Giovanni Delnevo

I want to ride my bicycle: A microservice-based use case for a MaaS architecture

This work presents a use case on multimodal urban paths in a smart mobility context. The proposed solution builds on the experience already matured and developed by the authors in different fields: crowdsourcing and sensing done by users to gather data related to urban barriers and facilities, computation of personalized paths for users with special needs, and integration of open data provided by bus companies to identify the actual accessibility features and estimate the real arrival time of vehicles at stops. In terms of functionality, the first “monolithic” prototype fulfilled the goal of composing the aforementioned pieces of information to support citizens with reduced mobility (users with disabilities and/or elderly people) in their urban movements. In this paper, we describe a service-oriented architecture that exploits the microservices orchestration paradigm to enable the creation of new services and to make the management of the various data sources easier and more effective. The manuscript demonstrates the effectiveness of the approach showing a successful use case of a service that take into account multimodal paths, by involving cyclists, bicycle lanes, and bike sharing services in a urban environments. Such a use case take into account the users interface and interaction mechanisms, which are strongly affected by the context of use.

In-vehicle Human Machine Interface: An Approach to Enhance Eco-Driving Behaviors

In the context of behavioral change for a more sustainability mobility, we designed and implemented an in-vehicle human machine interface for electric vehicles, on the basis of an approach we propose that exploits gamification and machine learning techniques. Our main goal is to equip the driver with instant and accurate eco\-driving strategies, obtaining an optimization of the energy consumption. More specifically, we have developed a prototype that collects data related to the drivers braking style and makes use of a machine learning model to forward-predict the resulting energy gain. It then accordingly fosters custom eco-driving behaviour by means of gamified interactions provided on an infotainment dashboard on the car. We have conducted some tests and this paper presents the preliminary and promising results we obtained.

Discovering the City: Crowdsourcing and Personalized Urban Paths Across Cultural Heritage

Travel planners and mobile applications related to cultural heritage can play an interesting role in the development of smart cities, when they are integrated each other, engaging the user in touristic and entertainment activities, letting him/her be a source of cultural resources. This paper focuses on a microservices-based architecture, defined with the aim of providing support in computing personalized urban paths across cultural heritage places and in sharing multimedia resources about points of interest. A prototype of mobile application has been implemented on the basis of such architecture, showing the feasibility of the proposed approach thanks to personas and related scenarios.

Gamifying cultural experiences across the urban environment

New media and devices are offering huge possibilities for the enhancement and the enrichment of heritage experiences, improving the users’ involvement. In particular, tourists equipped with their mobile devices are invading cultural attractions, sharing pictures and comments (together with hashtags and geo-localized positions) on social networks. These represent an unofficial source of data, which can be integrated with the official ones provided by GLAM (Galleries, Libraries, Archives, and Museums) and cultural heritage institutions, enriching them. At the same time, travel planners and mobile applications related to cultural heritage can play an interesting role in the development of smart cities, when they are integrated each other, engaging the user in touristic and entertainment activities, letting him/her be a source of cultural resources.This work focuses on equipping users (citizens and tourists) with a system providing support in computing personalized urban paths across cultural heritage places (monuments, palaces, museums, and other points of interest (POIs) related to cultural heritage in the urban environment) and in sharing multimedia resources about POIs, by exploiting gamification elements with the aim of engaging citizens and tourists. A mobile application prototype has been implemented, showing the feasibility of the proposed approach and exploiting crowdsourcing activities as a source of information for cultural places and works of art.

Digital Invasions Within Cultural Heritage: Social Media and Crowdsourcing

The wide diffusion of mobile devices and of digital technologies are dramatically changing the usage scenarios in different contexts. One of them is cultural heritage, where new media are offering huge possibilities for the enhancement and the enrichment of heritage experience, improving the users’ involvement. In particular, tourists equipped with their mobile devices are invading cultural attractions, sharing pictures and comments (together with hashtags and geo-localized positions) on social networks. These represent a source of data, which can be integrated with the official ones provided by GLAM (Galleries, Libraries, Archives, and Museums) and cultural heritage institutions, enriching them. In this paper, we explore how social networks and crowdsourcing activities can be exploited as a source of information for cultural places and pieces of art.

Smart Mobility and Sensing: Case Studies Based on a Bike Information Gathering Architecture

Mapping services and travel planner applications are experiencing a great success in supporting people while they plan a route or while they move across the city, playing a key role in the smart mobility scenario. Nevertheless, they are based on the same algorithms, on the same elements (in terms of time, distance, means of transports, etc.), providing a limited set of personalization. To fill this gap, we propose PUMA, a Personal Urban Mobility Assistant that aims to let the user add different factors of personalization, such as sustainability, street and personal safety, wellness and health, etc. In this paper we focus on the use of smart bikes (equipped with specific sensors) as means of transports and as a mean to collect data about the urban environment. We describe a cloud based architecture, personas and travel scenario to prove the feasibility of our approach.