Special Issue "Sensors with Machine Learning Methods for Assisted Systems - Recent Advances and Future Trends"
Deadline for manuscript submissions: closed (30 July 2021) | Viewed by 10899
Interests: sensors; pattern recognition; artificial intelligence; machine learning; big data; assisted system; robotics; healthcare; image processing; computer vision
Interests: sensors; data integration; artificial intelligence; big data; semantic web; human computer interaction
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Special Issue in Multimodal Technologies and Interaction: Interactive Web
In this era of artificial intelligence (AI) and big data, the approaches for data analysis, information extraction, and underlying event analysis with state-of-the-art machine learning algorithms have grown radically. Hence, there is an increasing demand for solutions that can successfully handle enormous data from lots of sensors and model the events in data. Assisted systems incorporate systems, applications, and services adopting sensors, measurement methods, and information technologies to offer new products and solutions to address various necessities, such as health and wellbeing. The expected outcomes from the introduction of such a paradigm include a positive impact on health-related quality of life, reducing the costs of healthcare provision at the same time.
Despite the marvelous advancements and achievements of artificial intelligence fields so far, their black-box nature and questions around the lack of transparency are still hampering their applications in society. To trust, accept, and adopt emerging AI solutions in our lives and practices, explainable AI (XAI) is in very much demand these days, along with state-of-the-art machine learning algorithms such as convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory (LSTM), neural structured learning (NSL), etc. XAI can provide human-understandable interpretations by explaining the machine learning model’s algorithmic behavior and outcomes. Thus, it can enable people to control and continuously improve the performance, transparency, and explainability throughout the lifecycle of AI applications. Considering this motivation, the recently emerging trend among the diverse and multidisciplinary research communities is exploration of AI approaches and the development of contextual models.
This Special Issue highlights the recent advances and future trends in developing intelligent and smart wearable and/or ambient sensor-based systems, methods, and frameworks to measure the wellbeing of people. It also focuses on machine learning approaches to model the underlying events in the data. Algorithms related to XAI would be quite interesting and encouraging in this regard, along with other machine learning algorithms to handle distinguished sensor data for assisted systems. We invite manuscripts on a wide range of smart sensing and machine learning research for assisted systems, including but not limited to:
- Artificial intelligence;
- Explainable AI models;
- Human–computer interactions;
- Robotics for healthcare;
- Signal processing;
- Multimodal sensing;
- Feature analysis;
- Context-based sensing;
- Knowledge discovery from sensor data;
- Machine learning on sensor data;
- Data analysis for smart sensing;
- Sensor data applications;
- Pattern recognition;
- Smart-assisted system;
- Expert systems and applications.
Dr. Md Zia Uddin
Dr. Ahmet Soylu
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. Sensors 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.
- Artificial intelligence
- Assisted system
- Machine learning
- Explainable AI