International Conference on Artificial Intelligence and Sustainable Innovation 2025 (ICAISI-2025)
Hybrid Mode
May 30^th-31^st, 2025
📩 Submission Link

About Track: The International Conference on Artificial Intelligence and Sustainable Innovation 2025 serves as a global platform for researchers, industry experts, and policymakers to explore the transformative role of Artificial Intelligence (AI) in driving sustainable innovation. As the world faces pressing challenges in climate change, urbanization, energy efficiency, and digital transformation, AI has emerged as a key enabler in fostering sustainability, efficiency, and resilience across multiple domains. This General Track focuses on the broad impact of AI-driven sustainable solutions across industries, bridging the gap between cutting-edge research and real-world applications.

About Track: The AI for Smart Computing and Communication Sustainability track focuses on leveraging artificial intelligence (AI) and emerging computational paradigms to enhance efficiency, sustainability, and intelligence in next-generation communication networks and computing infrastructures. With the rapid advancements in high-speed networks like 6G, AI-driven methodologies are essential for managing the complexity of fog computing, edge computing, and IoT-based systems.

About Track: The AI for Smart Cities & Urban Sustainability track focuses on the integration of artificial intelligence (AI) in urban environments to enhance efficiency, sustainability, and the overall quality of life. As cities grow and urbanization accelerates, AI-driven solutions are becoming essential for managing resources, optimizing infrastructure, and ensuring sustainable development. This track explores AI applications in transportation, energy management, environmental monitoring, and smart governance.

About Track: The AI in Healthcare & Medical Sustainability track explores the transformative impact of Artificial Intelligence (AI) in revolutionizing healthcare systems, enhancing patient care, and promoting sustainable medical practices. AI-driven innovations in predictive diagnostics, personalized medicine, medical imaging, and drug discovery are improving efficiency, reducing costs, and enabling early disease detection. This track focuses on AI-powered robotic surgeries, intelligent health monitoring, telemedicine, and AI-driven healthcare analytics to optimize medical resource utilization and accessibility.

About Track: The AI Ethics, Fairness & Governance track focuses on the critical need for responsible AI development, deployment, and regulation to ensure transparency, accountability, and inclusivity in AI-driven systems. As AI continues to influence decision-making across sectors, this track explores key challenges in bias mitigation, explainability, privacy protection, and ethical AI frameworks that promote fairness and trust. It examines AI governance policies, regulatory compliance, algorithmic transparency, and the role of AI in social justice, ensuring equitable outcomes for diverse communities.

About Track: The AI in Renewable Energy & Smart Grids track explores the transformative role of Artificial Intelligence (AI) in optimizing renewable energy generation, distribution, and consumption for a more sustainable future. AI-driven solutions are revolutionizing smart grids, energy forecasting, demand response, and grid resilience, enabling real-time decision-making and improving energy efficiency. This track focuses on AI applications in solar and wind energy prediction, automated grid balancing, intelligent energy storage management, and fault detection to enhance the reliability of renewable energy sources.

About Track: The AI for Cybersecurity & Data Protection track focuses on the critical role of Artificial Intelligence (AI) in securing digital infrastructures, protecting sensitive data, and mitigating cyber threats in an increasingly connected world. AI-driven cybersecurity solutions, such as threat detection, anomaly detection, automated incident response, and predictive analytics, are revolutionizing how organizations identify, prevent, and respond to cyberattacks in real time. This track explores AI-powered fraud detection, biometric authentication, privacy-preserving AI, and adversarial AI defense mechanisms, ensuring robust data security in cloud computing, IoT networks, and critical infrastructures.

About Track: The AI & Edge Computing for IoT track explores the fusion of Artificial Intelligence (AI) and Edge Computing to enhance the efficiency, responsiveness, and sustainability of Internet of Things (IoT) ecosystems. By processing data closer to the source, AI-driven edge computing reduces latency, bandwidth usage, and energy consumption, enabling real-time decision-making for smart cities, healthcare, industrial automation, and connected vehicles. This track focuses on AI-powered edge analytics, federated learning for IoT security, intelligent sensor networks, and energy-efficient edge AI models, ensuring scalable and adaptive IoT solutions.

