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1st International Conference
on
Nature-Inspired AI Techniques for Industry 4.0 (ICNAI) - 2024
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About the Conference

The International Conference on Nature-Inspired AI Techniques for Industry 4.0 is a premier event bringing together innovators, researchers, and industry leaders to explore AI methodologies inspired by natural systems. The conference will showcase cutting-edge research on evolutionary algorithms, swarm intelligence, neural networks, and other nature-inspired AI techniques, highlighting their transformative applications in Industry 4.0. Attendees will gain insights from expert keynote speakers and engage in in-depth discussions on the ethical, social, and economic impacts of AI. The event also provides knowledge on implementing these AI techniques in manufacturing, supply chain management, robotics, and smart systems. Networking opportunities will allow participants to connect with professionals from academia and industry, fostering collaboration and the exchange of ideas. Join us to discover how nature-inspired AI is revolutionizing modern industries and shaping the future of Industry 4.0. All Selected papers from the conference will be published in the Scopus-indexed Springer book series.

About the Institute

Mahatma Gandhi Institute of Technology (MGIT), established by the Chaitanya Bharathi Educational Society (CBES) in 1997, is a premier engineering institution in Telangana, affiliated with JNTU, Hyderabad. MGIT offers eleven undergraduate and five postgraduate programs, all of which are accredited by the National Board of Accreditation (NBA) and NAAC with an A++ grade and recognized by UGC. The institute is renowned for its excellent academic track record, distinguished faculty with 91 Ph.D. holders, and a lush 30-acre campus at Gandipet, Hyderabad. MGIT has consistently been ranked among the top engineering colleges, with notable rankings by MHRD's NIRF, CSR-GHRDC, and The Week Magazine. The institute excels in providing industry-compliant education and has a robust placement cell, ensuring high placement rates. MGIT fosters a vibrant academic environment, enriched with state-of-the-art infrastructure, extensive research projects, and dynamic co-curricular activities, making it a sought-after destination for engineering aspirants.

College Building
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About the Department

The Department of Information Technology at MGIT was established in 1997 with an annual intake of 60 students. It has 19 qualified faculty members, including Two professors, Two associate professor, and fifteen assistant professors, supported by experienced non-teaching staff. Currently, the department has Five Ph.D. holders and nine faculty members pursuing their Ph.D.
The department boasts well-equipped independent laboratories, providing facilities for students to learn emerging technologies such as Data Analytics, Data Mining, IoT, AI, Machine Learning, and Open-Source Technologies. Faculty members are engaged in AICTE-sanctioned research projects. Students participate in various clubs and professional chapters like ASME, ISTE, IEEE, and the Innovation Club, showcasing their skills through product development and organizing workshops, seminars, and conferences. Our graduates are highly sought after by employers due to our hands-on curriculum, excellent labs, and strong industry connections.

Conference Tracks

Nature-Inspired Optimization Algorithms for Industrial Applications

Includes:

  • Genetic Algorithms
  • Particle Swarm Optimization
  • Ant Colony Optimization
  • Bee Colony Optimization
Swarm Intelligence in Manufacturing and Supply Chain Management

Includes:

  • Applications of swarm intelligence in logistics
  • Optimization of manufacturing processes
  • Resource allocation and scheduling
Bio-Inspired Robotics and Automation

Includes:

  • Autonomous robots inspired by biological systems
  • Adaptive and flexible automation systems
  • Bio-mimetic designs in robotics
Evolutionary Computing for Smart Manufacturing

Includes:

  • Adaptive and self-learning manufacturing systems
  • Evolutionary strategies for process optimization
  • Real-time adaptive control using evolutionary algorithms
Neural Networks and Deep Learning in Industrial Automation

Includes:

  • Convolutional Neural Networks for image-based inspection and quality control
  • Recurrent Neural Networks for predictive maintenance
  • Deep learning techniques for process optimization
Fuzzy Logic and Hybrid Systems for Decision-Making in Industry

Includes:

  • Fuzzy logic systems for process control
  • Integration of fuzzy logic with other AI techniques for enhanced decision-making
  • Hybrid AI systems combining fuzzy logic with evolutionary algorithms or neural networks
Artificial Immune Systems for Cybersecurity in Industrial IoT

Includes:

  • Anomaly detection and intrusion prevention
  • Immunological principles for network security
  • Resilient system designs inspired by biological immune systems
Nature-Inspired Algorithms for Big Data Analytics in Industry

Includes:

