scholarly journals Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1600 ◽  
Author(s):  
Zheng Yao ◽  
Sentang Wu ◽  
Yongming Wen
Keyword(s):  
Internet Of Things ◽  
Social Cognitive ◽  
Simulation Experiment ◽  
Unmanned Vehicles ◽  
The Internet ◽  
Unmanned Vehicle ◽  
Aerial Vehicle ◽  
Multi Agent ◽  
The Internet Of Things ◽  
Cognitive Optimization

Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, formation principles, formation scale, unmanned vehicle formation safety distance, and formation evaluation indicators are taken into consideration. The application of the IoT enables the optimization of distributed computing. To ensure the reliability of the formation algorithm, the convergence of MAHSCO has been proved. Finally, computer simulation and actual unmanned aerial vehicle (UAV) formation generation flight generating four typical formations are carried out. The result of the actual UAV formation generation flight is consistent with the simulation experiment, and the algorithm performs well. The MAHSCO algorithm based on the IoT is proved to be able to generate formations that meet the mission requirements quickly and accurately.

An Architecture to Implement the Internet-of-Things using the Prometheus Methodology

2020 ◽  
pp. 609-629
Author(s):  
Bogdan Manațe ◽  
Florin Fortiş ◽  
Philip Moore
Keyword(s):  
Internet Of Things ◽  
Rapid Expansion ◽  
The Internet ◽  
Data Types ◽  
Diverse Range ◽  
Complex Agent ◽  
Multi Agent ◽  
Complex Scenario ◽  
The Internet Of Things ◽  
Prometheus Methodology

The rapid expansion of the Internet of Things (IoT) will generate a diverse range of data types that needs to be handled, processed and stored. This paper aims to create a multi-agent system that suits the needs introduced by the IoT expansion, thus being able to oversee the Big Data collection and processing and also to maintain the semantic links between the data sources and data consumers. In order to build a complex agent oriented architecture, we have assessed the existing agent oriented methodologies searching for the best solution that is not bound to a specific programming language of framework, and it is flexible enough to be applied in such a divers domain like IoT. As complex scenario, the proposed approach has been applied to medical diagnosis and motoring of mental disorders.

scholarly journals A Smart Microcontroller Architecture for the Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1821 ◽  
Author(s):  
Zhenyu Wu ◽  
Kai Qiu ◽  
Jianguo Zhang
Keyword(s):  
Internet Of Things ◽  
Real World ◽  
Simulation Experiment ◽  
Cloud Model ◽  
Experimental Results ◽  
The Internet ◽  
Complex Problems ◽  
Logic Control ◽  
The Internet Of Things ◽  
Embedded Intelligence

The interoperations of endpoint devices are generally achieved by gateways in Internet of Things (IoT) systems. However, the gateways mainly focus on networking communication, which is lack of data logic control capabilities. The microcontrollers with embedded intelligence could work as an intermediate device to help the interconnections of the endpoint devices. Moreover, they could help control the endpoint devices. In this paper, a microcontroller architecture with intelligent and scalable characteristics is proposed. The intelligence means that the microcontroller could control the target endpoint devices by its logical circuits, and the scalability means that the microcontroller architecture could be easily extended to deal with more complex problems. Two real world industrial implementations of the proposed architecture are introduced. The implementations show that the microcontroller is important to provide the intelligent services to users in IoT systems. Furthermore, a simulation experiment based on the cloud model is designed to evaluate the proposed method. The experimental results demonstrate the effectiveness of the proposed architecture.

scholarly journals A Multi-Agent System for Data Fusion Techniques Applied to the Internet of Things Enabling Physical Rehabilitation Monitoring

2020 ◽  
Vol 11 (1) ◽  
pp. 331
Author(s):  
Héctor Sánchez San Blas ◽  
André Sales Mendes ◽  
Francisco García Encinas ◽  
Luís Augusto Silva ◽  
Gabriel Villarubia González
Keyword(s):  
Internet Of Things ◽  
Recovery Process ◽  
Feedback System ◽  
Easy Access ◽  
The Internet ◽  
Multi Agent System ◽  
Agent System ◽  
Healthcare Facilities ◽  
Multi Agent ◽  
The Internet Of Things

There are more than 800 million people in the world with chronic diseases. Many of these people do not have easy access to healthcare facilities for recovery. Telerehabilitation seeks to provide a solution to this problem. According to the researchers, the topic has been treated as medical aid, making an exchange between technological issues such as the Internet of Things and virtual reality. The main objective of this work is to design a distributed platform to monitor the patient’s movements and status during rehabilitation exercises. Later, this information can be processed and analyzed remotely by the doctor assigned to the patient. In this way, the doctor can follow the patient’s progress, enhancing the improvement and recovery process. To achieve this, a case study has been made using a PANGEA-based multi-agent system that coordinates different parts of the architecture using ubiquitous computing techniques. In addition, the system uses real-time feedback from the patient. This feedback system makes the patients aware of their errors so that they can improve their performance in later executions. An evaluation was carried out with real patients, achieving promising results.

scholarly journals A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management

Drones ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 12
Author(s):  
Naomi A. Ubina ◽  
Shyi-Chyi Cheng
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Low Cost ◽  
Labor Cost ◽  
Unmanned Vehicles ◽  
The Internet ◽  
Aquaculture Farm ◽  
Quality Water ◽  
Vehicle Technologies ◽  
The Internet Of Things

This paper aims to provide an overview of the capabilities of unmanned systems to monitor and manage aquaculture farms that support precision aquaculture using the Internet of Things. The locations of aquaculture farms are diverse, which is a big challenge on accessibility. For offshore fish cages, there is a difficulty and risk in the continuous monitoring considering the presence of waves, water currents, and other underwater environmental factors. Aquaculture farm management and surveillance operations require collecting data on water quality, water pollutants, water temperature, fish behavior, and current/wave velocity, which requires tremendous labor cost, and effort. Unmanned vehicle technologies provide greater efficiency and accuracy to execute these functions. They are even capable of cage detection and illegal fishing surveillance when equipped with sensors and other technologies. Additionally, to provide a more large-scale scope, this document explores the capacity of unmanned vehicles as a communication gateway to facilitate offshore cages equipped with robust, low-cost sensors capable of underwater and in-air wireless connectivity. The capabilities of existing commercial systems, the Internet of Things, and artificial intelligence combined with drones are also presented to provide a precise aquaculture framework.

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