About Track: The AI in Business & Finance for Sustainable Growth track focuses on the transformative role of artificial intelligence in driving economic sustainability, financial inclusion, and responsible corporate strategies. AI-powered solutions, such as predictive analytics, algorithmic trading, fraud detection, and risk management, are reshaping financial markets and business operations, improving efficiency while minimizing environmental and social impacts. This track explores AI applications in green finance, ESG (Environmental, Social, and Governance) investing, AI-driven financial forecasting, and sustainable supply chain management, ensuring businesses make data-driven, ethical, and long-term sustainable decisions.

About Track: The AI for Sustainable Education & Digital Learning track explores how artificial intelligence is transforming education by enhancing accessibility, personalization, and sustainability in learning environments. AI-driven technologies, such as adaptive learning systems, intelligent tutoring, and automated content generation, are revolutionizing digital education by providing personalized learning experiences tailored to individual student needs. This track also examines AI-powered virtual classrooms, learning analytics, and AI-driven assessments, which help optimize educational outcomes while promoting inclusivity and sustainability.

About Track: The AI in Transportation & Mobility track focuses on the transformative impact of Artificial Intelligence (AI) on modern transportation systems. As global mobility demands increase, AI-driven innovations are revolutionizing how we move people and goods, enhancing efficiency, safety, and sustainability. This track explores how AI is shaping the future of autonomous vehicles, intelligent traffic management, smart logistics, and sustainable mobility solutions.

About Track: The rapid evolution of futuristic technologies, including artificial intelligence, quantum computing, 5G communication, and blockchain, is transforming industries at an unprecedented pace. Recent advancements have paved the way for smarter automation, enhanced cybersecurity, and seamless human-machine collaboration. However, significant challenges remain, such as ethical concerns in AI decision-making, data privacy risks, the integration of emerging technologies into legacy systems, and the need for sustainable innovation.

About Track: This special track aims to provide a platform for researchers, practitioners, and industry experts to share their insights on leveraging AI to address sustainability challenges. The primary objectives of this track are to discuss recent advancements, promote interdisciplinary collaboration, and showcase innovative solutions for sustainable development.

About Track: The rapid advancement of Artificial Intelligence (AI) has revolutionized industries, economies, and societies, but it has also introduced unprecedented challenges in the realm of cybersecurity and digital forensics. As AI technologies become more sophisticated, they are increasingly being weaponized by cybercriminals to launch highly targeted, scalable, and evasive attacks. From deepfakes and adversarial machine learning to AI-powered malware and automated phishing campaigns, the threat landscape is evolving at an alarming pace. At the same time, AI is emerging as a powerful tool for cybersecurity professionals and forensic investigators, enabling them to detect, analyze, and mitigate these threats with greater speed and accuracy.

About Track: AI-driven visualization simplifies complex datasets, leading to better decision-making across industries. Medical AI improves diagnostic accuracy and supports personalized healthcare. Corporate AI enhances business intelligence, financial risk analysis, and operational efficiency. Social media analytics helps detect trends, misinformation, and audience behavior.

About Track: AI for Cognitive and Computational Intelligence involves using artificial intelligence to model, enhance, and automate cognitive processes such as learning, reasoning, perception, and problem-solving. This interdisciplinary field brings together machine learning, deep learning neuroscience, psychology, and computational theories to develop systems that mimic human intelligence or go beyond human capabilities in problem-solving. Computational intelligence involves metaheuristics algorithms for managing real-time applications in terms of image analysis and processing in healthcare, image, agriculture, biometrics, cyber networks, education, hate detection and many more.

About Track: New Age Technology for society 5.0 approach is the rapidly emergent technology in Computer Engineering and medical domains is among the best application challenges, providing future benefits in improved disease predictions system and medical diagnoses system. New age Technology can predicts different patterns associated with diseases and physical condition of patient by analyzing large available healthcare patient dataset. New Age Technology can help increase healthcare access in developing countries and predicting correct diagnosis and treatment for various diseases. Biomedical and health care informatics applies principles of computer science and engineering to the advancement of public health, patient care and health professions education. This multidisciplinary field works on healthcare information technologies (HIT), and involves the computer, cognitive, and social sciences.

About Track: The special track Artificial Intelligence with Data Science Techniques in Real-World Applications focuses on leveraging AI-driven methodologies and data science approaches to solve practical challenges across various domains. This track explores the integration of machine learning, deep learning, and statistical techniques with real-world datasets to enhance decision-making, automation, and predictive analytics. Key topics include data preprocessing, model optimization, interpretability, and ethical considerations in AI. Applications span industries such as healthcare, finance, manufacturing, and smart cities, demonstrating how AI-powered insights drive innovation and efficiency in real-world scenarios.

