{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T04:52:05Z","timestamp":1770526325136,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2020,11,7]],"date-time":"2020-11-07T00:00:00Z","timestamp":1604707200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s20216348","type":"journal-article","created":{"date-parts":[[2020,11,8]],"date-time":"2020-11-08T19:03:37Z","timestamp":1604862217000},"page":"6348","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Cloud-Based Monitoring of Thermal Anomalies in Industrial Environments Using AI and the Internet of Robotic Things"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9045-6698","authenticated-orcid":false,"given":"Mohammed","family":"Ghazal","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering Department, College of Engineering, Abu Dhabi University, Abu Dhabi 59911, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9435-8630","authenticated-orcid":false,"given":"Tasnim","family":"Basmaji","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering Department, College of Engineering, Abu Dhabi University, Abu Dhabi 59911, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9752-9124","authenticated-orcid":false,"given":"Maha","family":"Yaghi","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering Department, College of Engineering, Abu Dhabi University, Abu Dhabi 59911, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6140-7371","authenticated-orcid":false,"given":"Mohammad","family":"Alkhedher","sequence":"additional","affiliation":[{"name":"Mechanical Engineering Department, College of Engineering, Abu Dhabi University, Abu Dhabi 59911, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Mahmoud","sequence":"additional","affiliation":[{"name":"Emirates Global Aluminium, Technology Development and Transfer Midstream, Abu Dhabi 109111, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7264-1323","authenticated-orcid":false,"given":"Ayman S.","family":"El-Baz","sequence":"additional","affiliation":[{"name":"Bioengineering Department, University of Louisville, Louisville, KY 40292, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,7]]},"reference":[{"key":"ref_1","unstructured":"Bekey, G. (2017). Autonomous Robots, Bradford Books."},{"key":"ref_2","unstructured":"Murphy, A. (2020, September 07). Industrial: Robotics Outlook 2025. Loup Ventures, Available online: https:\/\/loupventures.com\/industrial-robotics-outlook-2025\/."},{"key":"ref_3","unstructured":"Rembold, U., Lueth, T., and Ogasawara, T. (1994, January 12\u201316). From autonomous assembly robots to service robots for factories. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS\u201994), Munich, Germany."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1109\/MIE.2019.2938025","article-title":"Real-Time Monitoring and Control of Industrial Cyberphysical Systems: With Integrated Plant-Wide Monitoring and Control Framework","volume":"13","author":"Yin","year":"2019","journal-title":"IEEE Ind. Electron. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Tas, M.O., Yavuz, H.S., and Yazici, A. (2018, January 25\u201327). Updating HD-Maps for Autonomous Transfer Vehicles in Smart Factories. Proceedings of the 6th International Conference on Control Engineering & Information Technology (CEIT), Istanbul, Turkey.","DOI":"10.1109\/CEIT.2018.8751934"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Saeed, M.S., and Alim, N. (2019, January 10\u201312). Design and Implementation of a Dual Mode Autonomous Gas Leakage Detecting Robot. Proceedings of the International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh.","DOI":"10.1109\/ICREST.2019.8644075"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Rey, R., Corzetto, M., Cobano, J.A., Merino, L., and Caballero, F. (2019, January 10\u201313). Human-robot co-working system for warehouse automation. Proceedings of the 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Zaragoza, Spain.","DOI":"10.1109\/ETFA.2019.8869178"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Montano, L. (2019, January 10\u201313). Robots in challenging environments. Proceedings of the 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Zaragoza, Spain.","DOI":"10.1109\/ETFA.2019.8869304"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Teja, P.R., and Kumaar, A.A.N. (2018, January 19\u201322). QR Code based Path Planning for Warehouse Management Robot. Proceedings of the International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, India.","DOI":"10.1109\/ICACCI.2018.8554760"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Chie, L.C., and Juin, Y.W. (2020, January 16\u201321). Artificial Landmark-based Indoor Navigation System for an Autonomous Unmanned Aerial Vehicle. Proceedings of the IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA), Bangkok, Thailand.","DOI":"10.1109\/ICIEA49774.2020.9102082"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Limeira, M.A., Piardi, L., Kalempa, V.C., de Oliveira, A.S., and Leit\u00e3o, P. (2019, January 23\u201325). WsBot: A Tiny, Low-Cost Swarm Robot for Experimentation on Industry 4.0. Proceedings of the 2019 Latin American Robotics Symposium (LARS), 2019 Brazilian Symposium on Robotics (SBR) and 2019 Workshop on Robotics in Education (WRE), Rio Grande, Brazil.","DOI":"10.1109\/LARS-SBR-WRE48964.2019.00058"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ciuccarelli, L., Freddi, A., Longhi, S., Monteriu, A., Ortenzi, D., and