A data-driven intelligent planning model for UAVs routing networks in mobile Internet of Things

2021 ◽  
Author(s):  
Dian Meng ◽  
Yang Xiao ◽  
Zhiwei Guo ◽  
Alireza Jolfaei ◽  
Lanxia Qin ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Mobile Internet ◽  
Data Driven ◽  
Planning Model ◽  
Intelligent Planning

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

scholarly journals Adaptive Routing Strategy Based on Improved Double Q-Learning for Satellite Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jian Zhou ◽  
Xiaotian Gong ◽  
Lijuan Sun ◽  
Yong Xie ◽  
Xiaoyong Yan
Keyword(s):  
Internet Of Things ◽  
Adaptive Routing ◽  
Mobile Internet ◽  
Secure Routing ◽  
Q Value ◽  
Average Delay ◽  
Q Learning ◽  
Data Packets ◽  
Routing Strategy ◽  
Node Status

Satellite Internet of Things (S-IoT), which integrates satellite networks with IoT, is a new mobile Internet to provide services for social networks. However, affected by the dynamic changes of topology structure and node status, the efficient and secure forwarding of data packets in S-IoT is challenging. In view of the abovementioned problem, this paper proposes an adaptive routing strategy based on improved double Q-learning for S-IoT. First, the whole S-IoT is regarded as a reinforcement learning environment, and satellite nodes and ground nodes in S-IoT are both regarded as intelligent agents. Each node in the S-IoT maintains two Q tables, which are used for selecting the forwarding node and for evaluating the forwarding value, respectively. In addition, the next hop node of data packets is determined depending on the mixed Q value. Second, in order to optimize the Q value, this paper makes improvements on the mixed Q value, the reward value, and the discount factor, respectively, based on the congestion degree, the hop count, and the node status. Finally, we perform extensive simulations to evaluate the performance of this adaptive routing strategy in terms of delivery rate, average delay, and overhead ratio. Evaluation results demonstrate that the proposed strategy can achieve more efficient and secure routing in the highly dynamic environment compared with the state-of-the-art strategies.

Applications of Cloud-Based Internet of Things

2021 ◽  
pp. 65-84
Author(s):  
Nipun R. Navadia ◽  
Gurleen Kaur ◽  
Harshit Bhardwaj ◽  
Taranjeet Singh ◽  
Aditi Sakalle ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Business Model ◽  
Data Driven ◽  
The Internet ◽  
Cloud Infrastructure ◽  
Business Decisions ◽  
Goods And Services ◽  
Cloud Network ◽  
The Internet Of Things

Cloud storage is a great way for companies to fulfill more of their data-driven needs and excellent technology that allows the company to evolve and grow at a faster pace, accelerating growth and providing a flexible forum for developers to build useful apps for better devices to be developed over the internet. The integration of cloud computing and the internet of things creates a scalable, maintainable, end-to-end internet of things solution on the cloud network. By applying the infrastructure to the real universe, it generates sources of insight. Cloud computing and IoT are separate technology but are closely associated and are termed as ‘cloud-based IoT' as IoT has the ability to create intelligent goods and services, gather data that can affect business decisions and probably change the business model to boost success and expansion, and cloud infrastructure can be at the heart of all IoT has to deliver.

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