a large amount of data.

Abstract

[EN] Today, smart cities are presented as a solution to achieve a more sustainable urban development while increasing the quality of life of its citizens through the use of new technologies (Neirotti, 2013). Smart Mobility is based on innovative and sustainable ways to provide transport for the inhabitants of cities, enhancing the use of fuels or vehicle propulsion systems that respect the environment, supported by technological tools and a proactive behaviour of citizenship (Neirotti, 2013). In urban mobility, the purpose of the Smart Cities is to develop flexible systems for real-time information to support decisionmaking in the use and management of different transport modes, generating a positive impact, saving users time and improving efficiency and quality of service. In this context, several solution types are being introduced in the world’s cities. They enable the improvement of the abovementioned factors acting on the demand side resulting in more efficient journeys for individual travelers, and improved satisfaction with the service. (Skelley et Al., 2013) with a lower level of investment than that of infrastructure deployment or an increase in the level of service. One of the most extended solutions is the use of mobile apps for providing the user with contextualized -static and real time- transport information. The study is based on a survey carried out among users of public transport in Madrid under the European OPTICITES project of the 7th Research Framework Programme. The survey contained items on their transportation habits, their level of skills and technological capabilities, and their main expectations about the possibility of using a new application, the main desired capabilities and willingness to pay for use. The study results show the preferences of users of public transport capacity, static, real-time search and in-app services for a multimodal real-time application and willingness to pay for this service, all analyzed by different Slicers users. The results also establish the basis for an estimate of the usefulness of these applications for users of public transport. Velázquez Romera, G.; Monzón, A. (2016). PUBLIC TRANSPORT USERS' PREFERENCES AND WILLINGNESS TO PAY FOR A PUBLIC TRANSPORTATION MOBILE APP IN MADRID. En XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València. 2248-2266. https://doi.org/10.4995/CIT2016.2015.3498 OCS 2248 2266