Special Issue "Advances in System Design Automation Using Artificial Intelligence"
Deadline for manuscript submissions: 30 June 2024 | Viewed by 8985
Interests: FPGA; CAD; EDA; reconfigurable architectures; routing; machine learning
Interests: communication systems; wireless sensor networks; optimization models; Internet of Things
Interests: Internet of Things; network security; cloud computing; network function virtualization; wireless networks; 5G
Special Issues, Collections and Topics in MDPI journals
Special Issue in Telecom: Recent Advances in Smart and Pervasive Internet of Things
Special Issue in Photonics: Optical Machine Learning for Communication and Networking
Special Issue in Sensors: Advance Tools and Techniques for Edge Computing in Dynamic Internet of Things Environment
System design automation in general, and in electronic design automation in particular, has seen rapid growth over the past few years. It has made the systems ever more capable and powerful. The growth in the popularity of electronic systems is the result of multiple factors, such as shrinking processing technology, improved design processes, better tools, efficient protocols, and ever-improving system optimization models, to name a few. The improved systems have changed human perception about their lives. For example, current handheld devices have more computation power than the supercomputers of a few decades ago. The enormous growth in the popularity and capability of electronic systems has come at the cost of ever-increasing complexity in the design process of these systems. Regarding the state-of-the-art, the complexity of electronic systems is increasing at a rate of 58% per year, whereas the capability of engineers who design those systems is only increasing by 28% per year. Researchers are exploring various avenues where the design of newer and more efficient systems can keep pace with their complexity.
In this regard, we propose a Special Issue on ‘Advances in System Design Automation using Artificial Intelligence’. Lately, artificial intelligence algorithms been applied in almost every aspect of efficient and optimized problem solving. Through this Special Issue, we invite researchers to address the issue of complex system design automation through artificial intelligence algorithms. This Special Issue is particularly interested in research works that provide evidence of optimized system design through artificial intelligence, be it electronic, communication, digital, control systems, etc.
This Special Issue aims to cover the advances in system design automation using various artificial intelligence algorithms and techniques. Topics of interest include, but are not limited to:
- Efficient embedded system design;
- Optimized system design automation;
- Efficient electronic design automation;
- Artificial intelligence algorithms for system optimization;
- Machine learning algorithms/techniques for efficient systems;
- Deep learning techniques/algorithms for optimized systems;
- Internet of Things and artificial intelligence;
- Efficient computer-aided design tools;
- Communication system optimization;
- Optimized system models;
- Control system optimization using artificial intelligence/machine learning/deep learning;
- Big data handling through artificial intelligence.
Dr. Umer Farooq
Dr. Najam Hasan
Dr. Ali Kashif Bashir
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. Electronics 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 2200 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.
- system design automation
- electronic design automation
- artificial intelligence
- machine learning
- deep learning
- Internet of Things
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Leveraging Swarm Intelligence for Optimal Thermal Camera and Sensor Placement in Industrial Environments
Authors: Hubert Zarzycki; Dawid Ewald; Piotr Prokopowicz
Affiliation: Faculty of Computer Science, Kazimierz Wielki Univesrity in Bydgoszcz, Poland (e-mail:
Abstract: The strategic placement of thermal cameras and sensors in industrial spaces plays a pivotal role in enhancing process monitoring, safety, and resource optimization. In this research, we harness the potential of a nature-inspired Swarm Intelligence algorithm to address the intricate challenge of sensor placement in industrial settings. Drawing inspiration from collective behaviors in nature, this algorithm has demonstrated its efficacy in solving optimization problems. This study delves into its application for optimizing thermal camera and sensor locations, with a focus on maximizing coverage while minimizing redundancy in the production hull, ultimately leading to enhanced operational efficiency and safety.