Integration of Cloud Computing with Internet of Things. Группа авторов

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Low-end devices are low-cost sensors, actuators, RFID tags, Arduino, OpenMote, etc. with resource-crunch, communication, low energy, and processing abilities. It aims for better integration and communication among several heterogeneous devices in advanced IoT platforms. Network interoperability [20] The network remains is multi-service, multi-vendor, largely distributed and, heterogeneous. It facilitates the better transfer of data among several smart systems using efficient networking systems. It can alleviate issues such as addressing, resource optimization, routing, security, QoS, mobility support, etc. Syntactical interoperability [21] It allows interoperation of the format and structure of the data during communication among heterogeneous IoT devices, entities, domains, systems, etc. It includes the syntactic set rules in the same or some different grammar It is significant in the case of disparities between the encode and decode rules involving the source and the end-user. Semantic interoperability [22] It allows the meaningful exchange of knowledge and information among agents, services, and applications. It is significant when the automatic interoperation of IoT information or data models is not materialized due to the difficulties in descriptions and understandings of operational resources or procedures. Platform interoperability [21] The need arises with the advancement of diverse and versatile operating systems, programming languages, data structures, IoT architectures, access mechanisms, etc. Different mechanisms are developed for efficient data management involving several IoT platforms. Similarly, cross-platform and cross-domain in different heterogeneous domains are addressed.

      1.5.3 Semantic Interoperability (SI) Security

      1.5.4 Semantic IoT vs Machine Learning

      The Machine Learners (MLs) are essential components in the field of pattern recognition, classification, and regression analysis. Over the years, several MLs have been efficiently applied in the field of power management, speech, and speaker identification, emotion recognition, etc. [28–32]. The integration and coordination of SIoT with MLs has been often discussed in the literature involving pervasive and ubiquitous computing, ambient intelligence, wireless sensor networks, artificial intelligence, human–computer interaction, cognitive science, etc. The multi-layered back-propagating Neural Networks have been effectively utilized to identify human movements such as sitting, walking, running, etc. in smart home applications. Similarly, identification ML models such as the Naive Base Classifiers, Bayesian networks, Support Vector Machines, K-Nearest Neighbor, Hidden Markov Model, etc. have been efficiently applied in the field of context-aware search systems, home automation, navigation systems, etc. in IoT domains.

      Internet of Things (IoT) application in smart homes or cities, workplace, agriculture, transportation, healthcare, artificial intelligence, Cognitive Science, Blockchain, Micro-service Architecture, Robotic Process, Automation, Quantum Computing are all concepts gaining attention in recent years in public, private, and corporate worlds due to media publicity and efficacy. With its growing interest on everybody and everyday applications, it helps people enjoy self-driving cars, use wearables for efficiency and timely assistance, plan taxi services or business meetings, and so on. The IoT application domains have covered all sectors, industries, and every sphere of life today, thus thrive to boost the financial health of the world. It has begun to shape the future world with a unique perspective never seen before in the history of humanity. With these intuitions, this paper elaborates several factors concerned to IoT world that rule and dominate the world today in the current scenario.

       References

      1. Das, S.K. and Palo, H.K., Internet of Things (IoT) Application in Green Computing: An Overview, in: Advances in Greener Energy Technologies, pp. 85–102, Springer, Singapore, 2020.

      2. Evans, D., The internet of things: How the next evolution of the internet is changing everything, vol. 1, pp. 1–11, CISCO white paper, USA, 2011.

      3. Philip, V., Suman, V.K., Menon, V.G., Dhanya, K.A., A review on latest internet of things based healthcare applications. Int. J. Inf. Secur., 15, 1, 248, 2017.

      4. Palo, H.K. and Mohanty, M.N., Wavelet-based feature combination for recognition of emotions. Ain Shams

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