  • Handling and processing large-scale industrial data
  • Nature-inspired data mining techniques
  • Predictive analytics for the industry using bio-inspired algorithms
Self-Organizing Systems and Emergent Behavior in Smart Factories

Includes:

  • Self-organizing manufacturing systems
  • Emergent behaviors in industrial networks
  • Decentralized control systems inspired by natural systems
Energy Efficiency and Sustainable Industry Using Nature-Inspired AI

Includes:

  • Optimizing energy consumption with bio-inspired techniques
  • Sustainable manufacturing processes
  • Green logistics and supply chain management
Biologically Inspired Materials and Their Manufacturing Processes

Includes:

  • Development of new materials based on biological principles
  • Manufacturing techniques inspired by nature
  • Applications of bio-inspired materials in industry
Adaptive and Intelligent Systems for Industry 4.0

Includes:

  • Adaptive learning algorithms for smart manufacturing
  • Intelligent systems for dynamic environments
  • Implementation of adaptive AI in industrial processes
Case Studies and Industrial Applications of Nature-Inspired AI

Includes:

  • Real-world applications of nature-inspired techniques in industry
  • Success stories and lessons learned
  • Future trends and challenges in adopting nature-inspired AI in industry

Special Tracks

Medical

Bio-Inspired Algorithms in Healthcare

  • Evolutionary computation for medical diagnosis and treatment optimization.
  • Swarm intelligence for patient monitoring and management systems.
  • Nature-inspired models for drug discovery and development.

AI for Medical Imaging and Diagnostics

  • Application of neural networks and deep learning in radiology and pathology.
  • Nature-inspired approaches for image segmentation and pattern recognition in medical scans.
  • Enhancing diagnostic accuracy using bio-mimetic algorithms.

Bio-Inspired Algorithms in Medical Diagnostics

  • Application of genetic algorithms, neural networks, and swarm intelligence in medical imaging and diagnosis.

Optimization of Healthcare Systems

  • Enhancing hospital operations, patient management, and drug delivery systems using AI techniques inspired by natural processes.

AI for Personalized Medicine

  • Utilizing nature-inspired machine learning models to develop personalized treatment plans and predict patient outcomes.

Science and Humanities

Nature-Inspired Computing in Scientific Research

  • Application of genetic algorithms in physics and chemistry for problem-solving and simulations.
  • Bio-inspired optimization techniques in environmental science and ecology.
  • Quantum-inspired computational models for complex scientific problems.

Humanities and AI

  • Ethical implications of using nature-inspired AI in society.
  • Philosophical perspectives on AI and nature-inspired intelligence.
  • Cultural impacts and narratives surrounding AI in the humanities.

Ethical Implications of Nature-Inspired AI

  • Examining the ethical considerations and societal impacts of deploying AI systems modeled after natural processes.

Philosophical Perspectives on Nature and Technology

  • Exploring philosophical questions about the intersection of nature, AI, and human ingenuity.

Cultural Influences on AI Development

  • Investigating how different cultural perspectives influence the development and acceptance of nature-inspired AI technologies.

Interdisciplinary and Intra-disciplinary

Nature-Inspired AI in Electronics and Communication Engineering

  • Swarm intelligence for optimizing network routing and communication protocols.
  • Bio-inspired algorithms for signal processing and wireless communications.
  • Neural networks and evolutionary computation in VLSI design and testing.
  • Integrating bio-inspired AI techniques in communication networks and signal processing for enhanced efficiency and reliability.

Mechanical Engineering Applications

  • Application of genetic algorithms and evolutionary strategies in mechanical design and manufacturing.
  • Bio-inspired robotics and automation in Industry 4.0.
  • Optimization of mechanical systems using nature-inspired computation.
  • Applying evolutionary algorithms and neural networks in the design and optimization of mechanical systems and processes.

Aeronautical Engineering Innovations

  • Use of evolutionary algorithms in aerospace design and structural optimization.
  • Nature-inspired control systems for unmanned aerial vehicles (UAVs).
  • Swarm intelligence in air traffic management and coordination.
  • Utilizing swarm intelligence and genetic algorithms for optimizing flight paths, aircraft design, and air traffic management.

Civil Engineering

  • Nature-inspired optimization techniques for infrastructure planning, smart cities, and sustainable construction practices.

Nature-Inspired Robotics and Automation

  • Developing autonomous systems and robots for industrial applications using principles from biology and natural evolution.

Materials Science and Engineering

  • Innovating new materials and manufacturing processes inspired by biological organisms and natural phenomena.

