{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T03:35:23Z","timestamp":1764732923316,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T00:00:00Z","timestamp":1628208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Robotics Programme under its Robotics Enabling Capabilities and Technologies","award":["192 25 00051, 192 22 00108"],"award-info":[{"award-number":["192 25 00051, 192 22 00108"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Routine rodent inspection is essential to curbing rat-borne diseases and infrastructure damages within the built environment. Rodents find false ceilings to be a perfect spot to seek shelter and construct their habitats. However, a manual false ceiling inspection for rodents is laborious and risky. This work presents an AI-enabled IoRT framework for rodent activity monitoring inside a false ceiling using an in-house developed robot called \u201cFalcon\u201d. The IoRT serves as a bridge between the users and the robots, through which seamless information sharing takes place. The shared images by the robots are inspected through a Faster RCNN ResNet 101 object detection algorithm, which is used to automatically detect the signs of rodent inside a false ceiling. The efficiency of the rodent activity detection algorithm was tested in a real-world false ceiling environment, and detection accuracy was evaluated with the standard performance metrics. The experimental results indicate that the algorithm detects rodent signs and 3D-printed rodents with a good confidence level.<\/jats:p>","DOI":"10.3390\/s21165326","type":"journal-article","created":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T08:01:42Z","timestamp":1628236902000},"page":"5326","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["AI Enabled IoRT Framework for Rodent Activity Monitoring in a False Ceiling Environment"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3243-9814","authenticated-orcid":false,"given":"Balakrishnan","family":"Ramalingam","sequence":"first","affiliation":[{"name":"Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore"}]},{"given":"Thein","family":"Tun","sequence":"additional","affiliation":[{"name":"Oceania Robotics, Singapore 627606, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6504-1530","authenticated-orcid":false,"given":"Rajesh Elara","family":"Mohan","sequence":"additional","affiliation":[{"name":"Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore"}]},{"given":"Braulio F\u00e9lix","family":"G\u00f3mez","sequence":"additional","affiliation":[{"name":"Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore"}]},{"given":"Ruoxi","family":"Cheng","sequence":"additional","affiliation":[{"name":"Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore"}]},{"given":"Selvasundari","family":"Balakrishnan","sequence":"additional","affiliation":[{"name":"Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore"}]},{"given":"Madan","family":"Mohan Rayaguru","sequence":"additional","affiliation":[{"name":"Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6141-4600","authenticated-orcid":false,"given":"Abdullah Aamir","family":"Hayat","sequence":"additional","affiliation":[{"name":"Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2019\/5137139","article-title":"Visual Inspection of the Aircraft Surface Using a Teleoperated Reconfigurable Climbing Robot and Enhanced Deep Learning Technique","volume":"2019","author":"Ramalingam","year":"2019","journal-title":"Int. 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