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The Internet of Things (IoT) is one of the most fast-evolving and most pervasive technological advancements of the last decade. Driven by IoT's promise for an interconnected world for all people, through a shared Internet-based infrastructure, more and more businesses expand their activities to embrace, competitively, this new concept. More importantly, the ubiquitous, highly granular, and of increasing interconnection and computational capabilities nature of the IoT fabric creates a unique ecosystem for developing powerful, intelligent applications not limited to simply gathering and analyzing environmental and people data. This potential combines the IoT's physical capabilities with the achievements of the more mature discipline of Artificial Intelligence (AI). However, there is still a large number of businesses with no clear plans of investing in the IoT-plus-AI potential, citing multiple obstacles mainly related to the difficulty of understanding, adapting, and developing advanced AI techniques. Our goal is to show that advanced AI functionalities can, now, be easily implemented and operated through existing IoT platforms, by developing an intelligent, remote, surveillance application based on IBM's Cloud and Watson platforms as well as the Raspberry Zero W low-cost IoT device. [ABSTRACT FROM AUTHOR]

This paper presents a cognitive computing model, based on artificial intelligence (AI) technologies, supporting task automation in the accounting industry. Drivers and consequences of task automation, globally and in accounting, are reviewed. A framework supporting cognitive task automation is discussed. The paper recognizes essential differences between cognitive computing and data analytics. Cognitive computing technologies that support task automation are incorporated into a model delivering federated knowledge. The impact of task automation on accounting job roles and the resulting creation of new accounting job roles supporting innovation are presented. The paper develops a hypothetical use case of building a cloud-based intelligent accounting application design, defined as cognitive services, using machine learning based on AI. The paper concludes by recognizing the significance of future research into task automation in accounting and suggests the federated knowledge model as a framework for future research into the process of digital transformation based on cognitive computing. [ABSTRACT FROM AUTHOR]

In the recent years the progress in technology and the increasing availability of fast connections have produced a migration of functionalities in Information Technologies services, from static servers to distributed technologies. This article describes the main tools available on the market to perform Analytics as a Service (AaaS) using a cloud platform. It is also described a use case of IBMWatson Analytics, a cloud system for data analytics, applied to the following research scope: detecting the presence or absence of Heart Failure disease using nothing more than the electrocardiographic signal, in particular through the analysis of Heart Rate Variability. The obtained results are comparable with those coming from the literature, in terms of accuracy and predictive power. Advantages and drawbacks of cloud versus static approaches are discussed in the last sections. [ABSTRACT FROM AUTHOR]

In February 2011, Watson, IBM's "smart" computer, defeated two former Jeopardy champions. While the application of the technology may support some legal research functions, the current state of the technology probably will not allow Watson to replace law librarians in the near future. Yet, given the economic realities of our firms and institutions, librarians do need to consider technologies that may reduce the considerable cost associated with discovering and maintaining access to legal information. Free and open source software and systems and cloud-based initiatives may provide innovative approaches librarians should consider. [ABSTRACT FROM AUTHOR]

Nowadays, the penetration of sensors and actuators in different application fields is revolutionizing all aspects of our daily life. One of the major sectors that is taking advantage of such cutting-edge cheap smart devices is healthcare. In this context, Remote Patient Monitoring (RPM) at home represents a tempting opportunity for hospitals to reduce clinical costs and to improve the quality of life of both patients and their families. It allows patients to be monitored remotely by means networks of Internet of Things (IoT) medical devices equipped with sensors and actuators that collect healthcare data from patients and send them to a Cloud-based Hospital Information System (HIS) for processing. Up to now, many different proprietary software systems have been developed as stand-along expensive solutions, presenting interoperability, extensibility, and scalability issues. In recent years, the European Commission (EC) has promoted the wide adoption of FIWARE technology, launching 16 Industrial Accelerators focusing on different application fields. One of these, i.e., FICHe, is specialized in healthcare, providing the guidelines on how to develop eHealth systems. This paper focuses on how to compose new cutting-edge IoT and Cloud-based Cyber Physical Health Sytem (CPHS) services and applications interconnected with remote medical sensors and actuators using FIWARE technology in the context envisioned by FICHe. In particular, we discuss the design and development of an RPM system implemented through the collaboration between the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) "Bonino Pulejo" (i.e., a clinical and research healthcare centre specialized in the treatment of neuro lesions), University of Messina, IBM Research, Telefónica, and the University of the Western Cape in South Africa. The description of our best practice provides a model and guidelines for the development of lightweight and low cost RPM services for rural and isolated areas, with the expectation of expanding healthcare to the developing world and in general allows us to outline how to deal with the real adoption of the FIWARE technology in an e-health project. [ABSTRACT FROM AUTHOR]