Environmental Monitoring and Sustainability

  • Employing AI algorithms inspired by nature to monitor and manage environmental systems and resources.

Business and Management

AI in Business Decision Making

  • Leveraging nature-inspired algorithms to improve business strategy, supply chain management, and operational efficiency.
  • Application of bio-inspired algorithms in business analytics and decision-making.
  • Evolutionary computation for financial modeling and risk management.
  • Nature-inspired techniques for supply chain optimization and logistics.

Innovation and Entrepreneurship

  • Exploring how nature-inspired AI can drive innovation and entrepreneurial ventures in Industry 4.0.

Financial Services

  • Application of bio-inspired machine learning models in financial analysis, risk management, and automated trading.

Law and Policy

Regulatory Frameworks for AI

  • Developing legal frameworks to govern the use of nature-inspired AI in various industries.
  • Legal implications of implementing nature-inspired AI in industry.
  • Policy frameworks for ethical AI deployment in business and technology.
  • Regulatory challenges and solutions for nature-inspired AI in Industry 4.0.

Data Privacy and Security

  • Ensuring the protection of sensitive information in AI applications through secure, nature-inspired algorithms.

Intellectual Property and Innovation

  • Addressing IP issues related to the development and deployment of nature-inspired AI technologies.

Paper Submission

Submit your research paper for the International Conference 2024. Ensure your paper follows the submission guidelines provided on our website.

Submit Now

Important Dates

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S.NO Description Dates
1 Paper Submission Deadline TBA
2 Acceptance Notification TBA
3 Registration Starts TBA
4 Camera Ready Paper Submission TBA
5 Conference Dates TBA

Registration Details

The details of the registration fee will be updated soon in accordance with the publisher's policy.

Register Here

Programme Committee

Prof. Dr. Shahrulniza Musa

Prof. Dr. Shahrulniza Musa

Professor, MIIT, University Kuala Lumpur.

Dr. Jimson Mathew

Dr. Jimson Mathew

Professor, CSE, IIT Patna.

Keynote Speakers

Will be added soon.

Conference Team

  • Dr. B. Harika, Associate Professor, Dept. of IT, MGIT.
  • Mrs. A. V. Lakshmi Prasuna, Assistant Professor, Dept. of IT, MGIT.
  • Mr. B. Tulasi Dasu, Assistant Professor, Dept. of IT, MGIT.

  • Dr. M. Rudra Kumar, Professor, Dept. of IT, MGIT.
  • Dr. Premkumar Chithaluru, Associate Professor, Dept. of IT, MGIT.
  • Dr. K P Supreethi, Professor and Head of the Department Computer Science & Engineering, JNTUH University College of Engineering, Science & Technology Hyderabad.
  • Dr. Mathini Sellathurai, Dean of Science and Engineering and the head of the Signal Processing for Intelligent Systems and Communications Research Group, Heriot-Watt University, Edinburgh, UK.
  • Dr. Nabil Mohammed Ali Munassar, Faculty at, University of Science and Technology, Yemen.
  • Dr. Fuad A. M. Al-Yarimi, faculty at Department of Computer Science, King Khalid University, Muhayel Aseer, KSA.
  • Dr. C. Shoba Bindhu, Professor, JNTUA, Ananthapuramu.
  • Dr. M. Venu Gopalachari, Prof & Head IT, CBIT, Hyderabad, India.

  • Mr. B. Lokesh, Assistant Professor, Dept. of IT, MGIT.
  • Ms. J. Hima Bindu, Assistant Professor, Dept. of IT, MGIT.

