Interfaces of the Agriculture 4.0

The introduction of information technologies in the environmental field is impacting and changing even a traditional sector like agriculture. Nevertheless, Agriculture 4.0 and data-driven decisions should meet user needs and expectations. The paper presents a broad theoretical overview, discussing both the strategic role of design applied to Agri-tech and the issue of User Interface and Interaction as enabling tools in the field. In particular, the paper suggests to rethink the HCD approach, moving on a Human-Decentered Design approach that put together user-technology-environment and the importance of the role of calm technologies as a way to place the farmer, not as a final target and passive spectator, but as an active part of the process to aim the process of mitigation, appropriation from a traditional cultivation method to the 4.0 one

A Mobile Money Solution for Illiterate Users

Existing mobile money platforms have text based interfaces and target literate people. Illiterate people, without the assistance of literate individuals, cannot use such platforms. Applying user-centered requirements gathered in an Ethiopian context, this paper presents the design and development of a mobile money solution that targets illiterate people. Particular emphasis is given to how illiterate users deal with cash money in their everyday life and how such practices can be mapped into financial technology design. Given the ubiquity of mobile telephony in Africa, our solution is based on the widely available, relatively inexpensive and open source Android mobile web platform. The proposed system enables illiterate individuals to count money bills, while providing the facility to accept and make payments. In so doing, we provide an example of how a pervasive technology such as smartphones can empower a hitherto often neglected user category of illiterate users

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

The impact of Digital Platforms on Business Models: an empirical investigation on innovative start-ups

Digital platforms have the ability to connect people, organizations and resources with the aim of facilitating the core interactions between businesses and consumers as well as assuring a greater efficiency for the business management. New business concepts, such as innovative start-ups, are therefore created based on innovation, scalability and the relationships within the community around them. The purpose of this work is to deeply understand the evolution of business models brought by innovative and dynamic companies operating through online platforms. In order to achieve the objectives set, an exploratory multiple-case study was designed based on in-depth structured interviews. The aim was to conduct a mixed analysis, in order to rely both on qualitative and quantitative data. The structured interview protocol was therefore designed to collect and then analyse data concerning the company profile and managers’ perspectives on the phenomenon of interest. The interview protocol was submitted in advance and then face-to-face interviews were carried out with the following professional figures: Chief Executive Officer (CEO), General Manager, Chief Technology Officer (CTO), Marketing Manager and Developers. Collected data were analysed and processed through the Canvas Business Model in order to clearly outline similarities and differences among the sample. Results can be considered under two viewpoints. On the one hand, this work provides a detailed overview of the companies interviewed, according to the dimensions of: reference market dynamics, type and number of customers, scalability. On the other one, they allow to identify some success patterns regarding key activities, key resources, channel mix strategy, costs management, value proposition, customer segmentation, key partners and the way to obtain revenues. Results from the multiple-case study with 15 Italian start-ups provide interesting insights by comparing the innovative business models developed and highlighting key differences and similarities. verall, the start-ups analyzed, operating in several sectors, showed great growth prospects and the possibility to create value for their customers through innovative products and services offered through digital platforms