The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) has ushered in a new era of possibilities, allowing for the emergence of predictive, prescriptive, and autonomous systems. This transformative synergy reshapes applications from mere assistance to full-fledged autonomous intelligence across diverse manufacturing, healthcare, and beyond sectors. IoT sensors gather valuable data at its core, while AI leverages this data to craft more intelligent and adaptive applications. In the contemporary landscape of smart devices, sophisticated systems, and advanced analytics, this powerful union confronts Quality of Service (QoS), privacy, security, and scalability challenges. We solicit original contributions that introduce fresh perspectives on novel architectures, innovative algorithms, and groundbreaking applications within the domain of AI-powered IoT that can overcome these challenges.
Topics of Interest:
We invite original (un-published) research contributions based on theabove mentioned theme including following topics:
- AI for data analysis, and decision-making in IoT
- Optimization and streamlining of IoT processes using Deep learning and AI
- Role of Deep learning in automation and predictive maintenance
- Role of AI in secure data transmission
- AI driven attack detection and recovery
- Lightweight machine learning models for constraint devices in IoT
- Edge AI for IoT networks
- Federated learning for AI-powered IoT systems
- Meta-heuristic algorithms for IoT
- Fuzzy based decision making for IoT security
- Soft computing for IoT data accumulation, mobility, Interoperability, and security.
Details of Session Chair and Co-Chair:
Dr. Rashmi Sahay, Assistant Professor, Dept. of Computer Science and Engineering, IcfaiTech (Faculty of Science and Technology) The Icfai Foundation of Higher Education, Hyderabad, India, Email: rashmi.sahay@ifheindia.org
Dr. Rajesh Shrivastava, Assistant Professor, IEEE Senior Member, Department of Computer Science and Engineering, Bennett University, Greater Noida, UP, India, Email- rajesh.shrivastava@bennett.edu.in
Dr. Sanket Mishra is an Assistant Professor,School of Computer Science and Engineering (SCOPE) at VITAP University, Amaravati, AP, India, Email: sanket.mishra@vitap.ac.in
Aims & Scope (Theme of Session):
In digital world, numerous technologies have been rapidly emerged up. With the emergence of these technologies, huge data started travelling on the Internet in a continuous fashion. The data that is travelling on the Internet comprises of confidential information like transactions handling in the banks in online mode, or this data comprises of non-confidential information like fetching of temperature on hourly basis. This movement of data along with source/destination energy consumes a lot more energy, that needs to be optimized. To handle this data and energy, and to perform data analysis at a faster rate on the Internet, emerging paradigms like Artificial Intelligence, deep learning, and many emerging technologies and Renewable Energy needs to be considered. Artificial Intelligence is a branch of computer science where the devices are embedded with intelligent algorithms and are made smart to formulate smart devices. Energy is a major constraint with such devices as these devices works 24x7 days with the Internet. How to reduce energy is the main question with such devices. As a result, energy optimization can be considered using Artificial Intelligence and deep learning approaches. Use of such a combination will lead to the growth of Smart Networks, which is atmost desired in present times of Smarter technologies. Everywhere we are hearing about Smart City, Smart Homes, Smart Transport System and many others, but to attain these, mechanisms of renewable energy and artificial intelligence approaches, covering machine learning and deep learning approaches are atmost desired. Many different solutions in artificial intelligence and renewable energy enabled smart networks have been proposed to address the issues and challenges in emerging technologies and to overcome the battle of networks, optimization in distributed environments, distributed learning and other aspects using numerous technologies. However, they are not properly designed to address the emerging needs of the society. Many service parameters are yet remain uncovered, that needs to be focused for enhancement of quality of service like secure data migration and their issues, intelligent cybersecurity systems to manage emerging technologies, security issues arising during resource allocation and resource scheduling, challenges related to security in manufacturing product designs, authentication and authorization issues in accessing products and services, minimization of energy efficiency and reduction of computational costs. Therefore, use of artificial intelligence and renewable energy enabled smart networks for emerging technologies is the key factor especially for emerging factories in the world of “smart” and “intelligent” devices. We solicit original contributions on novel artificial intelligence and renewable energy enabled smart networks, enhancing challenges related to smart networks, use of artificial intelligence and renewable energy, and applications of AAI-based technology for effective data transmission and secure data transfer in emerging technologies. We also seek contributions motivated by taking real-world society and deployment problems and theoretical works that have clear intention for practical applications towards artificial intelligence and renewable energy enabled smart networks. To meet the requirements of emerging technologies, artificial intelligence and renewable energy enabled smart networks should be an efficient and safe way-out to pursue with optimized and enhanced data transmission over the network.
