A Review on Machine Learning Trends, Application and Challenges in Internet of Things

Reddy, R. Ravinder; Mamatha, Ch.; Reddy, Ravinithesh

doi:10.1109/icacci.2018.8554800

Cited by 13 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It is somewhat challenging to make decisions on cross-cutting issues such as HCN management due to the different types of resources used, such as heterogeneous networks, several types of sensors and devices, and the vast number of data collection sources, among others. Based on these reasons, reaching agreements on standards is a continuous improvement issue [ 199 , 200 ]. Furthermore, integrating decision-making and machine learning is an exciting matter due to the large amount of data, processing capacities, and the range of techniques that must adjust to needs under data uncertainty.…”

Section: Discussionmentioning

confidence: 99%

“…However, as fog computing continues to face several new challenges, such as business models, security, privacy, and scalability, further research on these areas may be required [4]. [199,200]. Furthermore, integrating decision-making and machine learning is an exciting matter due to the large amount of data, processing capacities, and the range of techniques that must adjust to needs under data uncertainty.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Decision-Making under Uncertainty for the Deployment of Future Hyperconnected Networks: A Survey

Alzate-Mejía

Santos-Boada

Amazonas

2021

Sensors

View full text Add to dashboard Cite

Among the several emerging dimensioning, control and deployment of future communication network paradigms stands out the human-centric characteristic that creates an intricate relationship between telematics and human activities. The hard to model dynamics of user behavior introduces new uncertainties into these systems that give rise to difficult network resource management challenges. According to this context, this work reviews several decision-making computational methods under the influence of uncertainties. This work, by means of a systematic literature review, focuses on sensor-based Internet of Things scenarios such as Smart Spaces and Industry 4.0. According to our conclusions, it is mandatory to establish a means for modeling the human behavior context in order to improve resource assignment and management.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Decision-Making under Uncertainty for the Deployment of Future Hyperconnected Networks: A Survey

Alzate-Mejía

Santos-Boada

Amazonas

2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Multiple simultaneous and symbiotic advances in the areas of sensor technology, ubiquitous computing, distributed computing, connected devices (e.g., smartphones, wearables, augmented/ virtual reality devices), and machine learning have facilitated novel systems of health measurement and intervention (Reddy et al 2018). Models of human behavior can now be developed and deployed on any number of connected devices to create a digital data source or activate an action directly on the device.…”

Section: Digital Measurement Of Human Behaviormentioning

confidence: 99%

Machine Learning and the Digital Measurement of Psychological Health

Galatzer‐Levy

Onnela

2023

Annual Review of Clinical Psychology

View full text Add to dashboard Cite

Since its inception, the discipline of psychology has utilized empirical epistemology and mathematical methodologies to infer psychological functioning from direct observation. As new challenges and technological opportunities emerge, scientists are once again challenged to define measurement paradigms for psychological health and illness that solve novel problems and capitalize on new technological opportunities. In this review, we discuss the theoretical foundations of and scientific advances in remote sensor technology and machine learning models as they are applied to quantify psychological functioning, draw clinical inferences, and chart new directions in treatment.

show abstract

“…Bagaimana agar pengguna yakin bahwa data yang digunakan adalah data yang valid dan aktual. Protokol dari IoT yang beragam juga merupakan isu dan tantangan tersendiri dalam sebuah penelitian yang melibatkan IoT dan machine learning [5], [22], [26], [27] [28].…”

Section: Isu Dan Tantangan Machine Learning Dan Iotunclassified

A Survey on Machine learning and IoT

Hardini

2019

ITEJ

View full text Add to dashboard Cite

Internet of Things is an intelligence devices that can connect to any other devices. Based on that ability to connect and its intelligence, it makes people to create an intelligence device and capable to learn like human brain. To accomplish that goal, machine learning is the solution. Combination between machine learning and IoT generate a revolution in human life and application industry. The combination also generate new trend in market. Therefore, in this paper will be discuss about machine learning including machine learning technique and algorithm and also discuss about IoT including architecture and elements. Then in this paper will discuss about some researches that have already done that combine IoT with machine learning approach, including issue and challenge in those researches.

show abstract

A Review on Machine Learning Trends, Application and Challenges in Internet of Things

Cited by 13 publications

References 14 publications

Decision-Making under Uncertainty for the Deployment of Future Hyperconnected Networks: A Survey

Decision-Making under Uncertainty for the Deployment of Future Hyperconnected Networks: A Survey

Machine Learning and the Digital Measurement of Psychological Health

A Survey on Machine learning and IoT

Contact Info

Product

Resources

About