Monitoring And Control Systems Design


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In addition to the socio-economic developments, the population is also seeking higher living standards. Despite their work, they have no spare time to care for their toys. The main aim of this project is to develop smart systems to monitor the aquaponic ecosystem and provide environmental and ecological protection for ornamental fish and hydroponic plants. Initially, a comprehensive description was provided of the importance and functions of the system, and then architecture, hardware components, and software development were included. The system includes three components, namely information gathering, mobile transmission, and intelligent interactive applications.

Control System Monitoring for Industrial Equipments

In this section, a mobile monitoring system is proposed for industrial equipment, with the main objective to provide real-time efficient sensor data analysis and control capabilities. This paper reviews the design of a wireless monitoring system for industrial equipment. The proposed solution facilitates centralized management of available information from different areas, allowing the users to check the status and gain detailed insights into their operations at any given moment. Underlying functionality is based on a hierarchical approach that involves three major components: Wireless Sensors Network (WSN), aggregator device, and cloud server. Interaction between these elements takes place via two types of protocols: ZigBee Smart Energy profile as well as HTTP/XML using JSON objects as transport mechanism over Internet Protocol version 6 (IPv6).

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The IoT Will Transform the Global Business Industry

This paper, written by Ira Tanenbaum, discusses what is known as the Internet of Things (IoT) and how it will transform the global business industry over time. The concepts and components that make up IoT technology are also discussed in detail. Tanenbaum provides examples of uses for the technology and explains why companies should invest now to reap potential benefits later on. There is a comparison made between IoT and earlier technologies such as AI, ML, and Big Data.

Periodically Synchronized Clocks of IoT Devices

As the number of interconnected devices within the Internet of Things (IoT) grows, there is a need for them to communicate and coordinate their activities. This coordination requires synchronization among all networked devices. Timekeeping is an integral part of any coordination mechanism because time is required to make decisions about when events should happen. Thus, achieving accurate timekeeping with synchronized clocks on IoT devices becomes increasingly important for the efficient coordination of data exchanges between these devices. The paper addresses this problem by proposing the Periodically Synchronized Clock (PSC) scheme that facilitates accurate timing measurements on resource-constrained wireless sensor networks (WSNs).

The Challenges of M2M Heterogeneous Networks

Due to the rapid growth of mobile devices and sensors that operate in resource-constrained environments, machine-to-machine (M2M) communication is becoming ubiquitous. Heterogeneous networks (HetNets), which are composed of conventional network nodes (e.g., macro access points) and low-power wireless access points (e.g., picocells, femtocells, relay nodes), are an enabling technology for M2M communications; however, they also pose unique challenges to traditional networking protocols such as medium access control (MAC). This paper examines these challenges by studying both existing MAC layer solutions for HetNets and proposing new approaches in this area.

The Power of Mobile Crowd Sensing

Mobile crowdsensing, which is defined as geographically distributed users equipped with mobile devices participating in sensing tasks, plays an important role in many applications. By leveraging the power of mobile crowdsensing, we can provide location-aware information services to communities, increase the accuracy of geographic data annotations for social media contents, and enhance geosocial networking. In this paper, we survey recent advances in mobile crowdsensing that can be applied to achieve these goals.

The Design And Implementation Of A Packet Forwarding Module For Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of small low-power sensors embedded within unattended environments. WSNs have emerged as a very popular platform used to monitor physical phenomena for industrial applications. Despite their numerous applications, the limited resources of sensor nodes (e.g., memory, energy) pose unique problems in terms of network optimization. The paper presents a case study that uses OpenWSN; an open-source software framework for embedded wireless network research and simulation to design and implement a packet forwarding module for WSNs.

