Applied Artificial Intelligence for Sustainability

Dear Colleagues,

Modern civilization is surrounded by a technologically networked environment. Many of the applications created for this digital ecosystem employ advanced artificial intelligence techniques to solve a variety of problems: ranging from improved search engines to advanced facial recognition features on the web; from shape recognition algorithms for image processing to pattern recognition methods for social networks and economic studies; and from complex behavioral engines for synthetic characters in computer-generated images in movies and video games to advanced routing algorithms. Artificial intelligence has the potential to transform the world in the future decades, from corporate to domestic uses.

It is predicted that AI will contribute more to the global economy than China and India combined. It is also expected that, within the next 10 years, practically every successful industry or corporation would employ some form of artificial intelligence to ensure that their operations run smoothly and efficiently.

This Special Issue aims to disseminate the most recent artificial intelligence research results and breakthroughs, with a particular emphasis on their practical applications in science, engineering, industry, medical, robotics, manufacturing, entertainment, optimization, business, and other sectors. Researchers and practitioners are invited to submit high-quality original research or review articles on these subjects for consideration in this Special Issue.

The topics of interest for this Special Issue include, but are not limited to, novel applications of:

• Internet of Things (IoT) and Cyber-Physical Systems (CPS);
• Intelligent Transportation Systems (ITS) and smart vehicles;
• Analyzing big data and interpreting complex networks;
• Deep learning and real-world applications;
• Neural networks, fuzzy systems, and neuro-fuzzy systems;
• Architectures, methods, and approaches for distributed AI systems;
• Decision-support systems, including evolutionary algorithms, swarm intelligence, nature and biologically inspired meta-heuristics, and so on;
• Knowledge representation, expert systems, and knowledge processing;
• Image processing, pattern recognition, and speech recognition;
• Detection, analysis, diagnostics, and monitoring of intelligent faults;
• Practical applications with the aforementioned approaches in the industry, such as case studies or benchmarking.

You may choose our Joint Special Issue in Sustainability.

Dr. Muhammad Syafrudin
Dr. Ganjar Alfian
Dr. Norma Latif Fitriyani
Dr. Muhammad Anshari
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. Big Data and Cognitive Computing is an international peer-reviewed open access monthly 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 1800 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.

• Internet of Things (IoT)
• Cyber-Physical Systems (CPS)
• Intelligent Transportation Systems (ITS) and smart vehicles
• analyzing big data and interpreting complex networks
• deep learning and real-world applications
• neural networks, fuzzy systems, and neuro-fuzzy systems
• architectures, methods, and approaches for distributed ai systems
• decision-support systems, including evolutionary algorithms, swarm intelligence, nature and biologically inspired meta-heuristics
• knowledge representation, expert systems, and knowledge processing
• image processing, pattern recognition, and speech recognition
• detection, analysis, diagnostics, and monitoring of intelligent faults