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

Recent Advancements of Light-Emitting Diodes in Dairy Industries DOI

Pranavi KS,

Shaik Basha, A. Chattopadhyay

и другие.

Trends in Food Science & Technology, Год журнала: 2025, Номер unknown, С. 105018 - 105018

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

SMART DAIRY FARMING: ENHANCED EFFICIENCY, PRODUCTIVITY AND ANIMAL WELFARE THROUGH THE INTERNET OF THINGS AND CLOUD INTEGRATION DOI Creative Commons
Manzar Abbas, Ghulam Abbas,

S. Jaffery

и другие.

The Journal of Animal and Plant Sciences, Год журнала: 2025, Номер 1, С. 18 - 35

Опубликована: Янв. 8, 2025

Dairy industry faces numerous challenges today and, in the future, including labor shortage, stemming from economic pressure due to high cost and insufficient returns, evolving marketing dynamics. In order cope with these challenges, integration of advance technologies such as automation data analytics is indispensable. The Internet Things (IoT) has enabled development “smart” devices installed sensors smart collars, wearables, thermometer, hygrometer, air quality detectors for efficient sustainable dairy farming. Moreover, vast volume generated by IoT necessitates cloud computing effective handling. However, this presents challenges; particular, overload superfluous communication noise. To address this, pre-processing trimming services gateways, networks, fog have been employed. livestock farming, CoT revolutionized real-time monitoring, advanced care, in-time ovum pick-up, vitro fertilization, embryo transfer, artificial insemination, milk production, gene selection. Through sensors, regarding an animal’s health (e.g., body temperature, level reproductive hormones, vaginal pH), behavior, environment facilitated animal welfare practices. CoT’s cloud-based infrastructure enables comprehensive analysis, leading improved veterinary early disease detection, insightful research into diverse species’ Ultimately, signify a paradigm shift transcending mere offer holistic, data-driven approach that harmonizes productivity welfare. By leveraging innovations, sector poised achieve growth saving 178% on feed pushing, 44.05% milking, 121.97% cleansing, 126.2% herd 109.3% analyzing forecasting. This study falls under umbrella UNO’s goals development. Keywords: Things, computing, intelligent breeding, management, farm management

Язык: Английский

Процитировано

0

Smart technologies to improve the management and resilience to climate change of livestock housing: a systematic and critical review DOI Creative Commons
Francesco Bordignon, Giorgio Provolo, Elisabetta Riva

и другие.

Italian Journal of Animal Science, Год журнала: 2025, Номер 24(1), С. 376 - 392

Опубликована: Янв. 24, 2025

Язык: Английский

Процитировано

0

Smart Practices in Modern Dairy Farming in Bangladesh: Integrating Technological Transformations for Sustainable Responsibility DOI Creative Commons
Mohammad Shamsuddoha,

Tasnuba Nasir

Administrative Sciences, Год журнала: 2025, Номер 15(2), С. 38 - 38

Опубликована: Янв. 27, 2025

The current Bangladeshi dairy sector faces many problems related to sustainability indicators from economic, social, and environmental perspectives. In this circumstance, they must combine cutting-edge innovation overcome growing concerns technical revolutions become smart farms. This study analyzes how farmers might use technologies in their sub-processes determine the benefits of achieving additional productivity efficiency. paper examines precision livestock farming, information analytics, alternative energy sources reduce hazards increase resource Using like artificial intelligence (AI), machine learning (ML), robotics (RPA), Internet Things (IoT), data system dynamics, simulation modeling can assist improving results. Analyzing developing country case studies best practices reveals crucial answers for reconciling stewardship operational dynamics method builds a model finds projected results before implementing it real life. findings provide considerable waste reduction gains through technological deployments. creates two scenarios ‘current’ ‘technology-adopted’ processes examine transformational sustainable practices. A was adopted technology deployment organize comprehensive strategy that blends sustainability. ends with recommendations policymakers create resilient environmentally friendly operation secure sector’s long-term viability transforming technologies. Future farms follow practical, technical, policy, as well improve processes, such farm concepts available academia dairy-developed countries.

Язык: Английский

Процитировано

0

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

Процитировано

0