Daniele Sacco

Personal Mobility Service System in Urban Areas: The IRMA Project

We present an ongoing research project, namely Integrated Real-time Mobility Assistant (IRMA). IRMA is a software system that targets the personal mobility in a near future scenario, oriented to green, shared and public transports. IRMA aims to be an extensible, easy-to-implement and sustainable modular platform based on the combined use of multiple information sources (crowd, open, social, and sensor data) and on array of value propositions, each serving a class of stakeholders, which include municipality, users, transport providers. Hence, IRMA supports users in the entire lifecycle of mobility, and municipalities and transport providers in the whole cycle of mobility management. IRMA is deployed on both smartphone and web, and is built on a hierarchy of re-usable web services, that are based on SOA/EDA (Service Oriented Architecture / Event Driven Architecture).

Cloud Computing: An Architectural and Technological Overview

We present a Systematic Literature Review (SLR) on Cloud Computing that selected 39 papers from first tier journals and conferences in the period 2008-2012. The selective approach captures the relevant points of view on Cloud Computing, namely the overall paradigm in terms of delivery and deployment. Afterwards, we point out the technological issues about networking and data management in Cloud Computing. This SLR extends previous reviews thanks to a longer time period and a wider research sample.

Service Level Management (SLM) in Cloud Computing - Third Party SLM Framework

The key issue in cloud computing in enterprises is the management of the Quality of Service (QoS), by an appropriate SLM (Service Level Management). Cloud Service Provider are offering SLMs to their users. We think that a third party SLM can be a better way to assure a robust and equal SLM. This paper presents the elements of third party SLM, namely Cloud Service Registration Agent, Negotiation Agent, Compensation Agent, Comment Agent, Billing Agent and Service Monitoring Engine. Such framework has been tested in a real life case. Results show that third party SLM is not only equal, but also dependable and reasonably easy to implement.

CITY FEED: A Crowdsourcing System for City Governance

In city governance, participation and engagement of stakeholders are a critical issue. Many researches use crowdsourcing to foster such participation and collaboration. To make sure that such support is complete, an evaluation grid shall be developed. To serve such need, we introduce a framework to assess the maturity of crowd-sourced municipality services. To show a structured example of crowd based city governance, we present CITY FEED, a system consisting of transactional and analytical modules. CITY FEED has been designed, implemented and deployed as a pilot in Pavia, Italy.

A system for green personal integrated mobility: A research in progress

We present an ongoing research on an Integrated Real-time Mobility Assistant (IRMA). IRMA is a software system that targets the personal mobility in a near future scenario, based on green, shared and public transports. IRMA handles end-to-end itineraries that may involve multiple transport systems, and encompasses both commuter mobility and visitor mobility. The objective of IRMA is to make practically feasible a mobility that balances efficiency of time, energy/pollution and cost. Therefore, IRMA supports users in plotting the itinerary and also when en-route. IRMA architecture includes a smartphone application and a set of web services to gather and interpret any relevant source of information, that includes open data, crowd data and big data. The technology is SOA/EDA (Service Oriented Architecture / Event Driven Architecture) and uses GTFS format to access open data. IRMA, after being proved on test cases, shall be tested by the students of University of Pavia. IRMA concept is a step ahead current personal mobility systems that simply suggest and track itineraries.

Cloud Computing: A Business and Economical Perspective

We present a Systematic Literature Review (SLR) on Cloud Computing that selected 51 papers from first tier journals and conferences in the period 2008-2012. The selective approach captures the economical perspective on Cloud Computing highlighting especially the business issues, cost/pricing models, and legal issues raised by the adoption of this new technological approach. Finally, it also spots emerging issues as a general lack of framework for security and service level management that respond to the peculiar profile of Cloud Computing.

Mobility Service Systems: Guidelines for a possible paradigm and a case study

This paper discusses a framework for the design of business services, called Service System (SS). SSs are a layer built on the top of Internet of Things (IoT) and Internet of Services (IOS). SSs integrate two components, Internet of Business (IOB) and Internet of Data (IOD). IOB delivers complex business services that combine services from IOS and IOT. In turn, IOD links semantically the information that is extracted from IOS and IOT and that is processed in IOB; also, it provides a repository for future applications. The association of SS architecture with Open Source drives a twofold roadmap, with a top down design and a bottom implementation. The SS concept is exemplified on a IRMA, namely a project on urban mobility, with pilot cities in Europe and China, where a demo SS is being developed by using Open Source software.

Social data analysis framework in cloud and Mobility Analyzer for Smarter Cities

One emerging and challenging issue in Smarter Cities is Mobility. In order to gather mobility data for relevant analyses, two solutions are widely discussed, namely the conventional standardized infrastructure sensors and the novel social sensing solution. However infrastructure sensors solution is too costly, that is unfeasible for every city. On the contrast, social sensing is a renewal approach, by which people perform “sensory data” collection tasks. In order to widely conduct the second solution and meet various needs of cities, it requires the ability to 1) support various social data sources, 2) be scalable, customizable and configurable, and 3) use cost-efficient IT resources. However current research cannot overcome these challenges. Therefore, this paper presents a social sensing data analysis framework in cloud for smarter cities, especially to support smart mobility. As a case study, Mobility Analyzer, a subsystem of IRMA (Integrated Real-time Mobility Assistant, that is a pilot project of Pavia, Italy), is implemented.

Cloud Computing: The Issue of Service Quality: An Overview of Cloud Service Level Management Architectures

The paper presents a framework for quality management of Cloud Services, that aims to meet requirements of both providers and enterprises. In providers, a capacity planning phase forecasts the load in order to identify resources, while a quality aware cloud balances in real time SLM and efficiency. In enterprises, a dynamic SLA negotiation system chooses the most convenient provider for commodity services, while a dashboard enables enterprises to analyze the business impact of the cloud Qos. Finally, an independent authority verifies the actual QoS that is delivered by providers to enterprises.

Smart cities, urban sensing, and big data: mining geo-location in social networks

Location-based social networks offer spatiotemporal information which can be accessed through public application programming interfaces and have drawn the interest of researchers with diverse scientific backgrounds. This availability of data enables the potential use of geo-located content as an additional, low-cost and infrastructureless source of information for urban sensing in smart cities. All these aspects along with the need for real-time analytics for urban sensing, take us to Big Data management and its related issues. Real-time urban sensing uses citizens as active and passive sensors and can reveal important insights about human behavior in the city. A systematic literature review outlines related works and gaps in current research. In this chapter, we propose a reference model to exploit Big Data for urban sensing and we validate it using a case study. Finally, we give recommendations for future research about location and mobility mining of social network data.