The Industrial Internet of Things (IIoT) is bringing evolution with remote monitoring, intelligent analytics, and control of industrial processes. However, as the industrial world is currently in its initial stage of adopting full-stack development solutions with IIoT, there is a need to address the arising challenges. In this regard, researchers have proposed IIoT architectures based on different architectural layers and emerging technologies for the end-to-end integration of IIoT systems. In this paper, we review and compare three widely accepted IIoT reference architectures and present a state-of-the-art review of conceptual and experimental IIoT architectures from the literature. We identified scalability, interoperability, security, privacy, reliability, and low latency as the main IIoT architectural requirements and detailed how the current architectures address these challenges by using emerging technologies such as edge/fog computing, blockchain, SDN, 5G, Machine Learning, and Wireless Sensor Networks (WSN). Finally, we discuss the relation between the current challenges and emergent technologies and present some opportunities and directions for future research work.
Abstract:The intention of this research is to establish a relationship between dairy cattle diseases with various non-invasive sensors for the development of a health monitoring system. This paper expands on the conference paper titled "Sensor technology for animal health monitoring" published in the International Journal on Smart Sensing and Intelligent Systems (s2is) for the proceedings of International Conference on Sensing Technology (ICST) 2014. This paper studies and explores particular characteristics of dairy cattle's health and behavioural symptoms. The aim is to consider the nature of the diseases a cow may have and relate it with one or many sensors that are suitable for accurate measurement of the behavioural changes. The research uses ontological relationship mapping or ontology matching to integrate heterogeneous databases of diseases and sensors and explains it in detail. This study identifies the sensors needed to determine illnesses in a dairy cow and how they would be beneficial for the development of non-invasive, wearable, smart, dairy cattle health monitoring system to be placed on the cows' neck. It also explains how the primary sensors identified by this research can be used to forecast cattle health in a simple, basic manner. The scope of this paper is limited to the discussion about the non-invasive, wearable sensors that are needed to determine the cattle diseases. We focused only on non-invasive sensors because they are easy to install on cows and no training is required for them to be installed as compared to invasive sensors. Development of such a system and its evaluation is not in the scope of this paper and is left for our next paper.
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