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Ms. Tasnim Basmaji
Abu Dhabi University, Abu Dhabi

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0 Cyber Security
0 Mobile Application Development
0 Smart Cities
0 Robotics and Automation
0 Artificial Intellengence

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Journal article
Published: 07 November 2020 in Sensors
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Recent advancements in cloud computing, artificial intelligence, and the internet of things (IoT) create new opportunities for autonomous industrial environments monitoring. Nevertheless, detecting anomalies in harsh industrial settings remains challenging. This paper proposes an edge-fog-cloud architecture with mobile IoT edge nodes carried on autonomous robots for thermal anomalies detection in aluminum factories. We use companion drones as fog nodes to deliver first response services and a cloud back-end for thermal anomalies analysis. We also propose a self-driving deep learning architecture and a thermal anomalies detection and visualization algorithm. Our results show our robot surveyors are low-cost, deliver reduced response time, and more accurately detect anomalies compared to human surveyors or fixed IoT nodes monitoring the same industrial area. Our self-driving architecture has a root mean square error of 0.19 comparable to VGG-19 with a significantly reduced complexity and three times the frame rate at 60 frames per second. Our thermal to visual registration algorithm maximizes mutual information in the image-gradient domain while adapting to different resolutions and camera frame rates.

ACS Style

Mohammed Ghazal; Tasnim Basmaji; Maha Yaghi; Mohammad Alkhedher; Mohamed Mahmoud; Ayman El-Baz. Cloud-Based Monitoring of Thermal Anomalies in Industrial Environments Using AI and the Internet of Robotic Things. Sensors 2020, 20, 6348 .

AMA Style

Mohammed Ghazal, Tasnim Basmaji, Maha Yaghi, Mohammad Alkhedher, Mohamed Mahmoud, Ayman El-Baz. Cloud-Based Monitoring of Thermal Anomalies in Industrial Environments Using AI and the Internet of Robotic Things. Sensors. 2020; 20 (21):6348.

Chicago/Turabian Style

Mohammed Ghazal; Tasnim Basmaji; Maha Yaghi; Mohammad Alkhedher; Mohamed Mahmoud; Ayman El-Baz. 2020. "Cloud-Based Monitoring of Thermal Anomalies in Industrial Environments Using AI and the Internet of Robotic Things." Sensors 20, no. 21: 6348.