Smart City Scenario Editor for General What-If Analysis.

Due to increasing urbanization, nowadays, cities are facing challenges spanning multiple domains such as mobility, energy, environment, etc. For example, to reduce traffic congestion, energy consumption, and excessive pollution, big data gathered from legacy systems (e.g.

Data Sources and Models for Integrated Mobility and Transport Solutions.

The number of data sources and models in the mobility and transport domain strongly proliferated in the last decade. Most formats have been created to enable specific and innovative applications. On the other hand, the available data models present a certain degree of complexity in terms of their integration and management due to partial overlaps, and in most cases, they could be exploited alternatively to implement the same smart and latest innovative solutions.

Evidence-based clinical engineering: Health information technology adverse events identification and classification with natural language processing.

The primary goal of this project is to create a framework to extract Real-World Evidence to support Health Technology Assessment, Health Technology Management, Evidence-Based Maintenance, and Post Market Surveillance (as outlined in the EU Medical Device Regulation 2017/745) of medical devices using Natural Language Processing (NLP) and Artificial Intelligence. An initial literature review on Spontaneous Reporting System databases, Health Information Technologies (HIT) fault classification, and Natural Language Processing has been conducted, from which it clearly emerges that adverse events related to HIT are increasing over time. The proposed framework uses NLP techniques and Explainable Artificial Intelligence models to automatically identify HIT-related adverse event reports.

Estimating CO Emissions from IoT Traffic Flow Sensors and Reconstruction.

CO emissions from burning fossil fuels make a relevant contribution to atmospheric changes and climate disruptions. In cities, the contribution by traffic of CO is very relevant, and the general CO estimation can be computed (i) on the basis of the fuel transformation in energy using several factors and efficiency aspects of engines and (ii) by taking into account the weight moved, distance, time, and emissions factor of each specific vehicle. Those approaches are unsuitable for understanding the impact of vehicles on CO in cities since vehicles produce CO depending on their specific efficiency, producer, fuel, weight, driver style, road conditions, seasons, etc.

Multi Clustering Recommendation System for Fashion Retail.

Fashion retail has a large and ever-increasing popularity and relevance, allowing customers to buy anytime finding the best offers and providing satisfactory experiences in the shops. Consequently, Customer Relationship Management solutions have been enhanced by means of several technologies to better understand the behaviour and requirements of customers, engaging and influencing them to improve their shopping experience, as well as increasing the retailers' profitability. Current solutions on marketing provide a too general approach, pushing and suggesting on most cases, the popular or most purchased items, losing the focus on the customer centricity and personality.

Automating IoT Data Ingestion Enabling Visual Representation.

The Internet of things has produced several heterogeneous devices and data models for sensors/actuators, physical and virtual. Corresponding data must be aggregated and their models have to be put in relationships with the general knowledge to make them immediately usable by visual analytics tools, APIs, and other devices. In this paper, models and tools for data ingestion and regularization are presented to simplify and enable the automated visual representation of corresponding data.

Classification of users' transportation modalities from mobiles in real operating conditions.

The modern mobile phones and the complete digitalization of the public and private transport networks have allowed to access useful information to understand the user's mean of transportation. This enables a plethora of old and new applications in the fields of sustainable mobility, smart transportation, assistance, and e-health. The precise understanding of the travel means is at the basis of the development of a large range of applications.

An IoE and Big Multimedia Data Approach for Urban Transport System Resilience Management in Smart Cities.

Today, the complexity of urban systems combined with existing and emerging threats constrains administrations to consider smart technologies and related huge amounts of data generated as a means to take timely and informed decisions. The smart city needs to be prepared for both expected and unexpected situations, and the possibility to mitigate the effect of the uncertainty behind the causes of disruptions through the analysis of all the possible data generated by the city open new possibility for resilience operationalization. This article aims at introducing a new conceptualization for resilience and presenting an innovative full stack solution to exploit Internet of Everything (IoE) and big multimedia data in smart cities to manage resilience of urban transport systems (UTS), which is one of the most critical infrastructures of the city.

High Density Real-Time Air Quality Derived Services from IoT Networks.

In recent years, there is an increasing attention on air quality derived services for the final users. A dense grid of measures is needed to implement services such as conditional routing, alerting on data values for personal usage, data heatmaps for Dashboards in control room for the operators, and for web and mobile applications for the city users. Therefore, the challenge consists of providing high density data and services starting from scattered data and regardless of the number of sensors and their position to a large number of users.

MicroServices Suite for Smart City Applications.

Smart Cities are approaching the Internet of Things (IoT) World. Most of the first-generation Smart City solutions are based on Extract Transform Load (ETL); processes and languages that mainly support pull protocols for data gathering. IoT solutions are moving forward to event-driven processes using push protocols.

Sii-Mobility: An IoT/IoE Architecture to Enhance Smart City Mobility and Transportation Services.

The new Internet of Things/Everything (IoT/IoE) paradigm and architecture allows one to rethink the way Smart City infrastructures are designed and managed, but on the other hand, a number of problems have to be solved. In terms of mobility the cities that embrace the sensoring era can take advantage of this disruptive technology to improve the quality of life of their citizens, also thanks to the rationalization in the use of their resources. In Sii-Mobility, a national smart city project on mobility and transportation, a flexible platform has been designed and here, in this paper, is presented.

Mobile emergency, an emergency support system for hospitals in mobile devices: pilot study.

Background: Hospitals are vulnerable to natural disasters, man-made disasters, and mass causalities events. Within a short time, hospitals must provide care to large numbers of casualties in any damaged infrastructure, despite great personnel risk, inadequate communications, and limited resources. Communications are one of the most common challenges and drawbacks during in-hospital emergencies.