Applied Artificial Intelligence for Sustainability

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 2515

Special Issue Editors


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Guest Editor
Department of Artificial Intelligence, Sejong University, Seoul, Republic of Korea
Interests: industrial AI; information systems; IoT; big data; health informatics
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Guest Editor
Department of Electrical Engineering and Informatics, Vocational College, Universitas Gadjah Mada, Yogyakarta, Indonesia
Interests: machine learning; artificial intelligence; information system; IoT; health informatics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Data Science, Sejong University, Seoul, Republic of Korea
Interests: data mining and analysis; machine learning; image processing; artificial intelligence; health informatics
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Guest Editor
UBD School of Business and Economics, Univesiti Brunei Darussalam, Bandar Seri Begawan BE 1410, Brunei
Interests: business information systems; knowledge management systems; digital business & digital humanities; big data in business; ICT & area studies (ASEAN/Borneo); ICT in education; e-health & mobile health
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

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.

Keywords

  • 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

Published Papers (1 paper)

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Research

28 pages, 4156 KiB  
Article
Heterogeneous Traffic Condition Dataset Collection for Creating Road Capacity Value
by Surya Michrandi Nasution, Emir Husni, Kuspriyanto Kuspriyanto and Rahadian Yusuf
Big Data Cogn. Comput. 2023, 7(1), 40; https://doi.org/10.3390/bdcc7010040 - 22 Feb 2023
Cited by 1 | Viewed by 2009
Abstract
Indonesia has the third highest number of motorcycles, which means the traffic flow in Indonesia is heterogeneous. Traffic flow can specify its condition, whether it is a free flow or very heavy traffic. Traffic condition is the most important criterion used to find [...] Read more.
Indonesia has the third highest number of motorcycles, which means the traffic flow in Indonesia is heterogeneous. Traffic flow can specify its condition, whether it is a free flow or very heavy traffic. Traffic condition is the most important criterion used to find the best route from an origin to a destination. This paper collects the traffic condition for several road segments which are calculated based on the degree of saturation by using two methods, namely, (1) by counting the number of vehicles using object detection in the public closed-circuit television (CCTV) stream, and (2) by requesting the traffic information (vehicle’s speed) using TomTom. Both methods deliver the saturation degree and calculate the traffic condition for each road segment. Based on the experiments, the average error rate obtained by counting the number of vehicles on Pramuka–Cihapit and Trunojoyo was 0–2 cars, 2–3 motorcycles, and 0–1 for others. Meanwhile, the average error on Merdeka-Aceh Intersection reached 6 cars, 11 motorcycles, and 1 for other vehicles. The average speed calculation for the left side of the road is more accurate than the right side, and the average speed on the left side is less than 3.3 km/h. Meanwhile, on the right side, the differences between actual and calculated vehicle speeds are between 11.088 and 22.222 km/h. This high error rate is caused by (1) the low resolution of the public CCTV, (2) some obstacles interfering with the view of CCTV, (3) the misdetection of the type of vehicles, and by (4) the vehicles moving too fast. The collected dataset can be used in further studies to solve the congestion problem, especially in Indonesia. Full article
(This article belongs to the Special Issue Applied Artificial Intelligence for Sustainability)
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