Sub Topics:
Topics include but are not limited to:
- Artificial intelligence and renewable energy enabled smart networks for fault tolerance abilities
- Intelligent theoretical and mathematical models for energy optimization
- Data Analytics: Tools and Techniques.
- Learning from energy patterns using Internet of Things (IoT) and Blockchain
- Futuristic technologies based on artificial intelligence and renewable energy enabled smart networks for emerging technologies
- Intelligent decision-making and visual semantic analytics
- Secure energy efficient data transmission in Artificial Intelligence
- IoT-based energy minimization solutions for artificial intelligence based smart systems
- Deep Learning towards smart computing systems
- Preventative Measures using artificial intelligence based smart systems
- Artificial intelligence and renewable energy enabled smart networks for mobiles
- Modelling and control of artificial intelligence and renewable energy enabled smart networks using emerging technologies
- Artificial intelligence and renewable energy approaches for data analytics of computational intelligent systems
Details of Session Chair and Co-Chair:
Dr. Simar Preet Singh, Bennett University, Greater Noida, India
Email: dr.simarpreetsingh@gmail.com
Dr. Divya Singh, Bennett University, Greater Noida, India
Email: divya.singh@bennett.edu.in
Dr. Gagandeep, Chandigarh Engineering College-CGC, Landran, Mohali, India
Email: gaganpec@yahoo.com
Dr. Hemant Petwal, University of Petroleum and Energy Studies, Bidholi, Dehradun, India
Email: hemant.petwal@ddn.upes.ac.in
Dr. Wakar Ahmad, Indian Institute of Information Technology, Sonepat, India
Email: w.ahmad@iiitsonepat.ac.in
Aims & Scope (Theme of Session):
The conference covers a diverse set of research in cross-disciplinary themes. Its applications range from computer vision, image processing, artificial intelligence, and machine learning to Data Science and Big Data analytics. The text provides an in-depth, multidisciplinary discussion of recent advancements and state-of-the-art methods in the spectrum of disciplines. The publication is ideally designed for academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in these fields. It also features explanatory, illustrations of Algorithms, architecture, applications, software systems, and data analytics in the scope of a specified domain.
Sub Topics:
Following is the list of sub-topics suitable for this special conference:
- Artificial intelligence and renewable energy approaches for data analytics of computational intelligent systems
- Deep Learning towards smart computing systems
- Artificial intelligence technologies like machine learning in Health care.
- Data Science and its application business.
- Federated learning for AI-powered IoT systems
- Artificial intelligence technologies like Deep Learning in Agriculture.
- AI-enabled monitoring systems
Details of Session Chair and Co-Chair:
Dr. Mahesh Kumar Singh, Associate Professor, Department of Computer Science Engineering, Dronacharya Group of Institutions, Gr. Noida, UP.
Email: maheshkrsg@gmail.com
Dr. Pushpendra Singh, Associate Professor, Department of Computer Science and Engineering, SRMIST, Ghaziabad, U.P.
Email: pushpendra.singh1@gmail.com
Dr. Pushpa Choudhary, Professor, Department of Computer Science and Engineering, Galgotias University, Gr Noida
Email: pushpak2728@gmail.com
Dr. Arun Kumar Singh, Professor, Department of Computer and Engineering, Greater Noida Institute of Technology, Gr Noida
Email: arun.k.singh.iiit@gmail.com
Aims & Scope (Theme of Session):
Edge-Cloud Computing is an emerging distributed paradigm to implement edge offloading, in which complex tasks are migrated from IoT devices to edge-cloud servers. Edge-Cloud Computing is a novel concept focused on the core problem of energy management in the whole architecture, that is closely related to task dispatch, resource scheduling, network communication and so on. It is obvious that Edge-Cloud Computing holds great promise in energy-sensitive domains, such as smart grid, Internet of vehicles, healthcare. With the great development of intelligent algorithms, explainable AI is a powerful analysis technology that is well applied to dealing with the energy management in Edge-Cloud Computing. It is efficient to utilize deep learning to implement the task allocation of edge servers and reduce the energy consumption of the whole system.