  • Dr. Gopi Chand Merugu, Deputy Secretary, University Grants Commission, New Delhi
  • C. Krishna Mohan, Professor, Department of Computer Science and Engineering, IIT Hyderabad, Telangana, India.
  • Dr. A. Ananda Rao, Professor, Dept of CSE, JNTUA, Anantapur, AP., India.
  • Dr. Habibollah Haron, Qaiwan International University, Iraq.
  • Dr. Sam Goundar, Victoria University of Wellington, New Zealand.
  • Dr. Marjan Kuchaki Rafsanjan, Shahid Bahonar University of Kerman, Kerman, Iran.
  • Dr. M. S. Mekala, Yeungnam University, Gyeongsan, Korea.
  • Dr. T. V. Ramana, TVET, Addis Ababa 1000, Ethiopia.
  • Dr. Srinivas Nowduri, United States of America.
  • Dr. Siva Ram Rajeyyagari, Shaqra University, Shaqra, Saudi Arabia.
  • Dr. R. Balasubramanian, IIT Roorkee, India.
  • Dr. Govindham V. K., NIT Calicut.
  • Dr. P. Viswanadh, IIIT Sricity.
  • Dr. Devender Gurjat, NIT Silchar.
  • Dr. K. Jairam Naik, NIT Raipur.
  • Dr. G. C. Nandi, IIIT Allahabad, Jhalwa, Uttar Pradesh.
  • Dr. Deepak Garg, Bennett University, Greater Noida, Uttar Pradesh.
  • Dr. Jagadish Kannan. R, VIT, Chennai.
  • Dr. A. Vinaya Babu, JNTUH, Hyderabad.
  • Dr. S. Viswanadha Raju, JNTUHCEJ, Jagityal, Karimnagar.
  • Dr. B. Eswar Reddy, JNTUA College of Engineering, Kalikiri.
  • Dr. P. Chenna Reddy, JNTUA, Ananthapuramu.
  • Dr. V. Valli Kumari, Professor, Andhra University, Vishakhapatnam.
  • Dr. B. K. Tripathy, VIT, Vellore.
  • Dr. B. Balamurugan, Galgotias University, Greater Noida, Uttar Pradesh.
  • Dr. Thirunavukkarasu K, Karnavati University, Uvarsad, Gandhinagar, Gujarat.
  • Dr. M. Rajasekhar Babu, VIT University, Vellore.
  • Dr. Praveen Shukla, BBD University, Lucknow.
  • Dr. G. Vara Prasad, BMS College of Engineering, Bangalore.
  • Dr. E. S. Madhan, SRM University, Chennai.
  • Ramzi Salah, Facility of Information Science and Technology, University Kebangassan Malaysia.
  • Khaled Mohamoud, Faculty at Department of Information System, King Khalid University, Muhayel Aseer, Kingdom of Saudi Arabia.
  • Prof. C. Ramesh Kumar Reddy, HoD CSE, MGIT.
  • Prof. M. Rama Bai, Professor HoD ET, MGIT.

  • Dr. Thirumal Yerragunta, MBBS MS(Gen. Surgery), MCH(Neurosurgery), Associate Professor of Neurosurgery, Nizam's Institute of Medical Sciences, Hyderabad.
  • Dr. G. Madhavi, Associate Professor, Dept. of ECE, MGIT.
  • Dr. K. Satish Kumar, Associate Professor, Dept. of CSE, MGIT.
  • Dr. Barnali Gupta Banik, Associate Professor, Dept. of ET, MGIT.
  • Dr. P. Chandrashekar, Associate Professor, Dept. of EEE, MGIT.
  • Dr. P. Suresh Babu, M.D, D.M(neurology), PDF(Epilepsy), Arete hospitals, Hyderabad.
  • Ms. U. Chaitanya, Assistant Professor, Dept. of IT, MGIT.
  • Ms. B. Meenakshi, Assistant Professor, Dept. of IT, MGIT.
  • Ms. Ch. Lakshmi Kumari, Assistant Professor, Dept. of IT, MGIT.
  • Dr. R.V.S.M. Rama Krishna, Assistant Professor, Dept. of MME, MGIT.
  • Ms. B. Swetha, Assistant Professor, Dept. of IT, MGIT.
  • Ms. Chinnakka Sudha, Assistant Professor, Dept. of IT, MGIT.
  • Ms. V. Veena, Assistant Professor, Dept. of IT, MGIT.
  • Ms. A. Amulya, Assistant Professor, Dept. of IT, MGIT.
  • Ms. M. Varalakshmi, Assistant Professor, Dept. of IT, MGIT.
  • Ms. R. Vijayalakshmi, Assistant Professor, Dept. of IT, MGIT.
  • Ms. S. Suba, Assistant Professor, Dept. of IT, MGIT.
  • Ms. P. Naveena, Assistant Professor, Dept. of IT, MGIT.
  • Dr. Ch. Srinivasu, Assistant Professor, Dept. of P&C, MGIT.
  • Dr. G. Srinivas Reddy, Assistant Professor, Dept. of P&C, MGIT.
  • Mr. B. Sasidhar, Assistant Professor, Dept. of Management Science, MGIT.

Contact Us

If you have any questions or need further information, please contact us at icnai@mgit.ac.in

Email: mrudrakumar_it@mgit.ac.in chpremkumar_it@mgit.ac.in blokesh_it@mgit.ac.in Mobile:+91-8142781437, +91-7060509299, +91-8019923406