Nous avons le plaisir de présenter le 2ème numéro de la revue “Internet des objets” coordonnée par Mehdi Ammi et Samuel Szoniecky. Il est basé sur une sélection des articles proposés à la conférence “Nouveaux Défis de l’Internet des Objets : Technique, usage, éthique” qui a eu lieu à Fès au Maroc les 18 et 19 mai 2017.
The article presents the theoretical and graphical principles for an ethical modeling of the Internet of the Things. These principles are applied to modeling the views of the European Parliament on the issue of civil rights rules for robotics. More specifically, we show how to collect raw data for modeling information existences in a knowledge ecosystem. In conclusion, we question the viability of a diagram to evaluate the ethics of connected objects and the work they still have to do to achieve this.
This paper deals with sociopolitical issues and mobile access to online information from a mobile computer terminal, putting the emphasis on mobile phones. The stakes of the Internet of things are studied in the uses and the technical systems in mobile health that have destabilized the traditional health organization. We analyze the ways in which new editorial forms, centered on the new modes of production and dissemination of information, provide mobile access to contents. We show that these modes of access are the result of the cross-relationships between technical innovations, socio-economic models of the industrial stakeholders in mobile telephony, the publishing practices of application publishers and the modes of regulation of this cross-sector area.
This paper proposes to study the recognition of certain daily physical activities by using a network of smart objects. The approach consists in the classification of certain participants’ activities, the most common ones and those that are carried out with smart objects:Make a phone call (Call), open the door (Open), close the door (Close) and watch its smartwatch (Watch). The study exploits a network of commonly connected objects: a smart watch and a smartphone, transported by participants during an uncontrolled experiment. The sensors’ data of the two devices were classified by a deep neural network (DNN) algorithm without prior data pre-processing. We show that DNN provides better results than Decision Tree (DT) and Support Vector Machine (SVM) algorithms. The results also show that some participants’ activities were classified with an accuracy of more than 98%, on average.
The article presents the results of an interdisciplinary collaboration between theater and digital art around the modalities of real-time control of an avatar by a comedian (the mocapactor). We describe the new place occupied by the digital artist alongside the mocapactor and the director in the process of directing an digital avatar in interaction with physical actors.
Recent decades have seen an explosion of available information. This explosion concerns public as well as private information. From an individual perspective, the explosion is largely materialized by the computer system that we constantly have with us, namely the smartphone. The smartphone provides immediate access to a wealth of information and a multitude of data. All these various data are often delivered to the user by means of the same single output module ie. the screen (and episodically the sound or vibrations) of the smartphone. The smartphone is an easy way to get access to many different data, but this is not always the most practical solution for each category of information, nor in all circumstances. Ambient devices can be an answer to some situations for which the smartphone is not convenient enough to get access to the required information. Ambient displays deliver effortless, instant access to information at a glance. This paper introduces the Ambient Atoms, a new ambient visualization device. The Ambient Atoms is a cheep and flexible
connected object that looks like a frame on which information is symbolically visualized. An application for the visualization of data relative to an apartment is proposed as a sample application.
We propose in this article to analyse on-line handwriting acquired on a digital graphic tablet for the early detection of neurological pathologies. Our main goal is the characterization of neurodegenerative diseases, such as Parkinson, Alzheimer, Mild Cognitive Impairment and neuropsychiatric diseases such as schizophrenia, through the use of spatiotemporal parameters of handwriting. This paper mainly describes the phase of handwriting and hand-drawn data acquisition currently underway at the Neurological Service at CHU Hassan II de Fez hospital, and gives a preliminary analysis of the spatiotemporal parameters extracted from the handwriting.