ML4IoT: A framework to orchestrate machine learning workflows on internet of things data
Internet of Things (IoT) applications generate vast amounts of real-time data. Temporal
analysis of these data series to discover behavioural patterns may lead to qualified …
analysis of these data series to discover behavioural patterns may lead to qualified …
[PDF][PDF] Orchestrating development lifecycle of machine learning based IoT applications: A survey
Machine Learning (ML) and Internet of Things (IoT) are complementary advances: ML
techniques unlock complete potentials of IoT with intelligence, and IoT applications …
techniques unlock complete potentials of IoT with intelligence, and IoT applications …
Orchestrating the development lifecycle of machine learning-based IoT applications: A taxonomy and survey
Machine Learning (ML) and Internet of Things (IoT) are complementary advances: ML
techniques unlock the potential of IoT with intelligence, and IoT applications increasingly …
techniques unlock the potential of IoT with intelligence, and IoT applications increasingly …
IoT data analytics in dynamic environments: From an automated machine learning perspective
With the wide spread of sensors and smart devices in recent years, the data generation
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …
IOTWC: Analytic hierarchy process based Internet of Things workflow composition system
Internet of Things (IoT) allows the creation of virtually endless connections into a global
array of distributed intelligence. However, the design, development, and deployment of IoT …
array of distributed intelligence. However, the design, development, and deployment of IoT …
Toward deep transfer learning in industrial internet of things
Machine learning techniques have been widely adopted to assist in data analysis in a
variety of Internet of Things (IoT) systems. To enable flexible use of trained learning models …
variety of Internet of Things (IoT) systems. To enable flexible use of trained learning models …
Machine learning and internet of things applications in enterprise architectures: Solutions, challenges, and open issues
The rapid growth of the Internet of Things (IoT) has led to its widespread adoption in various
industries, enabling enhanced productivity and efficient services. Integrating IoT systems …
industries, enabling enhanced productivity and efficient services. Integrating IoT systems …
A Dataflow-Oriented Approach for Machine-Learning-Powered Internet of Things Applications
The rise of the Internet of Things (IoT) has led to an exponential increase in data generated
by connected devices. Machine Learning (ML) has emerged as a powerful tool to analyze …
by connected devices. Machine Learning (ML) has emerged as a powerful tool to analyze …
iprocess: Enabling iot platforms in data-driven knowledge-intensive processes
Abstract The Internet of Things (IoT), the network of physical objects augmented with Internet-
enabled computing devices to enable those objects sense the real world, has the potential …
enabled computing devices to enable those objects sense the real world, has the potential …
From cloud down to things: An overview of machine learning in internet of things
With the numerous Internet of Things (IoT) devices, the cloud-centric data processing fails to
meet the requirement of all IoT applications. The limited computation and communication …
meet the requirement of all IoT applications. The limited computation and communication …