The aim of this workshop is to provide a platform for industrial practitioners and academic researchers to think beyond the boundaries to submit the new developments related to Edge AI for distributed systems and networks. Moreover, our focus is intended to discuss the near-term and long-term confluence of the Edge AI and Distributed Systems and Networks.
Sub Topics:
Technical scope of this special issue includes, but is not limited to:
- Design of explainable AI-based energy-efficient architecture in Edge Computing
- Explainable AI algorithms in Edge Computing
- Explainable AI-based applications of Edge Computing in energy management
- Explainable AI for energy management in Edge-Cloud Computing
- Deployment of federated learning in Edge Computing
- Explainable AI-based task Scheduling in Edge Computing
- Explainable and interpretable edge AI
- Resource management for federated learning in Edge-Cloud Computing
- Security and privacy in Edge Computing
- Intelligent task and resource management on the edge.
- Energy optimization of federated learning in Edge-Cloud Computing
Details of Session Chair and Co-Chair:
Dr. Ishan Budhiraja, Assistant Professor, Department of Computer Science Engineering & Technology, Bennett University, Greater Noida, India.
Email: ishan.budhiraja@bennett.edu.in
Dr. Rajat Chaudhary, Assistant Professor, Department of Computer Science Engineering & Technology, Bennett University, Greater Noida, India.
Email: rajat.chaudhary@bennett.edu.in
Aims & Scope (Theme of Session):
The research presented at this Special Session will be diverse and address cross-disciplinary topics. Data Science and Big Data analytics are just a couple of its many applications, which also include computer vision, image processing, artificial intelligence, and machine learning. The volume offers a thorough, comprehensive overview of contemporary developments and cutting-edge techniques across a range of fields. The publication is perfectly suited for academics, technological experts, students, and researchers looking to learn about the most recent advancements in these sectors.
Sub Topics:
Technical scope of this special issue includes, but is not limited to:
- Artificial Intelligence strategies to analyze data within computational intelligent systems.
- Exploring the role of Deep Learning in advancing intelligent computing systems, Healthcare, Agriculture
- Applying Data Science to enhance business operations.
- Explainable AI for energy management in Edge-Cloud Computing
- Utilization of artificial intelligence (AI) in conjunction with renewable energy sources to facilitate the development and operation of intelligent networks optimized for mobile communication.
- Significant Contributions of Artificial Intelligence (AI) in Ensuring the Confidentiality and Reliability of Data During the Process of Secure Data Transmission
- Explainable and interpretable edge AI
- Artificial Intelligence (AI)-Powered Architectural Framework Geared Towards Achieving Optimal Energy Efficiency in the Realm of Edge Computing"
- Making use of collaborative learning for AI-enabled IoT devices.
- Distributed Learning Techniques in Internet of Things (IoT) Systems Empowered by Artificial Intelligence (AI)
- Implementing AI-enabled monitoring systems for enhanced surveillance and control.
Details of Session Chair and Co-Chair:
Dr. Pankaj Kumar Sharma, Professor, Department of Computer Science, ABES Engineering College, Ghaziabad, UP
Email: hodcs@abes.ac.in
Dr. Manu Singh, Associate Professor, Department of Computer Science, ABES Engineering College, Ghaziabad, U.P.
Email: manu.singh@abes.ac.in
Dr. Neha Gupta, Associate Professor, Department of Computer Science, ABES Engineering College, Ghaziabad, U.P.
Email: neha.gupta@abes.ac.in
Dr. Neha Gupta, Assistant Professor, Department of Computer Science, ABES Engineering College, Ghaziabad, U.P.
Email: sonia.verma@abes.ac.in