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Applied Sciences
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Advances and Applications in Ambient Intelligence and Smart Environments
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Advances and Applications in Ambient Intelligence and Smart Environments

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 2322

Special Issue Editors

Dr. Alberto Trombetta

E-Mail Website
Guest Editor
Department of Pure and Applied Sciences, Computer Science Division, Insubria University, 21100 Varese, Italy
Interests: design and implementation of secure and reliable applications in distributed; data-intensive architectures; analysis, integration and management of very large - possibly non-relational - data repositories; data modeling using Semantic Web technologies
Special Issues, Collections and Topics in MDPI journals
Dr. Daniele Spoladore

E-Mail
Guest Editor
1. Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), 23900 Lecco, Italy
2. Department of Pure and Applied Sciences, Computer Science Division, Insubria University, 21100 Varese, Italy
Interests: ontology development and engineering; decision support systems; semantic web application; applications for rehabilitation and continuity of care; smart home and environments
Special Issues, Collections and Topics in MDPI journals
Dr. Andrea Zangiacomi

E-Mail Website
Guest Editor
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), 20133 Milan, Italy
Interests: digitalization; Industry 4.0; supply chain management; industrial engineering; human factors; technology acceptance; technology roadmapping; mass customization

Special Issue Information

Dear Colleagues,

Smart environments have been widely investigated in the past 25 years because of their potential for tackling some of the major issues that characterize modern societies, such as independent living of aging population, supporting people with disabilities in daily life activities, monitoring and optimizing energy consumption, enhancing interconnection and enabling adaptability in smart workplaces. Recent advancements in the fields of Ambient Intelligence (AmI) and Artificial Intelligence (AI) have provided momentum for the Internet of Things, Smart Homes, Tele-healthcare and Ambient Assisted Living as paradigms for the personalization of services to improve living conditions in indoor environments.

The combination of AmI and AI is gradually becoming more common and accessible for everyone, and promises to revolutionize the ways in which people behave and interact in living environments. Nonetheless, there are still some technological, theoretical and societal issues that may hinder the further progress and adoption of these technologies.

In this context, this Special Issue encourages the submission of high-quality, original and innovative contributions regarding the application of AmI and AI in different areas. The list of possible topics includes (but is not limited to):

  • AI and AmI-based applications in Smart Homes and Buildings;
  • AI and AmI-based applications exploiting wearable systems to deliver personalized indoor services;
  • AI and AmI-based Telehealthcare systems;
  • AI and AmI for the management and optimization of energy in domestic and commercial buildings;
  • Novel AI and AmI approaches to activity recognition in indoor environments;
  • AmI and AI-enabled smart working places and public spaces (parks, squares, beaches, gardens, etc.) applications;
  • Societal challenges in the adoption of AI and AmI-based technologies for smart society (ethical issues, privacy concerns, non-invasive approaches, stigma, willingness to adopt, accessibility issues);
  • The role of Human factors in the design and development of AmI environments;
  • Impact of the COVID-19 pandemic on the application of AmI and smart environments.

Dr. Alberto Trombetta
Dr. Daniele Spoladore
Dr. Andrea Zangiacomi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com 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. Applied Sciences 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 2400 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.

Keywords

  • smart workplaces
  • smart home
  • AmI environments
  • applied AI
  • digitalization

Published Papers (1 paper)

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Research

15 pages, 10436 KiB  
Article
Performance Analysis of Deep Convolutional Network Architectures for Classification of Over-Volume Vehicles
by S. Sofana Reka, Venkata Dhanvanthar Murthy Voona, Puvvada Venkata Sai Nithish, Dornadula Sai Paavan Kumar, Prakash Venugopal and Visvanathan Ravi
Appl. Sci. 2023, 13(4), 2549; https://doi.org/10.3390/app13042549 - 16 Feb 2023
Viewed by 1656
Abstract
The number of vehicle accidents has increased in recent years due to overloaded goods carriers. Off-road driving, mountain roads, and sharp edges on a road are the main causes of an imbalance in overloaded trucks. In rural areas, where smaller roads cannot accommodate [...] Read more.
The number of vehicle accidents has increased in recent years due to overloaded goods carriers. Off-road driving, mountain roads, and sharp edges on a road are the main causes of an imbalance in overloaded trucks. In rural areas, where smaller roads cannot accommodate high volume vehicles, such vehicles cause many problems for cars, bikes, bicycles, and other small vehicles, as well as an increase in traffic congestion in those areas. This has become a major problem in the daily lives of drivers in rural areas as well as major urban areas. Solutions are needed to detect over-volume goods carriers and alert drivers to slow down or control the volume in their trucks. This work mainly focuses on a solution that uses deep CNN models. In this work, different deep convolutional architectures are evaluated for their ability to classify goods based on their volume. The model implemented is based on a dataset-specific transfer learning process with CNN layers generated in ImageNet in which only dense layers are learned. The primary objective of this work is to identify a classification method that exhibits proven results with respect to the accuracy parameters. In this work, different deep architectures were tested, and among the efficient networks, Net-B3 was found to perform with 95% accuracy on average. The different architectures were evaluated based on their accuracy, confusion matrix, ROC curve, and AUC score with a real-time dataset. Full article
(This article belongs to the Special Issue Advances and Applications in Ambient Intelligence and Smart Environments)
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