About Track: The integration of Artificial Intelligence (AI), Big Data, and Quantum Computing is transforming Intelligent E-Commerce for personalized and secure shopping experiences. This special session will explore advancements in AI based n recommendation engines, conversational AI, and real-time big data processing for predictive consumer insights. Key topics include AI-based inventory management and automated warehouses, optimizing supply chains for efficiency. Additionally, the session will highlight Quantum Computing’s role in accelerating machine learning for retail, enabling ultra-fast data processing, and enhancing security with quantum-based encryption for secure transactions.

About Track: This special session focuses on the ethical challenges and human-centric design of AI systems, ensuring they align with societal values. It will explore fairness, transparency, accountability, and trust in AI, fostering interdisciplinary discussions among researchers, practitioners, and policymakers.

About Track: This special session explores recent advancements in Artificial Intelligence (AI), Machine Learning (ML), and Cloud Computing, focusing on their applications in data analytics and image intelligence. It aims to bring together researchers and industry experts to discuss scalable AI-driven solutions, deep learning techniques, and cloud-based frameworks that enhance intelligent computing. Aligned with the theme of "Artificial Intelligence and Sustainable Innovation," the session emphasizes sustainable and impactful AI applications in healthcare, smart cities, and automation. Key topics include AI-powered data mining, deep learning for image analysis, cloud-integrated AI models, and energy-efficient computing strategies. By fostering discussions on these emerging trends, the session seeks to drive innovation and sustainability in intelligent computing.

About Track: The fusion of Natural Language Processing (NLP) and Computer Vision (CV) is transforming AI, enabling machines to understand and connect both text and images effectively. This session explores how combining NLP and CV can solve real-world challenges while promoting sustainability, inclusivity, and ethical AI. Key topics include multimodal intelligence, contextual understanding, and AI-driven decision-making, with applications in healthcare, education, smart cities, and environmental monitoring. The session will highlight the latest advancements in Vision-Language Models (VLMs), transformer architectures, and generative AI, showcasing their role in image captioning, text-to-image generation, and video analysis for accessibility, medical diagnostics, and sustainable urban development.

About Track: The healthcare sector is looking to improve the sustainability of the system by implementing IoT and artificial intelligence (AI) to augment patient outcomes and improve workflow efficiencies. For instance, the objective of IoT is to improve outcomes through remote patient monitoring. Remote patient monitoring devices will record vital signs such as heart rate and blood pressure. Data generated by such devices is analysed utilizing machine learning and AI to help identify possible risks to health and provide personalized treatment for the patient, if warranted, thus improving chronic disease management and reducing preventable hospital readmissions. Another use of AI in conjunction with IoT devices is in the data being collected in real time; along with providing early warning of abnormalities, it can also create personalized patient care. AI algorithms can improve diagnostic and predictive analytics on the data collected, providing evidence-based decision-making processes for the healthcare professional. Sustainability in healthcare involves reducing operational expenses and improving resource allocation. An example of the application of IoT is current examples of inventory management and asset tracking that identify waste and increase operational efficiency. More broadly the introduction of edge computing could speed processing time, resulting in less latency and quicker real-time decision making. As with anything, there are challenges to realizing the potential of these technologies, including developing standards and processes that address data security, data privacy, cyber security, and infrastructure issues. However, the convergence of these technologies has the potential to bring unprecedented change to the delivery of health services to make them more sustainable, resilient, and responsive.

About Track: This session explores the integration of Rough Set Theory, Soft Computing, and Quantum Computing for intelligent decision-making, optimization, and cybersecurity. It is widely known and proven that Rough Sets handle uncertainty, while Fuzzy-Rough Hybrid approaches enhance data analysis and classification. Swarm Intelligence optimizes AI and robotics by mimicking natural behaviours. Now in recent years, it has been observed that Quantum Computing is revolutionizing AI and Machine Learning, offering faster computation and pattern recognition. Recent research in Quantum-Inspired Optimization in Soft Computing provides powerful solutions for complex problem-solving. The emergence of Hybrid Quantum-Soft Computing Architectures is enhancing AI-driven applications with improved efficiency. Additionally, Cybersecurity is also evolving with Quantum Cryptography and Soft Computing, ensuring secure data transmission and protection against cyber threats.