Virtual Machine Scheduling Algorithm For Cloud Computing Using A Multi-objective Genetic Algorithm

The need to develop virtual machines on cloud computing platforms has become inevitable due to its numerous advantages over traditional physical machines. Recently, many scheduling algorithms have been developed to deploy virtual machines on heterogeneous distributed systems efficiently; however, they are mainly designed based on a priority queueing model which is not suitable for real deployments of these systems. This paper presents a novel scheduling algorithm for cloud computing by leveraging a genetic algorithm. This approach optimizes the scheduling of virtual machines on a heterogeneous distributed system in terms of minimizing job completion time, maximizing fairness, and minimizing overhead costs simultaneously.

The Role Of Software Defined Radio In Cognitive Radio Networks

The vision of cognitive radio (CR) networks is to leverage spectrum knowledge through deploying radio resources intelligently to improve spectral efficiency. To this end, CR networks need access to unlicensed bands which can be achieved by dynamically allocating the available licensed bands to secondary users (SUs). However, SUs may not always use these allocated bands due to their intermittent operation. This paper proposes an architecture that integrates software-defined radio (SDR) with CR networks to enable SUs to access these secondary bands efficiently.

Tracking Multiple Multi-rotor UAVs With Active Localization And Sequential Monte Carlo Methods

Unmanned autonomous vehicles (AUVs) or unmanned aerial vehicles (UAVs) have been widely used for more than a decade due to their widespread benefits and attractive features such as reduced risk and damage, extended mission life, and wider accessibility. However, there is always a need for accurate localization of these vehicles to enhance the performance of tasks assigned by human operators. This paper presents collaborative localization algorithms that support multi-vehicle missions with high accuracy as well as reduce network latency. The proposed approach first localizes airborne vehicles using an active algorithm called DIRCM (Distributed and Interconnected Rooftop Compatible Localization) and then uses a sequential Monte Carlo localization algorithm to localize ground vehicles.

User-aware Content Delivery In Social Media: A Survey

With the rapid growth of social media, such as Facebook and Twitter, people can easily share multimedia content like text, video, photos with their networks via web interfaces or mobile applications. Recently many studies have shown that these contents are more popular when they are shared by users who have a high reputation in terms of several followers/friends. This paper reviews the existing literature about user-aware content delivery in social media from three different aspects including techniques for ranking social media contents based on the influence of users on service providers, load balancing among multiple distribution servers for content delivery in social media, and techniques based on the influence of users in peer-to-peer (P2P) networks.

This paper reviews the existing literature about user-aware content delivery in social media from three different aspects including techniques for ranking social media contents based on the influence of users on service providers, load balancing among multiple distribution servers for content delivery in social media, and techniques based on the influence of users in peer-to-peer (P2P) networks.

Design, Installation, Testing & Commissioning of Control & Monitoring Systems

The Electric Utility industry is witnessing a paradigm shift in the way power generation, distribution, and transmission are carried out. The traditional concept of centralized grid control with high voltage AC power has given way to a distributed system where digital controls are moving from the utilities to substations for local control. Power generation has become more diversified with renewable energy sources playing an important role in future planning. These changes need an upgrade of the existing electrical infrastructure which includes not only updating utility poles but also revision & up-gradation of the entire network including protection relays, metering systems, etc.,

Real-Time Detection And Classification Of Airport Landings Using Single-Stage Transonic Anemometer Radar

Airport surveillance radar provides airport management with information about weather conditions that affect airplane operations. This information is used by airport management during the decision-making process to determine whether an airplane can land or take off under current conditions, and helps to assist in making decisions regarding airport operations. Since airport surveillance radar data are frequently utilized for airport decision support systems (DSS), there is a growing need for DSSs capable of providing real-time reporting of meteorological parameters with high accuracy so that airplane managers can make accurate decisions at all times.

To achieve this goal, this paper proposes a novel single-stage transonic anemometer (STATCOM) radar system for remote airport weather surveillance monitoring applications which utilizes the Doppler frequency shift principle. The proposed system collects wind speed data by processing Doppler frequency swept by the proposed radar and detects landings of aircraft by comparing the processed data with typical landing pattern profiles (LPPs). Subsequently, the system classifies detected landings into two groups: normal and rejected. For this application, a low-complexity classification algorithm has been selected for real-time implementation on an embedded processor. The characterization and testing results of the proposed radar system will be discussed in detail.

