International Journal of Data Science and Analytics - CfP: Innovative Hardware and Architectures for Ubiquitous Data Science

Artificial intelligence (AI) may be used via activities relating to human intellect and gadget efficiency in applying diverse principles. The increased 5G wireless communication ensures that a device-to-internet link is always accessible, improving data collection and processing between devices. Moreover, ubiquitous computing is based on connecting gadgets to the internet, which simplifies data processing while increasing efficiency.  Due to the device's continuous connection, it will be accessible at all times of request. Thus, ubiquitous systems might be used to monitor and analyse data in various mission-critical applications. Further, ubiquitous systems are frequently used in healthcare, education, commerce, military applications, smart industries or Industrial Internet of Things, and intelligent geographical analysis.  Moreover, with ubiquitous systems, location-based services are feasible, which enable efficient location identification via data collecting.

One of the critical aspects of the widespread adoption of data science is the availability of low-cost processors for data mining and analysis. Since they focus on wearable devices, they can provide real-time features connected to many connections via ubiquitous data science.  With increased features associated with wireless device convergence and current technological advancements, ubiquitous hardware and architecture innovations must be considered.

Moreover, the hardware utilised in ubiquitous systems must be capable of decision-making, high-speed processing, information convergence, sociability, reduced visual clutter, and goal-oriented design. The objective of effective data analysis may be accomplished via the combination of fuzzy model approaches, effective artificial neural networks, reinforcement learning models ,  convolutional neural networks, and deep learning models.   Data marts may be used to improve the design of ubiquitous systems. Specifically, data marts offer an enhanced mechanism for accessing server-side data updated frequently. Additionally, the data mart incorporates the capability that has been introduced to the location-based business analysis data depending on the geographic location of the device and collected data. Indeed, data marts might be used in conjunction with data visualisation approaches, depending on the data management requirements. The data visualisation allows interfaces for data sources irrespective of the type of data format and geographical locations. 

This special issue explores the concept of ubiquitous data science and the associated applications, technology, and architectural deployments. Given that pervasive systems or ubiquitous data management systems are responsible for collecting enormous amounts of data from a variety of sources, the architecture and technology must have enough processing capabilities.

LIST OF TOPICS AREAS INCLUDE, BUT ARE NOT LIMITED TO:

• Deployment of wearable health monitoring systems with enhanced ubiquitous system architectures
• Syntactic pattern recognition with real-time image monitoring with effective hardware and architecture related to ubiquitous systems
• Continual coverage of space-air- ground communication with the integration of ubiquitous computing 
• Ubiquitous system architecture related to the integration of cyber-twin systems
• Ubiquitous system deployment architecture related to the knowledge transfer applications
• Applications based on meta-learning supported by ubiquitous architecture and hardware
• Effective ubiquitous architecture related to socialisation and decision-making capabilities
• Optimised data mart architecture for ubiquitous system deployment with less visual clutter
• Multiple fusion and multimodal image analysis architecture and hardware design for building ubiquitous systems
• Heterogenous networking and blockchain applications related to ubiquitous hardware deployment

Guest Editors:

Dr. Faheem Khan, Gachon University, Seongnam, South Korea

Dr. Umme Laila. Sir Syed University of Engineering & Technology, Karachi, Pakistan

Dr. Muhammad Adnan Khan, Riphah International University, Pakistan

Important Dates:
Submission Deadline: 10^th September, 2023
Author Notification: 20^th December, 2023
Revision and Resubmission Deadline: 25^th February, 2024
Paper Acceptance: 05^th May, 2024