Journal Information
IT Professional (ITPRO)
https://www.computer.org/web/computingnow/itpro
Impact Factor:
3.700
Publisher:
IEEE
ISSN:
1520-9202
Viewed:
10442
Tracked:
1
Call For Papers
IT has emerged as an exciting, robust field unto itself, drawing on applications, data engineering, algorithms, system software, computer systems organization, and other contemporary computer technologies as applied to business problems. IT Pro publishes articles that cross all these fields, defining the synergistic partnerships and interactions among them. All articles are readable by IT specialists employed in various industries worldwide; i.e., IT Pro articles should overcome the barriers usually created by industry-oriented vocabularies. Articles on topics across the IT spectrum are encouraged.

A sampling of topics follows: Building the corporate networking; Information resources for strategic infrastructure competitive advantage; Business intelligence applications; Internet/lntranet design and organization; Case studies applications and security; Collaborative technology; IT training issues; Conversion of legacy data; IT management and leadership; Cooperative information systems; IT strategic planning; Data distribution from multiple databases; IT tools; Data warehousing/storage issues; Intellectual property and other legal issues; Data mining; Interoperability of UNIX and NT; Decision Support Systems (DSS); Online analytical processing (OLAP); Design engineering and implementation; Online transaction processing (OLTP) of complex computer systems; Opinion pieces and analyses of trends; Developing and maintaining databases facilitated by IT; Distributed databases; Project management and prioritization of complex organizations; Systems administration; Document management systems; Systems integration; Electronic commerce applications and systems; Use and application of IT standards; Executive Information Systems (EIS); Worknow automation and systems; Y2K.
Last updated by Dou Sun in 2021-07-25
Special Issues
Special Issue on Computational Advances for Industrial Transformation Towards Smart and Sustainable Society
Submission Date: 2024-05-08

Technological innovation is the bedrock of attempts to improve strategic sustainability goals, including resource and energy efficiency. Industrialization would be impossible without technological advancement. Early acquirers of integrated and interdependent innovations in the manufacturing industries are reaping the economic advantages of increased efficiency improvements, economic output, protection, cost reductions, revenue growth, and client satisfaction and retention as they work toward Industrial Transformation for Sustainability. Among all technological advances are those associated with the Industrial Transformation for Sustainability movement, including Artificial Intelligence, deep learning, business intelligence, Internet of Things (IoT) communication, and blockchain technology. To identify a few, industrial production, power generation, utility services, automobile industries, and aerospace businesses have benefited from investment opportunities in such ground-breaking technologies. Additionally, global warming requiring additional transition to low-carbon communities necessitates a sea difference in how emerging markets and industries operate. With regards to intelligent urban as methodologies for Industrial Transformation toward a Smart and Sustainable Society, experimental computational intelligence has been increasingly comprehended. Carbon-intensive processes that underlie the world economy could help influence a much more sustainable future across innovation, predictive analysis, computerization, electricity generation, and operational efficiencies. Despite the numerous benefits of integrating computational intelligence methodologies into numerous Industrial Transformation for Sustainability initiatives, the effective implementation of the AI model presents numerous difficulties, including information amount and complexity, interoperability, and the precision of qualitative findings from the gathered information. Technological improvements through AI-enabled techniques, such as enhanced pattern recognition and natural language processing, have opened up numerous new research directions for evaluating the computational intelligence conceptual model by observing factual data and sensed information. Additionally, advances in computational competence methodologies like decentralized and federated learning should be used to empower the multiple edge devices and generate an optimization method under the supervision of a vital network edge. In recent years, academics and practitioners have seen significant interest in innovative computational intelligence technologies for Industrial Transformation for Sustainability. Besides that, industry 4.0 was indeed reshaping how businesses manufacture, enhance, and distribute their consumer goods. Likewise, industrial automation integration of advanced sensing devices, integrated development environment, and robotic systems that collect information and enable more informed decision-making is critical in achieving Industrial Transformation toward a Smart and Sustainable Society. These digital technologies enable enhanced automation, preventative analysis, self-optimization of operational efficiencies, and, most importantly, a previously unattainable threshold of responsiveness and efficiency to customers. Topics of interest include, but are not limited to: - Advanced computational using green communication for Industrial Transformation toward a Smart and Sustainable Society - Green edge platform using caching techniques for Industrial Transformation towards Smart and Sustainable Society - Low latency and ultra-reliable communication protocol for Industrial Transformation towards Smart and Sustainable Society - Collaborative computational intelligence using ML/DL models for Industrial Transformation - AI-enabled Federated/distributed learning for Industrial Transformation - Enhanced computational intelligence progression in Industry 4.0 for Industrial Transformation towards Smart and Sustainable Society - Blockchain-based computational intelligence for Industrial Transformation towards Smart and Sustainable Society - Progress in Digital twin for Industrial Transformation towards Smart and Sustainable Society - Green computing for energy-aware data centers for Industrial Transformation - Deep learning for acquiring advanced computational intelligence for studying sustainability challenges
Last updated by Dou Sun in 2023-09-02
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