Online Velocity Control and Data Capture of Drones for the Internet of Things: An Onboard Deep Reinforcement Learning Approach

2020 ◽  
pp. 0-0
Author(s):  
Kai Li ◽  
Wei Ni ◽  
Eduardo Tovard ◽  
Abbas Jamalipour
Keyword(s):  
Reinforcement Learning ◽  
Internet Of Things ◽  
Data Capture ◽  
The Internet ◽  
Learning Approach ◽  
Velocity Control ◽  
The Internet Of Things

A Novel Multihop Range-Free Localization Based on Kernel Learning Approach for the Internet of Things

2015 ◽  
Vol 87 (1) ◽  
pp. 269-292 ◽  
Author(s):  
Xiaoyong Yan ◽  
Zhong Yang ◽  
Aiguo Song ◽  
Wankou Yang ◽  
Yu Liu ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Kernel Learning ◽  
The Internet ◽  
Learning Approach ◽  
The Internet Of Things ◽  
Range Free

scholarly journals Deep Reinforcement Learning for Cybersecurity Applications

2021 ◽  
Vol 10 (12) ◽  
pp. 32-38
Author(s):  
Alex Mathew
Keyword(s):  
Reinforcement Learning ◽  
Internet Of Things ◽  
Rapid Growth ◽  
Smart Devices ◽  
The Internet ◽  
Complex Problems ◽  
The Internet Of Things ◽  
Security Concern

There has been a rapid growth of the devices connected to the internet in the last decade for the various internet (IoT) of things applications. The increase of these smart devices has posed a great security concern in the internet of things ecosystem. The internet of things ecosystem must be protected from these threats. Reinforcement learning has been proposed by the cybersecurity professionals to provide the needed security tools for securing the IoT system since it is able to interact with the environment and learn how to detect the threats. This paper presents a comprehensive research on cybersecurity threats to the IoT system applications. The RL algorithms are also presented to understand the attacks on the IoT. Reinforcement learning is widely employed in cybersecurity because it can learn on its own experience by investigating and capitalizing on the unknown ecosystem, this enables it solve many complex problems. The RL capabilities on dealing with cybercrime challenges are also exploited in this paper.

Multimedia system and database simulation based on internet of things and cloud service platform

2020 ◽  
pp. 1-12
Author(s):  
Zhang Caiqian ◽  
Zhang Xincheng
Keyword(s):  
Internet Of Things ◽  
Cloud Service ◽  
Multimedia System ◽  
The Internet ◽  
Multimedia Database ◽  
Cloud Platform ◽  
Service Platform ◽  
Device Management ◽  
Cloud Service Platform ◽  
The Internet Of Things

The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance.

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