Cloud Computing and Big Data for Cognitive IoT
Dr. Elena Verdu (Lead GE)
Universidad Internacional de la Rioja
Dr. Yuri Vanessa Nieto
Universidad Nacional Abierta y a Distancia UNAD,
Dr. Nasir Saleem
Faculty of Engineering and Technology, Gomal University,
Dera Ismail Khan, Pakistan
The cognitive Internet of Things (Cognitive IoT) is one of the concepts that is accelerating in recent days with high technological advancements in various sectors. Cognitive IoT system is often integrated with other technologies such as cloud computing and big data to deliver better results. These advancements have high decision-making capacity which sometimes, is better than that of humans. The evolution of Cognitive IoT in recent years is enormous. It is also applied in all the domains ranging from smart wearables to healthcare and communication sectors. As the number of devices increases the technologies associated with them are also getting upgraded. Other than cloud computing and big data, Cognitive IoT also has the applications of deep learning, machine learning, data analytics and other programming languages. This process of integration of various technologies together is very useful for research and study purposes.
In the era of big data, various computing systems are benefitted from the growth of data analytics and data sciences. In Cognitive IoT, big data is used in computers, smart homes, smartphones, wearable devices and social networks. The special feature of big data for gathering, storing, processing and analysing complex data makes it very useful for the cognitive IoT to predict and mimic human intelligence with the help of a stored database. This feature also increases the sensing capability of cognitive IoT. Additionally, they are also implemented in supply chain markets, businesses, automobiles, electrical grids and smart farming. The operational efficiency of big data equips the cognitive IoT to predict the complex relationship between humans and the environment, businesses and markets, demand and supply, etc. Similarly, the usage of cloud computing in the cognitive IoT is also making a huge impact on its application. Firstly, cloud computing is used in the lifecycle management of cognitive IoT enhanced devices. This reduces the support and management costs of the devices. Secondly, cloud computing improves the portability of cognitive IoT by enabling the interoperability of devices. This helps in monitoring and processing data with connected devices. Thirdly, the infrastructure and platform model of cloud computing can be used for increasing critical data and reducing the maintenance cost of operating systems. Thus, most of the leading tech giants are deploying cloud computing for better utilization of cognitive IoT. The continuous generation of data in cloud computing enhanced cognitive IoT is stored and analysed with big data tools. They predict the risks and failures as well as the outcomes of a certain process. This integrated technology is not only used in the service sector but also in the industrial and manufacturing sector to monitor machinery. Therefore, the flexible and reliable nature of big data and cloud computing has great potential if merged with cognitive IoT.
Potential topic of interest include but not limited to:
• Evolution of big data with cognitive IoT
• Cognitive IoT infrastructure based on big data
• Decision making in cognitive IoT using big data analytics
• Role of machine learning algorithms for better utilisation of cognitive IoT
• Recent trends in data analytics for computing algorithms
• Hybrid optimisation using cloud computing models
• Application of cloud computing in sensors and healthcare
• Smart grids using cloud computing and cognitive IoT
• Trends in the computing cloud services in cognitive IoT
• Increasing of critical data using cloud computing and big data tools.
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