Integration of AI-based manufacturing and industrial engineering systems with the Internet of Things [electronic resource] / edited by Pankaj Bhambri, Sita Rani, Valentina E. Balas and Ahmed A. Elngar.

"Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and machine learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments. T...

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Bibliographic Details
Other Authors: Bhambri, Pankaj (Editor)
Rani, Sita (Editor)
Balas, Valentina Emilia (Editor)
Elngar, Ahmed A. (Editor)
Language:English
Published: Boca Raton FL : CRC Press, 2024.
Edition:First edition.
Series:Intelligent manufacturing and industrial engineering
Subjects:
Online Access:
Format: Electronic eBook

MARC

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245 0 0 |a Integration of AI-based manufacturing and industrial engineering systems with the Internet of Things  |h [electronic resource] /  |c edited by Pankaj Bhambri, Sita Rani, Valentina E. Balas and Ahmed A. Elngar. 
250 |a First edition. 
264 1 |a Boca Raton FL :  |b CRC Press,  |c 2024. 
490 0 |a Intelligent manufacturing and industrial engineering 
504 |a Includes bibliographical references. 
505 0 |a Challenges, opportunities, and the future of industrial engineering with IoT and AI / Pankaj Bhambri and Sita Rani -- Evolution and future of industrial engineering with IOT and AI / Rachna Rana, Pankaj Bhambri and Yogesh Chhabra -- Applications of artificial intelligence and internet of things IoT in marketing / Lakshmi, M. Dharmananda and B S Harisha -- An introduction to multi-objective decision programming with fuzzy parameters / Zahid Amin Malik -- Data analytics / Saaema Akhtar -- Recent advances on deep learning based thermal infrared object tracking in videos: a survey / Aayushi Gautam, Santosh Kumar and Swaran Singh -- Heuristics to secure IoT-based edge driven UAV / Hemant Kumar Saini and Kusumlata Jain -- Phased.js: automated software deployment & resource provisioning and management for AI / Ushashree P, Archana Naik, Anurag Verma and Anshuman Priyadarshini -- Robust image enhancement technique to automatically enrich the visibility of satellite captured snaps / Dileep M R, Navaneeth A V, Vidyadevi G Biradar and Madhwaraj Kango Gopal -- Implementation of FIR filter and creation of custom IP blocks / Gampa Nikhitha, Pusa Vineela, Polishetty Gayatri and Dharmavaram Asha Devi -- Use cases of blockchain in post-Covid healthcare / Charu Krishna, Divya Kumar and Dharmender Singh Kushwaha -- A prediction of telecom customer churn analysis uses the I-GBDT algorithm / P Geetha, R K Kapila Vani, S Lakshmi Gayathri and S Keerthana Sri -- Deployment of machine learning and deep learning algorithms in industrial engineering / Hutashan Vishal Bhagat and Manminder Singh -- Simulation analysis of AODV and DSDV routing protocols for secure and reliable service in mobile adhoc networks (MANETs) / Gurjeet Singh and Pankaj Bhambri -- Landmine detection and classification based on machine learning algorithms / T. Kalaichelvi and S. Ravi -- Application of queuing technique in an educational institute canteen- a case study / Jagdeep Singh and Prem Singh -- IoT based driver drowsiness detection and alerting system using haar cascade and eye aspect ratio algorithms / R. Sathya, D. Sai Surya Harsha, G. Pavan Sundar Reddy and M. Gopala Krishna -- Force/position control of constrained reconfigurable manipulators using hybrid backstepping neural networks based control approach / Manju Rani and Naveen Kumar. 
520 |a "Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and machine learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments. The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency. A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies"--  |c Provided by publisher. 
650 0 |a Artificial intelligence  |x Industrial applications. 
650 0 |a Internet of Things  |x Industrial applications. 
700 1 |a Bhambri, Pankaj,  |e editor. 
700 1 |a Rani, Sita,  |e editor. 
700 1 |a Balas, Valentina Emilia,  |e editor. 
700 1 |a Elngar, Ahmed A.,  |e editor. 
773 0 |t Taylor & Francis Complete 2023 eBooks   |d Taylor and Francis 
776 0 8 |i Print version:  |t Integration of AI-based manufacturing and industrial engineering systems with the Internet of Things  |b First edition.  |d Boca Raton FL : CRC Press, 2024  |z 9781032466019  |w (DLC) 2023035107 
856 4 0 |y Access Content Online(from Taylor & Francis Complete 2023 eBooks)  |u https://ezproxy.msu.edu/login?url=https://www.taylorfrancis.com/books/9781003383505  |z Taylor & Francis Complete 2023 eBooks: 2023