Pagnotta, D.P. (2018, January 30\u201331). Cooperative Robots Architecture for an Assistive Scenario. Proceedings of the Zooming Innovation in Consumer Technologies Conference (ZINC), Novi Sad, Serbia.","DOI":"10.1109\/ZINC.2018.8448951"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Avola, D., Foresti, G.L., Cinque, L., Massaroni, C., Vitale, G., and Lombardi, L. (2016, January 19\u201321). A multipurpose autonomous robot for target recognition in unknown environments. Proceedings of the IEEE 14th International Conference on Industrial Informatics (INDIN), Poitiers, France.","DOI":"10.1109\/INDIN.2016.7819262"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/MRA.2018.2877189","article-title":"The VIKINGS Autonomous Inspection Robot: Competing in the ARGOS Challenge","volume":"26","author":"Merriaux","year":"2019","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Dharmasena, T., and Abeygunawardhana, P. (2019, January 5\u20137). Design and Implementation of an Autonomous Indoor Surveillance Robot based on Raspberry Pi. Proceedings of the International Conference on Advancements in Computing (ICAC), Malabe, Sri Lanka.","DOI":"10.1109\/ICAC49085.2019.9103399"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mogaveera, A., Giri, R., Mahadik, M., and Patil, A. (2018, January 29\u201331). Self Driving Robot using Neural Network. Proceedings of the International Conference on Information, Communication, Engineering and Technology (ICICET), Pune, India.","DOI":"10.1109\/ICICET.2018.8533870"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Omrane, H., Masmoudi, M.S., and Masmoudi, M. (2018, January 21\u201324). Neural controller of autonomous driving mobile robot by an embedded camera. Proceedings of the 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), Sousse, Tunisia.","DOI":"10.1109\/ATSIP.2018.8364445"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Ebuchi, T., and Yamamoto, H. (2019, January 11\u201313). Vehicle\/Pedestrian Localization System Using Multiple Radio Beacons and Machine Learning for Smart Parking. Proceedings of the International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Okinawa, Japan.","DOI":"10.1109\/ICAIIC.2019.8668993"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"9692","DOI":"10.1109\/TIE.2018.2881943","article-title":"Activity Recognition Using Temporal Optical Flow Convolutional Features and Multilayer LSTM","volume":"66","author":"Ullah","year":"2019","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ullah, W., Ullah, A., Haq, I.U., Muhammad, K., Sajjad, M., and Baik, S.W. (2020). CNN features with bi-directional LSTM for real-time anomaly detection in surveillance networks. Multimed. Tools Appl.","DOI":"10.1007\/s11042-020-09406-3"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1109\/TIE.2016.2607683","article-title":"A Data-Driven Learning Approach for Nonlinear Process Monitoring Based on Available Sensing Measurements","volume":"64","author":"Yin","year":"2017","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"711","DOI":"10.3724\/SP.J.1004.2013.00711","article-title":"A Survey on Anomaly Detection, Life Prediction and Maintenance Decision for Industrial Processes","volume":"39","author":"Zhou","year":"2014","journal-title":"Acta Autom. Sin."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Kammerer, K., Hoppenstedt, B., Pryss, R., St\u00f6kler, S., Allgaier, J., and Reichert, M. (2019). Anomaly Detections for Manufacturing Systems Based on Sensor Data\u2014Insights into Two Challenging Real-World Production Settings. Sensors, 19.","DOI":"10.3390\/s19245370"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Pittino, F., Puggl, M., Moldaschl, T., and Hirschl, C. (2020). Automatic Anomaly Detection on In-Production Manufacturing Machines Using Statistical Learning Methods. Sensors, 20.","DOI":"10.3390\/s20082344"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Kroll, B., Schaffranek, D., Schriegel, S., and Niggemann, O. (2014, January 16\u201319). System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants. Proceedings of the IEEE Emerging Technology and Factory Automation (ETFA), Barcelona, Spain.","DOI":"10.1109\/ETFA.2014.7005202"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.promfg.2019.02.013","article-title":"Anomaly Detection from Online Monitoring of System Operations Using Recurrent Neural Network","volume":"30","author":"Kubota","year":"2019","journal-title":"Procedia Manuf."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Hyland, M. (2016). Cell Electrical Preheating Practices at Dubal, Springer. Light Metals 2015.","DOI":"10.1007\/978-3-319-48248-4"},{"key":"ref_28","first-page":"682786","article-title":"Aluminium Process Fault Detection and Diagnosis","volume":"2015","author":"Majid","year":"2015","journal-title":"Adv. Mater. Sci. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gang, H., and Pyun, J. (2019). A Smartphone Indoor Positioning System Using Hybrid Localization Technology. Energies, 12.","DOI":"10.3390\/en12193702"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1109\/42.845174","article-title":"Parametric estimate of intensity inhomogeneities applied to MRI","volume":"19","author":"Styner","year":"2000","journal-title":"IEEE Trans. Med. 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