Computer-Aided Prevention Of Cyberbullying In Facebook

This paper proposes a system that uses machine learning to detect possible cases of cyberbullying before they happen using graphs showing friendship relations between users, posts, and comments. This information is visualized through heatmaps that show bullying risk levels for different places on periods chosen by analysts, which allows them to choose times in which actions must be taken to prevent a possible case of cyberbullying.

A Comprehensive Framework For Multi-layer Multimedia Big Data Analytics In Cloud Computing Environment

In the era of big data, scalable distributed scalable cloud computing systems have been developed and deployed in many domains. The capability of such systems to process extremely large multimedia datasets at scale is becoming a key differentiator for these systems. The design and development of such processing frameworks need to also consider various aspects including cost, adaptability with diverse data types and sources, middleware support for dynamic resource allocation, user interface requirements, etc., This paper proposes a multi-layer framework that targets scalability and adaptability while considering other considerations by modern users and developers. An end-to-end system is developed that addresses the challenges of real-world big data analytics problems with appropriate tradeoffs.

Design. Implementation And Evaluation Of A Heuristic Algorithm For The Single Machine Scheduling Problem With Release Dates

The single machine scheduling problem with release dates is a well-known NP-hard combinatorial optimization problem. The objective of this research work is to develop an effective heuristic algorithm for the single machine scheduling problem with release dates. A hybrid genetic algorithm was used, which combined both crossover and mutation techniques for producing smart offspring generations to solve it efficiently. An extensive set project schedule dataset was collected from various universities, which consists of 1239 projects with 33904 tasks and 51961 activity on time (actual) values were used in this paper. The proposed heuristic algorithm outperformed other algorithms reported in the literature in terms of computational time and optimality.

Service-Oriented Architecture For Cloud Computing

Cloud computing is a form of distributed computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. It has become an emerging technology that provides economical, reliable, secure, and On-demand accessible IT resources to the user community. Unfortunately, cloud computing still suffers from security issues due to its lack of built-in protection mechanisms against cyber attacks. Because cloud applications are inherently multi-tenant, they have to share the same physical infrastructure with other coexisting applications hosted on it. Therefore, protecting each application or data service becomes a challenging task since all tenants run on the same shared environment. This paper presents several proposed solutions to address the above-mentioned problem through applying Security Service Oriented Architecture (SSOA) for cloud computing.

Performance Evaluation Of Voip Over Ieee 802.11 Wireless Networks

This paper presents a model to simulate Ip Multimedia Subsystem (IMS) over IEEE 802.11 (Wi-Fi) mesh networks with different packet dropping probabilities at access points (APs). The proposed system consists of an application layer that is responsible for carrying out real-time multimedia traffic and the data link layer that is used for transporting packets over individual APs in wireless mesh networks. The performance metrics considered are voice quality, packet delivery ratios, mean end-to-end delay time, and jitter within each call. Three types of parameters were tested to evaluate the network behaviour under consideration: A single user with multiple voice channels, multiple users with a single voice channel each, and multiple users with one voice channel assigned to each. The proposed model can be used for different applications on IEEE-802.11 wireless mesh networks.

Spatial Data Mining Using K Means Clustering Algorithm

This paper presents a novel approach to find out the spatial pattern of data points using a k means clustering algorithm. For that purpose, various geolocation techniques are used for representing the data points as 3D coordinates data in the Euclidean space of three dimensions (x, y, and z). This Geolocation representation is considered as the input feature vector of the given dataset which is treated as observations or instances of some classifier where Euclidean distance between two points is computed by considering z coordinate values. The Euclidean distance matrix is computed using the data given in Geolocation representation and then normalized for better clustering results. After that, a k means clustering algorithm is applied to identify the spatial clusters of classifier data points.

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