scholarly journals A Survey of Using Swarm Intelligence Algorithms in IoT

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1420 ◽  
Author(s):  
Weifeng Sun ◽  
Min Tang ◽  
Lijun Zhang ◽  
Zhiqiang Huo ◽  
Lei Shu
Keyword(s):  
Swarm Intelligence ◽  
Big Data Analysis ◽  
Wireless Sensor ◽  
Future Trends ◽  
Distribution Characteristics ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wireless Telecommunications ◽  
Research Problems ◽  
The Internet Of Things

With the continuing advancements in technologies (such as machine to machine, wireless telecommunications, artificial intelligence, and big data analysis), the Internet of Things (IoT) aims to connect everything for information sharing and intelligent decision-making. Swarm intelligence (SI) provides the possibility of SI behavior through collaboration in individuals that have limited or no intelligence. Its potential parallelism and distribution characteristics can be used to realize global optimization and solve nonlinear complex problems. This paper reviews representative SI algorithms and summarizes their applications in the IoT. The main focus consists in the analysis of SI-enabled applications to wireless sensor network (WSN) and discussion of related research problems in the WSN. Also, we concluded SI-based applications in other IoT fields, such as SI in UAV-aided wireless network. Finally, possible research prospects and future trends are drawn.

scholarly journals Wireless Sensor Network Synchronization for Precision Agriculture Applications

Agriculture ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 89 ◽  
Author(s):  
Alexandros Zervopoulos ◽  
Athanasios Tsipis ◽  
Aikaterini Georgia Alvanou ◽  
Konstantinos Bezas ◽  
Asterios Papamichail ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Low Cost ◽  
Time Correlation ◽  
Wireless Sensor ◽  
Network Synchronization ◽  
Transmission Delays ◽  
Intelligent Decision Making ◽  
Cost System ◽  
Intelligent Decision ◽  
Synchronized Measurements

The advent of Internet of Things has propelled the agricultural domain through the integration of sensory devices, capable of monitoring and wirelessly propagating information to producers; thus, they employ Wireless Sensor Networks (WSNs). These WSNs allow real time monitoring, enabling intelligent decision-making to maximize yields and minimize cost. Designing and deploying a WSN is a challenging and multivariate task, dependent on the considered environment. For example, a need for network synchronization arises in such networks to correlate acquired measurements. This work focuses on the design and installation of a WSN that is capable of facilitating the sensing aspects of smart and precision agriculture applications. A system is designed and implemented to address specific design requirements that are brought about by the considered environment. A simple synchronization scheme is described to provide time-correlated measurements using the sink node’s clock as reference. The proposed system was installed on an olive grove to assess its effectiveness in providing a low-cost system, capable of acquiring synchronized measurements. The obtained results indicate the system’s overall effectiveness, revealing a small but expected difference in the acquired measurements’ time correlation, caused mostly by serial transmission delays, while yielding a plethora of relevant environmental conditions.

scholarly journals AI-powered Energy Internet Towards Carbon Neutrality: Challenges and Opportunities

2021 ◽  
Author(s):  
Chaojie Li
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Energy Supply ◽  
Big Data Analysis ◽  
Energy Industry ◽  
Energy Internet ◽  
Carbon Neutrality ◽  
Intelligent Decision Making ◽  
Intelligent Decision

From self-driving vehicles, voice recognition based virtual digital assistants, smart thermostats to recommendation systems, Artificial Intelligence (AI) is becoming a crucial part of the carbon neutral society that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. The emergence of AI initiates numerous opportunities to transform energy industry to AI-powered smart system which can revolutionize traditional approaches of creativity thinking, strategical operation, and solution seeking, especially for accelerating carbon neutrality of our society. This survey provides a comprehensive overview of fundamental principles that underpin applications of big data analysis in Energy Internet (EI), such as smart energy supply and consumption, smart health and Fintech. Next, we focus on intelligent decision-making for the energy industry and inform the state-of-the-art by thoroughly reviewing the literature. Subsequently, cybersecurity issues for AI system related to EI are discussed with recent advancements from vulnerability analysis of AI system to differential privacy and to blockchain based security technology. To our knowledge, this is one of the first academic, peer-reviewed works to provide a systematic review of AI applications for EI research and initiatives in terms of big data analysis, intelligent decision-making and AI related cybersecurity These initiatives were systematically classified into different groups according to the field of application, methodology and contribution Afterwards, potential challenges, limitations for existing research and opportunities for future directions are discussed, ranging from emerging explainable AI, to localized multi-energy marketplaces, self-driving electric vehicle charging and e-mobility. This paper can help us understand how to build smart cities and critical infrastructure for a climate-changed world towards the UN’s sustainable development goals.

Intelligence in MAS-Based Distributed Learning Environments

2011 ◽  
pp. 115-145
Author(s):  
Chunsheng Yang
Keyword(s):  
Research And Development ◽  
Learning Environments ◽  
Distributed Learning ◽  
Learning Systems ◽  
Student Modeling ◽  
Future Trends ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
E Learning ◽  
Coordination And Collaboration

This chapter first addresses the issue of the importance of intelligence in MAS-based DLEs. Then, it stresses that there are three main intelligent competencies in MAS-based DLEs: intelligent decision-making support, coordination and collaboration of the agents in MAS, and student modeling for personalization and adaptation in learning systems. It also describes in detail how to apply relevant AI techniques, including the introduction of AI techniques and their state-of-the-art application in the e-learning domain. Finally, future trends in the research and development of intelligence for MAS-based DLEs are discussed.

scholarly journals AI-powered Energy Internet Towards Carbon Neutrality: Challenges and Opportunities

2021 ◽  
Author(s):  
Chaojie Li
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Energy Supply ◽  
Big Data Analysis ◽  
Energy Industry ◽  
Energy Internet ◽  
Carbon Neutrality ◽  
Intelligent Decision Making ◽  
Intelligent Decision

From self-driving vehicles, voice recognition based virtual digital assistants, smart thermostats to recommendation systems, Artificial Intelligence (AI) is becoming a crucial part of the carbon neutral society that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. The emergence of AI initiates numerous opportunities to transform energy industry to AI-powered smart system which can revolutionize traditional approaches of creativity thinking, strategical operation, and solution seeking, especially for accelerating carbon neutrality of our society. This survey provides a comprehensive overview of fundamental principles that underpin applications of big data analysis in Energy Internet (EI), such as smart energy supply and consumption, smart health and Fintech. Next, we focus on intelligent decision-making for the energy industry and inform the state-of-the-art by thoroughly reviewing the literature. Subsequently, cybersecurity issues for AI system related to EI are discussed with recent advancements from vulnerability analysis of AI system to differential privacy and to blockchain based security technology. To our knowledge, this is one of the first academic, peer-reviewed works to provide a systematic review of AI applications for EI research and initiatives in terms of big data analysis, intelligent decision-making and AI related cybersecurity These initiatives were systematically classified into different groups according to the field of application, methodology and contribution Afterwards, potential challenges, limitations for existing research and opportunities for future directions are discussed, ranging from emerging explainable AI, to localized multi-energy marketplaces, self-driving electric vehicle charging and e-mobility. This paper can help us understand how to build smart cities and critical infrastructure for a climate-changed world towards the UN’s sustainable development goals.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

Sign in / Sign up

Export Citation Format

Share Document