A survey on enhancing the interoperability aspect of IoT based systems

Daliya, V. K.; Ramesh, T. K.

doi:10.1109/smarttechcon.2017.8358438

Cited by 8 publications

(1 citation statement)

References 4 publications

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“…Finally, the obtained knowledge is presented in stage 6. The data analysis and prediction if done meticulously can be very useful in telemedicine and remote monitoring of patients [6]. The use of machine learning in predictive analysis, data clustering and reinforcement learning is well known.…”

Section: Introductionmentioning

confidence: 99%

An Optimised Multivariable Regression Model for Predictive Analysis of Diabetic Disease Progression

Daliya

Ramesh

2021

IEEE Access

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With the advent of smart systems and smart IoT network all over the world leading to enormous amount of data generation; the right analysis and decision making based on the relevant data plays a crucial role. Various industries such as transportation, retail, healthcare etc. rely on analysis using this huge volumes of data for intelligent decision making. In smart healthcare system, accurate analysis of patients' data and prediction of diseases and medicine is important. To a great extent, fatalities can be avoided by timely recommendation of healthcare measures and immediate alert on emergency conditions. The use of machine learning algorithm for precise predictive analysis of data can be very promising in the field of healthcare. In this paper, optimised Multivariable Linear regression method is used to predict the diabetic disease progression of 442 patients based on various parameters such as age, gender, Body Mass Index and 6 different blood serum measurements. Here optimisation is performed using feature reduction and logarithmic transformation. The predicted output is found to be closely associated with actual output data with a Root Mean Square Error of 1.5 units; which indicates higher accuracy in comparison with the non-optimised model with the error of 54 units. There has also been a comparison with the results obtained from other state of the art regression methods, which proves that the proposed model exhibits maximum accuracy. This method can be used to provide promising medical advice to the patients on how to reduce the diabetic disease progression over a year by controlling various health parameters.

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Section: Introductionmentioning

confidence: 99%

An Optimised Multivariable Regression Model for Predictive Analysis of Diabetic Disease Progression

Daliya

Ramesh

2021

IEEE Access

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A systematic survey on internet of things: Energy efficiency and interoperability perspective

Rana

Singh

2020

Trans Emerging Tel Tech

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With the provision of rapid advancement in smart devices used in various technological fields exponentially increases the heterogeneity and energy consumption in internet of things (IoT). The technological leap in information and communication technology instigates the heterogeneity in smart devices, frameworks, architectures, communication technologies, and various industrial and nonindustrial applications. Therefore, a detailed taxonomy of IoT is proposed covering the diverse aspect of IoT lacking interoperability and energy efficiency. Existing research lacks the root causes of heterogeneity and energy consumption at the industrial and technological level. Keeping this in view, our research identified industrial integration and technological challenges. Moreover, we explore the effect on IoT devices when different types of energy harvesters are connected with IoT devices. Our comprehensive research addresses the various issues such as resource management, fog data analytics, energy consumption, heterogeneity, scalability, and the role of quality of service, data science, machine learning to accomplish interoperability and energy efficiency in IoT.

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IoT Based Real Time Vehicle Vital Parameter Monitoring and Analytics

Thodupunoori

Nair

2019

Advances in Intelligent Systems and Computing

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A survey on enhancing the interoperability aspect of IoT based systems

Cited by 8 publications

References 4 publications

An Optimised Multivariable Regression Model for Predictive Analysis of Diabetic Disease Progression

An Optimised Multivariable Regression Model for Predictive Analysis of Diabetic Disease Progression

A systematic survey on internet of things: Energy efficiency and interoperability perspective

IoT Based Real Time Vehicle Vital Parameter Monitoring and Analytics

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