Journal Information

Journal of Sensors (JS)

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Impact Factor:
1.1
Publisher:
Hindawi
ISSN:
1687-725X
Viewed:
27363
Tracked:
4

Call For Papers

Journal of Sensors (JS) is an academic journal published by Hindawi. (ISSN 1687-725X, impact factor 1.1).

Aims and scope Journal of Sensors publishes papers related to all aspects of sensors, from their theory and design, to the applications of complete sensing devices. All classes of sensor are covered, including acoustic, biological, chemical, electronic, electromagnetic (including optical), mechanical, proximity, and thermal. Submissions relating to wearable, implantable, and remote sensing devices are encouraged. Envisaged applications include, but are not limited to: Medical, healthcare, and lifestyle monitoring Environmental and atmospheric monitoring Sensing for engineering, manufacturing and processing industries Transportation, navigation, and geolocation Vision, perception, and sensing for robots and UAVs The journal welcomes articles that, as well as the sensor technology itself, consider the practical aspects of modern sensor implementation, such as networking, communications, signal processing, and data management. As well as original research, Journal of Sensors also publishes focused review articles that examine the state of the art, identify emerging trends, and suggest future directions for developing fields.
Last updated by Dou Sun in

Special Issues

Special Issue on AI in Advanced Manufacturing Submission Date: 2026-07-30 Description Artificial intelligence (AI) is transforming advanced manufacturing, powering smarter, more connected production systems that drive Industry 4.0. From machine learning streamlining factory processes to cyber-physical systems enabling real-time adaptability, AI is tackling big challenges like sustainability and efficiency with incredible precision. Fuelled by the surge in AI-driven manufacturing research, we’re excited to launch this special collection. Join us in exploring how AI is revolutionizing production, sparking innovation, and shaping the future of smart factories. This collection aims to consolidate cutting-edge research and comprehensive reviews on the application of AI in advanced manufacturing. By fostering interdisciplinary collaboration across AI, engineering, and manufacturing sciences, the issue seeks to elucidate how AI enhances production systems, drives innovation, and addresses industrial challenges like sustainability and scalability, paving the way for smart factories and Industry 4.0. Significance of the Collection- This collection will serve as a vital resource for researchers, industry professionals, and policymakers by compiling high-quality research and expert insights. It will advance understanding of AI’s role in revolutionizing manufacturing, fostering sustainability, and enhancing global competitiveness. The findings will support initiatives like Made in China 2025 and India’s AI Mission, shaping the future of smart manufacturing and Industry 4.0. Potential topics include but are not limited to the following: AI for Process Optimization: Machine learning and deep learning for real-time process control, parameter optimization, and quality assurance in manufacturing (e.g., machining, casting). Predictive Maintenance and Fault Diagnosis: AI-driven predictive analytics for equipment health monitoring, anomaly detection, and remaining useful life estimation. Additive Manufacturing Innovations: AI applications in material selection, defect detection, and topology optimization for 3D printing and advanced geometries. Human-Robot Collaboration: AI-enabled collaborative robots (cobots) for safe, efficient human-machine interaction in smart manufacturing environments. Sustainability and Digital Twins: AI strategies for reducing waste, optimizing energy use, and implementing digital twins for real-time production system optimization. Editors Lead Guest Editor Pramita Mishra1 1Wiley PRD, India Guest Editors Deepali .1 1Wiley PRD, India https://onlinelibrary.wiley.com/doi/toc/10.1155/9161.SI-2025-001105
Last updated by Dou Sun in

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