WSMS: Wearable Stress Monitoring System Based on IoT Multi-Sensor Platform for Living Sheep Transportation

Cui, Yan; Zhang, Mengjie; Li, Jun; Luo, Hui; Zhang, Xiaoshuan; Fu, Zetian

doi:10.3390/electronics8040441

Cited by 27 publications

(16 citation statements)

References 41 publications

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“…Given that welfare is impacted by a multitude of circumstances, one of the goals of the PLF technique is to analyse and summarize huge amounts of data in order to provide technical expertise with a specific solution. This is why specific technology has been developed that combines minimally or non-invasive temperature sensors inside and outside the animal, as well as accelerometers and sound detectors [130], to create algorithms and machine learning capable of detecting animal welfare on farms [131] and during transport [132].…”

Section: Animal Performances Feed Monitoring and Animal Behaviourmentioning

confidence: 99%

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

Morrone

Dimauro

Gambella

et al. 2022

Sensors

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Precision livestock farming (PLF) has spread to various countries worldwide since its inception in 2003, though it has yet to be widely adopted. Additionally, the advent of Industry 4.0 and the Internet of Things (IoT) have enabled a continued advancement and development of PLF. This modern technological approach to animal farming and production encompasses ethical, economic and logistical aspects. The aim of this review is to provide an overview of PLF and Industry 4.0, to identify current applications of this rather novel approach in different farming systems for food producing animals, and to present up to date knowledge on the subject. Current scientific literature regarding the spread and application of PLF and IoT shows how efficient farm animal management systems are destined to become. Everyday farming practices (feeding and production performance) coupled with continuous and real-time monitoring of animal parameters can have significant impacts on welfare and health assessment, which are current themes of public interest. In the context of feeding a rising global population, the agri-food industry and industry 4.0 technologies may represent key features for successful and sustainable development.

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Section: Animal Performances Feed Monitoring and Animal Behaviourmentioning

confidence: 99%

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

Morrone

Dimauro

Gambella

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Consequently, it is a primary concern to protect the sheep from death during transportation and damage that occurs because of the excessive amount of stress in the goat or sheep. A wearable stress monitoring system (WSMS) has been proposed to monitor the stress signs remotely during sheep transportation [58]. The designed system record and transmit the sensed data efficiently during sheep transportation and minimizes the effects of stress load.…”

Section: ) Stress Monitoringmentioning

confidence: 99%

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

et al. 2022

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The Internet of Things (IoT) is an emerging paradigm that is transforming real-world things (objects) into smarter devices. IoT is applicable to a variety of application domains including healthcare, smart grid, and agriculture. This domain has started revolutionizing the agriculture industry by providing smart solutions for precision farming, greenhouse management, and livestock monitoring. This article aims to present a comprehensive survey on the role of IoT in the Livestock field by categorizing and synthesizing existing research work in this area. To this end, a detailed discussion has been provided on IoT network infrastructure, topologies and platforms employed for livestock management. In addition, a list of communication protocols and connections of IoT-based livestock systems with relevant technologies have also been explored. Furthermore, numerous IoT-based livestock monitoring, controlling, and tracking applications have been discussed. Apart from this, it also analyses distinct security issues in IoT-based livestock field and developed a collaborative security model to detect and minimize the security risk. Lastly, pertinent open research challenges in the domain of IoT-based livestock management have been presented with future research directions.

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“…Cui et al [30] in their findings propose a non-invasive stress monitoring system with having sensor units; capable to measure temperature using Infrared Temperature Measurement (ITM), PhotoPlethysmoGram (PPG), and Inertial Measurement Units. The focus is to continuously monitor stress signs in sheep during transportation.…”

Section: Related Workmentioning

confidence: 99%

A Facial and Vocal Expression Based Comprehensive Framework for Real-Time Student Stress Monitoring in an IoT-Fog-Cloud Environment

et al. 2022

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In this era of digital and modern education, the existence of psychological stress on students cannot be denied. The surplus aggregation of the stress may lead to different problems like a decline in student grade (performance), an increase of violence in behavior, and even more extreme cases. The advent of Information Communication and Technology (ICT) and its tools opened the doors to innovations that facilitate interactions among things and humans. In this utilization, the paper proposes a novel, IoT-aware student-centric stress monitoring and real-time alert generating framework to predict student stress index in a particular context. In elaboration, we respectively used extended VGG16, Bidirectional Long Short Term Memory network (Bi -LSTM), and Multinomial Naïve Bayes techniques to generate the scores of emotions from student facial expressions, speech pitch, and content of student speech at the cloud layer. Specifically, the model aims to classify the stress events as normal or abnormal on basis of the overall emotion of the students' physiological data readings. The activation of the abnormal event in case of higher values for negative emotions like stress, fear, sadness, disgust, etc.; a stern alert is sent to the student, coordinators, and caretakers. This proposed framework will ultimately be a great tool that will support the education institutions, students, their parents, and guardians to get a real-time alert on students' overall emotions. The prior knowledge of stress accumulated on the mind of the student will help in overcoming major problems of student dropout, decrease student academic performance, and tackle the stress situation that may lead to the student attempting suicide.

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WSMS: Wearable Stress Monitoring System Based on IoT Multi-Sensor Platform for Living Sheep Transportation

Cited by 27 publications

References 41 publications

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

A Facial and Vocal Expression Based Comprehensive Framework for Real-Time Student Stress Monitoring in an IoT-Fog-Cloud Environment

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