Collaborative actuation of wireless sensor and actuator networks for the agriculture industry.

This paper investigates the deployment of collaborative estimation and actuation scheme of wireless sensor and actuator networks for the agriculture industry. In our proposed scheme, sensor nodes conduct a local estimation based on the Kalman filter for enhancing the estimation stability and further transmit data to the actuator nodes under a multi-rate transmission mode for enhancing the overall energy efficiency of the wireless network. Considering the mutual effect of related clusters, a collaborative actuation scheme of actuator nodes is integrated into our proposed scheme for improving the estimation accuracy and convergence speed. With an accurate estimation of the changes in the environmental parameters, combining the fuzzy neural network with the PID control algorithm, the actuator exerts reliable control over the environmental parameters. Performance evaluations and simulation analysis conducted based on the effects of temperature demonstrate the effectiveness of our proposed scheme in controlling the greenhouse environmental changes for in the agriculture industry.N/

Adaptive Fault Diagnosis of Motors Using Comprehensive Learning Particle Swarm Optimizer with Fuzzy Petri Net

This study proposes and applies a comprehensive learning particle swarm optimization (CLPSO) fuzzy Petri net (FPN) algorithm, which is based on the CLPSO algorithm and FPN, to the fault diagnosis of a complex motor. First, the transition confidence is replaced by a Gaussian function to deal with the uncertainty of fault propagation. Then, according to the Petri net principle, a competition operator is introduced to improve the matrix reasoning. Finally, a CLPSO-FPN model for motor fault diagnosis is established based on the motor failure mechanism and fault characteristics. The CLPSO algorithm is used to generate the system parameters for fault diagnosis and to improve the adaptability and accuracy of fault diagnosis. This study considers the example of a three-phase asynchronous motor. The results show that the proposed algorithm can diagnose faults in this motor with satisfactory adaptability and accuracy compared with the traditional FPN algorithm. By establishing the system model, the fault propagation process of motors can be accurately and intuitively expressed, thus improving the fault treatment and equipment maintenance of motors

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Networking Architecture and Key Technologies for Human Digital Twin in Personalized Healthcare: A Comprehensive Survey

Digital twin (DT), refers to a promising technique to digitally and accurately represent actual physical entities. One typical advantage of DT is that it can be used to not only virtually replicate a system's detailed operations but also analyze the current condition, predict future behaviour, and refine the control optimization. Although DT has been widely implemented in various fields, such as smart manufacturing and transportation, its conventional paradigm is limited to embody non-living entities, e.g., robots and vehicles. When adopted in human-centric systems, a novel concept, called human digital twin (HDT) has thus been proposed. Particularly, HDT allows in silico representation of individual human body with the ability to dynamically reflect molecular status, physiological status, emotional and psychological status, as well as lifestyle evolutions. These prompt the expected application of HDT in personalized healthcare (PH), which can facilitate remote monitoring, diagnosis, prescription, surgery and rehabilitation. However, despite the large potential, HDT faces substantial research challenges in different aspects, and becomes an increasingly popular topic recently. In this survey, with a specific focus on the networking architecture and key technologies for HDT in PH applications, we first discuss the differences between HDT and conventional DTs, followed by the universal framework and essential functions of HDT. We then analyze its design requirements and challenges in PH applications. After that, we provide an overview of the networking architecture of HDT, including data acquisition layer, data communication layer, computation layer, data management layer and data analysis and decision making layer. Besides reviewing the key technologies for implementing such networking architecture in detail, we conclude this survey by presenting future research directions of HDT

Emerging Communications for Wireless Sensor Networks

Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide

Fog computing for sustainable smart cities: a survey

The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, specially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g. network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build an sustainable IoT infrastructure for smart cities. In this paper, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges towards implementing them, so as to shed light on future research directions on realizing Fog computing for building sustainable smart cities

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Avoin alustakehitys IEEE 802.15.4 -standardin mukaisessa langattomassa automaatiossa

This doctoral dissertation focuses on open source platform development in wireless automation under IEEE 802.15.4 standard. Research method is empirical. A platform based approach, which targets to the design of a generic open source sensor platform, was selected as a design method. The design targets were further focused by interviewing the experts from the academia and industry. Generic and modular sensor platform, the UWASA Node, was developed as an outcome of this process. Based on the implementation results, a wireless sensor and actuator network based on the UWASA Node was a feasible solution for many types of wireless automation applications. It was also possible to interface it with the other parts of the system. The targeted level of sensor platform genericity was achieved. However, it was also observed that the achieved level of genericity increased the software complexity. The development of commercial sensor platforms, which support IEEE 802.15.4 sensor networking, has narrowed down the role of open source sensor platforms, but they are not disappearing. Commercial software is usually closed and connected to a specified platform, which makes it unsuitable for research and development work. Even though there exits many commercial WSN solutions and the market expectations in this area are high, there is still a lot of work to do before the visions about Internet of Things (IoT) are fulfilled, especially in the context of distributed and locally centralized operations in the network. In terms of control engineering, one of the main research issues is to figure out how the well-known control techniques may be applied in wireless automation where WSN is part of the automation system. Open source platforms offer an important tool in this research and development work.Tämä väitöskirja käsittelee avointa alustakehitystä IEEE 802.15.4 -standardin mukaisessa langattomassa automaatiossa. Tutkimusmenetelmä on empiirinen. Työssä sovelletaan alustaperustaista suunnittelutapaa, joka tähtää yleiskäyttöisen avoimen anturialustan kehittämiseen. Suunnittelun tavoitteita tarkennettiin haastattelemalla alan asiantuntijoita teollisuudesta ja yliopistomaailmasta. Tuloksena suunniteltiin ja toteutettiin anturialusta, the UWASA Node. Implementointituloksista voidaan vetää johtopäätös, että anturialustan tavoiteltu yleiskäyttöisyystaso saavutettiin. Toisaalta saavutettu yleiskäyttöisyystaso lisäsi alustan ohjelmistoarkkitehtuurin monimutkaisuutta. Kaupallisten IEEE 802.15.4 -standardia tukevien anturialustojen tulo markkinoille vähentää avointen anturialustojen käyttöä, mutta ne eivät ole katoamassa. Kaupalliset ohjelmistot ovat tyypillisesti suljettuja ja sidoksissa tiettyyn alustaan, mikä tekee niistä sopimattomia tutkimus- ja tuotekehityskäyttöön. Vaikka nykyään on saatavilla useita kaupallisia langattomia anturi- ja toimilaiteverkkoja, vaaditaan vielä paljon työtä ennen kun kaikki esineiden Internetiin (Internet of Things) liittyvät visiot voidaan toteuttaa. Tämä koskee erityisesti langattomassa anturi- ja toimilaiteverkossa hajautetusti tai paikallisesti toteutettavia toimintoja. Säätötekniikan näkökulmasta keskeinen kysymys on, miten tunnettuja säätömenetelmiä tulee soveltaa langattomassa automaatiossa, jossa langaton anturi- ja toimilaiteverkko on osa automaatiojärjestelmää. Avoimet anturialustat ovat tärkeä työkalu sen selvittämisessä.fi=vertaisarvioitu|en=peerReviewed