Special Issue on Recent Advances in Sensors and Machine Vision for Automated Systems
Automated systems are one of the most promising and exciting technologies that have emerged gradually in recent years, potentially disrupting various sectors. From a practical perspective, these systems have acquired plenty of hype recently, with a huge impact on our everyday lives. Sensors and machine vision play a central role among the many technologies that form an integral part of automated systems. Sensors help automated systems collect, store, and monitor data. While machine vision enhances the integrated capabilities of automated systems, they assist in solving real-world problems. When combined with machine vision and intelligence, smart sensors typically change the way they collect data and communicate information. It helps determine the extrinsic properties of the external objects such as position, distance, and proximity measures through which they carry out the complex decision making in real-time.
Indeed, many researchers are working actively to simplify the complex activities on the measured data locally within a sensor module of the automated systems. They face several challenges when it comes to the fusion of sensing and signal processing features of autonomous applications, which significantly redefines its landscape. Further, there is a wide array of hardware and software associated with the sensor configuration, resulting in millions of possible pitfalls in an automated environment. Even a small change in the sensor configuration will create a negative impact on the entire system. Due to this reason, artificial intelligence algorithms such as neural networks face numerous challenges when making real-time interpretations. For instance, any change to the sensitivity of the automated application can alter the final output. In addition to this, multiple facets need to be addressed while moving towards increased adoption of automated systems, especially with critical environments. Hence, finding the advancements in smart sensor technologies and intelligent machine vision techniques will significantly transfer the potential of automated systems to the next level. Further, if these two techniques are applied sensibly to automated systems, it will tremendously enhance the functionalities of the automated systems with numerous applications. Hence, to explore more in this regard, we welcome researchers and practitioners to present their novel and innovative research contributions.
Topics included, but are not limited to:
- Trends in artificial intelligence for enhancing machine vision across the automated systems
- Advances in smart sensors and machine intelligence for automated systems
- Sensor data fusion and integration with machine vision for decision making in autonomous systems
- Deep learning and computer vision for automated systems
- Role sensors and machine vision autonomous vehicle/ robot navigation
- Efficient sensors to deal with increased sensitivity measures in low-light environments associated with automated systems
- Novel image sensing modalities and its application in autonomous systems
- Advances in vision based sensory schemes for autonomous systems
- Application of advanced sensors and machine vision technologies for industrial automated systems and manufacturing
- Innovations in image and signal processing in sensor for machine vision in autonomous systems
- Sensors and machine vision for 3D reconstruction of images.
For more information, please contact the Guest Editors:
Dr. Deevi Radha Rani, (Lead Guest Editor)
Vignan's Foundation for Science, Technology & Research (Deemed to be University), India
Email: drr_cse@vignan.ac.in
Dr. A. Shanthini,
SRM Institute of Science and Technology, India
Email: shanthia@srmist.edu.in
Dr. Elena Verdu,
Universidad Internacional de la Rioja, Spain
Email: elena.verdu@unir.net
Deadline to submit manuscripts for consideration: October 31, 2023
Please submit your article at https://www.editorialmanager.com/saeconnautomveh and include a submission note in Editorial Manager to indicate that it is for this special issue.