Emerging Trends And Future Directions In Artificial Intelligence Machine Learning And Internet Of Things Innovations
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Emerging Trends and Future Directions in Artificial Intelligence, Machine Learning, and Internet of Things Innovations
Author: Khumukcham Robindro Singh
language: en
Publisher: CRC Press
Release Date: 2025-09-29
The “North East India AI Summit: Unravelling Trends (NEIAIS 2025)” served as a vibrant platform for the exchange of cutting-edge ideas and research in the field of Artificial Intelligence, with a strong emphasis on both foundational theo□ries and real-world applications. The summit brought together experts, researchers, and enthusiasts to explore critical areas including Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Smart Systems, IoT Security, Network Technology, and Artificial Intelligence in Healthcare and Biomedical Applications. Discussions also delved into emerging trends and computational techniques, highlighting the transformative potential of AI in addressing complex, real-world challenges. The conference received an overwhelming response, attracting more than 120 research paper submissions from various regions of India and abroad. After a rigorous review process, 55 high-quality papers were accepted, out of which over 44 papers were registered for presentation at the summit. By fostering interdisciplinary col□laboration and showcasing impactful innovations, NEIAIS 2025 aims to inspire sustained research, technological growth, and broader societal benefits.
Recent Trends and Advances in Artificial Intelligence and Internet of Things
Author: Valentina E. Balas
language: en
Publisher: Springer Nature
Release Date: 2019-11-19
This book covers all the emerging trends in artificial intelligence (AI) and the Internet of Things (IoT). The Internet of Things is a term that has been introduced in recent years to define devices that are able to connect and transfer data to other devices via the Internet. While IoT and sensors have the ability to harness large volumes of data, AI can learn patterns in the data and quickly extract insights in order to automate tasks for a variety of business benefits. Machine learning, an AI technology, brings the ability to automatically identify patterns and detect anomalies in the data that smart sensors and devices generate, and it can have significant advantages over traditional business intelligence tools for analyzing IoT data, including being able to make operational predictions up to 20 times earlier and with greater accuracy than threshold-based monitoring systems. Further, other AI technologies, such as speech recognition and computer vision can help extract insights from data that used to require human review. The powerful combination of AI and IoT technology is helping to avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management.
Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics
The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.