Intellimice Classifier: Towards Smart Object Detection and Classification of Laboratory Mice Using Multi-Sensor Integration DOI Open Access
Giva Andriana Mutiara,

Periyadi Mutiara,

Muhammad Rizqy Alfarisi

и другие.

Journal of Electrical and Electronic Engineering, Год журнала: 2025, Номер 13(1), С. 59 - 81

Опубликована: Фев. 27, 2025

Laboratory mice (Mus musculus) play a crucial role in scientific research, where accurate classification and sorting are essential for ensuring reliable experimental results. This study presents an intelligent multi-sensor system the automated of laboratory based on three key parameters: health status, gender, weight. The integrates thermal imaging cameras AMG8833 monitoring status mice, object detection algorithms (YOLOv8) gender classification, load cell HX711 sensors weight measurement. integration these leverages advanced sensor fusion techniques to improve accuracy efficiency. Thermal detects physiological anomalies assess condition while identify characteristics real-time with high precision. Additionally, provide data further categorization. combined eliminates need manual intervention, non-invasive, efficient, scalable approach animal management. proposed performed evaluation through multiple test scenarios aimed at assessing classifying their was evaluated using dataset comprising over 6,722 images stored STASRG laboratory. results indicated that across parameters achieved 100% success rate. 86.67%, measurement exhibited difference approximately 0.1 gram. overall response time 19 seconds. demonstrates potential enhance workflows, minimize human error, promote welfare animals via automated, data-driven processes.

Язык: Английский

Intellimice Classifier: Towards Smart Object Detection and Classification of Laboratory Mice Using Multi-Sensor Integration DOI Open Access
Giva Andriana Mutiara,

Periyadi Mutiara,

Muhammad Rizqy Alfarisi

и другие.

Journal of Electrical and Electronic Engineering, Год журнала: 2025, Номер 13(1), С. 59 - 81

Опубликована: Фев. 27, 2025

Laboratory mice (Mus musculus) play a crucial role in scientific research, where accurate classification and sorting are essential for ensuring reliable experimental results. This study presents an intelligent multi-sensor system the automated of laboratory based on three key parameters: health status, gender, weight. The integrates thermal imaging cameras AMG8833 monitoring status mice, object detection algorithms (YOLOv8) gender classification, load cell HX711 sensors weight measurement. integration these leverages advanced sensor fusion techniques to improve accuracy efficiency. Thermal detects physiological anomalies assess condition while identify characteristics real-time with high precision. Additionally, provide data further categorization. combined eliminates need manual intervention, non-invasive, efficient, scalable approach animal management. proposed performed evaluation through multiple test scenarios aimed at assessing classifying their was evaluated using dataset comprising over 6,722 images stored STASRG laboratory. results indicated that across parameters achieved 100% success rate. 86.67%, measurement exhibited difference approximately 0.1 gram. overall response time 19 seconds. demonstrates potential enhance workflows, minimize human error, promote welfare animals via automated, data-driven processes.

Язык: Английский

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