Diagnosis of lameness via data mining algorithm by using thermal camera and image processing method in Brown Swiss cows

Coşkun, Gizem; Şahin, Özcan; Delialioğlu, Rabia Albayrak; Altay, Yasin; Aytekin, İ̇brahim

doi:10.1007/s11250-023-03468-9

Cited by 11 publications

(5 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In research by Du et al [5], they optimized a high-dimensional design space for the supercritical CO 2 recompression cycle (abbreviated as sCO 2 -RC) by using deep learning and data mining techniques of machine learning to measure decisional variables for optimizing systems. Moreover, Coşkun et al [6] used both integrating lameness scores and some image parameters by using a data mining technique to process thermal images with the ImageJ program in order to measure the early detection of lameness in Brown Swiss cattle. Clancy et al [7] provided a method to decide a methodology to enable data-driven quality management in order to reduce the waste from manufacturing processes using data mining techniques.…”

Section: Research Motivationmentioning

confidence: 99%

Identification of the Yield Rate by a Hybrid Fuzzy Control PID-Based Four-Stage Model: A Case Study of Optical Filter Industry

Chen,

Hung,

Lee

et al. 2024

Axioms

View full text Add to dashboard Cite

With the vigorous development of emerging technology and the advent of the Internet generation, high-speed Internet and fast transmission 5G wireless networks contribute to interpersonal communication. Now, the Internet has become popular and widely available, and human life is inseparable from various experiences on the Internet. Many base stations and data centers have been established to convert and switch from electrical transmission to optical transmission; thus, it is entering the new era of optical fiber networks and optical communication technologies. For optical communication, the manufacturing of components for the purpose of high-speed networks is a key process, and the requirement for the stability of its production conditions is very strict. In particular, product yields are always low due to the restriction of high-precision specifications associated with the limitations of too many factors. Given these reasons, this study proposes a hybrid fuzzy control-based model for industry data applications to organize advanced techniques of box-and-whisker plot method, association rule, and decision trees to find out the determinants that affect the yield rate of products and then use the fuzzy control Proportional-Integral-Derivative (PID) method to manage the determinants. Since it is unrealistic to test the real machine online operation at the manufacturing stage, the simulation software supersedes this for improved results, and a mathematical neural network is used to verify the given data to confirm whether its result is similar to that of the simulation. The study suggests that excessive temperature differentials between substrate and cavity can lead to low yields. It suggests using fuzzy control technology for temperature management, which could increase yield, reduce labor costs, and accelerate the transition to high-speed networks by mass-producing high-precision optical filters.

show abstract

Section: Research Motivationmentioning

confidence: 99%

Identification of the Yield Rate by a Hybrid Fuzzy Control PID-Based Four-Stage Model: A Case Study of Optical Filter Industry

Chen,

Hung,

Lee

et al. 2024

Axioms

View full text Add to dashboard Cite

show abstract

“…They are based on the detection of physicochemical and biological changes in milk or udders or on the assessment of milk or blood biomarkers associated with mastitis (Džermeikaitė et al, 2023). To detect lameness, animal limb movement is assessed, along with imaging, using the Fog computing, Classification, and regressive tree (CART) XGBoost algorithm (Coşkun et al, 2023;Kavlak et al, 2023). Swine flu, on the other hand, is assessed using the Optical flow algorithm by measuring animals' mobility and direction (Neethirajan, 2020).…”

Section: Precision Livestock Farming and Crop Productionmentioning

confidence: 99%

“…Ukrainian Black Sea Region Agrarian Science, 27(3), 9 Анотація. Сільське господарство відіграє життєво важливу роль у виробництві продуктів харчування, використанні ресурсів та забезпеченні зайнятості, але стикається з проблемами, пов'язаними зі зростанням населення, зміною клімату та нестачею продовольства.…”

Section: Acknowledgmentsunclassified

Agriculture in the face of new digitization technologies

Wrzecińska,

Czerniawska-Piątkowska,

Kowalewska

et al. 2023

UBSRAS

View full text Add to dashboard Cite

Agriculture plays a vital role in food production, resource utilization, and employment but faces challenges from population growth, climate change, and food shortages. The development of information technology has significantly contributed to the industry's development, and modern technologies such as artificial intelligence, the Internet of Things, computer vision, and machine learning have revolutionized agricultural practices. The purpose of this review is to explore the adoption of digital technologies in agriculture, with a specific focus on their application in livestock breeding. Through the examination of current literature and the utilization of various research methods, this review contributes to the existing knowledge in the field. It is established that the latest information tools allow collecting, analysing data, automating tasks and supporting decision-making, which leads to increased agricultural efficiency, resource management and sustainable development. It has been proven that modern technologies play a crucial role in increasing agricultural production, improving the efficiency of livestock and crop production. These technologies include devices and sensors, data analytics and decision support systems, as well as systems for overall farm productivity assessment. Precision technologies in agriculture, thanks to automation, sensors and machine learning, allow farmers to monitor animal health, optimise feed consumption, detect diseases at early stages and increase overall productivity. IT solutions in agriculture facilitate data processing, visualisation and decision-making, leading to lower costs, greater efficiency and improved food security. The study provides practical insights for farmers and other agricultural stakeholders who can benefit from accurate information, real-time monitoring and automated processes through the integration of modern technologies, ultimately improving agricultural practices and sustainability

show abstract

“…Sin embargo, es necesario desarrollar sistemas que registren mediciones fiables y repetibles de comportamientos capaces de indicar el estado de bienestar de los animales (O' Kane et al 2016, Barwick et al 2020. El uso de acelerómetros instalados en los animales para predecir la cojera han sido usados y ya existen sistemas comerciales en la industria lechera (Barwick et al 2020), adicionalmente, se han empleado sistemas con imágenes térmicas para el diagnóstico de esta patología en ganado bovino (Coşkun et al 2023).…”

Section: Diagnósticounclassified