Machine-Environment Interaction

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Wireless Control Networks".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 3400

Special Issue Editors

Versailles Systems Engineering Laboratory, University of Versailles, 78000 Versailles, France
Interests: software ambient intelligence; sementicsemantic knowledge representation; software quality
Special Issues, Collections and Topics in MDPI journals
Department of Computer Science, ECE Paris School of Engineering (ECE Paris Ecole d’Ingénieurs), Paris, France
Interests: knowledge representation; machine learning; computational intelligence; artificial intelligence; formal methods; multimodal computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The machine-environment interaction is vast and is itself a complex domain. It is located at the crossroads of several artificial intelligence disciplines, the representation of knowledge and reasoning, ambient intelligence, networks of sensors, etc.

An intelligent machine (robot, vehicle, drone, etc.) can evolve in a so-called “smart” environment (e.g. smart home, smart city, etc.). Such connected environment has a network of sensors that an intelligent machine can use in addition to its own sensors to better understand the environment and interact with the objects that are present in such environment. Man is part of this environment; hence human-machine integration is a special case of machine-environment interaction.

The interaction loop between the machine and environment is made up of the following processes: perception, comprehension, decision and action. Thus, an intelligent machine has the capacity to perceive the environment, understand the current state of such environment, reason to make decisions, and act on the environment to execute decisions.

Research and development in interactive systems entails many challenges and opportunities, not only in hardware and software but also on various sensors, which constitute important tools of these systems to perceive the environment.

JSAN is delighted to launch this call for papers for this Special Issue. We invite researchers to submit papers on a topic within the field of machine-environment interaction including related fields, which may include, but are not limited to, the following areas:

  • Representation of the environment of an interactive system: models, formalisms
  • The perception of the environment of interactive systems
  • Data fusion and fission in interactive systems
  • Techniques and methods for optimization and learning to facilitate interaction
  • Reasoning in decision-making components of interactive systems
  • System for evaluation and analysis of interactive systems
  • Networks of sensors for interactive systems

Prof. Dr. Amar Ramdane-Cherif
Dr. Manolo Dulva Hina
Guest Editors

  • Submissions of “extended versions” of already published works (e.g., conference/workshop papers) should be significantly extended with a relevant part of novel contribution (at least 50% new work). A “Summary of Differences” between the submitted paper to this special issue and the former one must be included.
  • This  Special Issue includes selected papers from the Second EAI International Conference on Computational Intelligence and Communications  (     Authors of  these papers are invited to submit an extended version of their paper for consideration.
  • New submissions from other community are also welcome.

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • knowledge representation
  • reasoning systems
  • sensor networks
  • decision systems
  • sensors and actuators
  • AI

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:


23 pages, 2502 KiB  
Knowledge-Based Approach for the Perception Enhancement of a Vehicle
J. Sens. Actuator Netw. 2021, 10(4), 66; - 18 Nov 2021
Cited by 1 | Viewed by 2332
An autonomous vehicle relies on sensors in order to perceive its surroundings. However, there are multiple causes that would hinder a sensor’s proper functioning, such as bad weather or lighting conditions. Studies have shown that rainfall and fog lead to a reduced visibility, [...] Read more.
An autonomous vehicle relies on sensors in order to perceive its surroundings. However, there are multiple causes that would hinder a sensor’s proper functioning, such as bad weather or lighting conditions. Studies have shown that rainfall and fog lead to a reduced visibility, which is one of the main causes of accidents. This work proposes the use of a drone in order to enhance the vehicle’s perception, making use of both embedded sensors and its advantageous 3D positioning. The environment perception and vehicle/Unmanned Aerial Vehicle (UAV) interactions are managed by a knowledge base in the form of an ontology, and logical rules are used in order to detect and infer the environmental context and UAV management. The model was tested and validated in a simulation made on Unity. Full article
(This article belongs to the Special Issue Machine-Environment Interaction)
Show Figures

Figure 1

Back to TopTop