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1st international Scientific conference on Telecommunications, computing and Control, TELECCON 2019

1st International Scientific Conference on Telecommunication...

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1st international Scientific conference on Telecommunications, computing and Control, TELECCON 2019

ISBN: (纸本)9789813366312

The proceedings contain 46 papers. The special focus in this conference is on Telecommunications, computing and Control. The topics include: Solving Multicriteria Optimization Problem for an Oil Refinery Plant;methods and Techniques for Increasing the Accuracy of Continuous Non-invasive Blood Pressure Measurement Under Dynamic Loads;computer Modeling of Robust Control of Vibrationless Movement of Multi-mode Flexible structures;feature-Based Plant Seedlings Classification;medical Training Simulation in Virtual Reality;application of the Hybrid Model to Numerical Modeling of the Urban Transport Network Topology;Synchronization Scheme for UWB Wireless sensor Network System;the Deep Survival Forest and Elastic-Net-Cox Cascade Models as Extensions of the Deep Forest;an Explanation Method for Siamese Neural Networks;detection and Prediction of Safety Faults in Inter-Device Networks Applying a Set of Data-Driven Methods;Hierarchical Multi-agent System for Production Control Using KPI Reconciliation;semi-supervised Learning for Medical Image Segmentation;developing a New Generation of Reconfigurable Heterogeneous distributed High Performance computing System;Usage of a BART Algorithm and Cognitive Services to Research Collaboration Platforms;a Computer-Aided Diagnosis System in the Diagnosis of Multiple Sclerosis;Predicting students’ Performance on MOOC Using Data Mining Algorithms;on the Implementation of the Planar3D Model Using the Explicit Time Integration Scheme and the statistical Front Tracking Method;fast Fourier Transform in Planar3D Model Using an Explicit Numerical Integration Scheme;employee Performance Analytics Approach Based on Anomaly Detection in User Activity;deep Predictive Control;development of an Algorithm for Determining the Railway Tracks on Video Image;on the Computational Complexity of Deep Learning Algorithms.

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Rise of Diversity of Internet of Things (IoT): A Review

Rise of Diversity of Internet of Things (IoT): A Review

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2025 international conference on Intelligent Control, computing and Communications, IC3 2025

作者： Sobana, P. Yaiaman, Gummagatta Vybhavi Kumar, A. Pradeep Karthi, S. Almusawi, Muntather Rani, Hema Sethu Institute of Technology Department of Computer Science Engineering Pulloor Tamil Nadu Kariapatti626115 India Gokaraju Rangaraju Institute of Engineering and Technology Department of Cse Telangana Hyderabad India Cmr College of Engineering & Technology Department of Ece Telanagana Hyderabad India Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil nadu Chennai India College of technical engineering The Islamic University Department of computers Techniques engineering Najaf Iraq Centre for Managament studies Gitarattan International Business School Delhi India

ISBN: (纸本)9798331527495

It has been established for a long time and has evolved correspondingly that actuators and sensor systems may be connected to the internet for the purpose of continuously monitoring and controlling biological phenomena. The term 'Internet of Things (IoT)' was first used to combine these methods into a coherent framework a little more than a decade earlier. The IoT based idea has evolved along with science, adopting new vocabulary that is suited for technical advancements and many applications sectors. The IoT has undergone modifications since its inception, and this study examines studies on how technical advancements have transformed it as well and encouraged the emergence of modified terms appropriate for certain fields. A three separate study of the literature was done using games companies and classification data warehouses. First step involved looking for proposed changes on the Iot devices principle & evaluating them to compute the similarity, disparities, and functionality that enable us to generate a number of links its progression. The 1st step involved identifying and briefly assessing the much more common names handed to it IoT for multiple areas. As underpinning innovation continues to advance and software update areas are put out, the research supports the assertion that a consensus on the IoT concept is still not established. With information and information solutions playing an important role in the panorama, recent developments have been somewhat restrained and its variants on possible applications are distinct. © 2025 ieee.

关键词： Labeled data

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Aligning AI-Led Smart Manufacturing with SDGs for Poverty Reduction

Aligning AI-Led Smart Manufacturing with SDGs for Poverty Re...

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Humanitarian Technology conference (KHI-HTC), ieee Karachi Section

作者： Muhammad Abrar-Ul-Haq Jayendira P Sankar Farheen Akram Gazi Md Nurul Islam Hafiz Abid Mahmood Malik Kashif Akram Department of Economics & Finance College of Business Administration University of Bahrain Zallaq Bahrain College of Administrative and Financial Sciences University of Technology Bahrain Salmabad Bahrain Graduate School of Business Universiti Tun Abdul Razak Kuala Lumpur Malaysia Knight Foundation School of Computing and Information Sciences Florida International University Miami USA Institute of Business Management and Administration Sciences The Islamia University of Bahawalpur Bahawalpur Pakistan

This study explores the intersection of smart manufacturing and the Sustainable Development Goals (SDGs) from a poverty reduction perspective. Smart manufacturing refers to the integration of advanced technologies, such as automation, artificial intelligence, and data analytics, into the manufacturing sector to improve productivity, efficiency, and sustainability. The SDGs, adopted by the United Nations in 2015, provide a comprehensive framework to address global challenges, including poverty eradication. This study examines how smart manufacturing can reduce poverty by aligning with the SDGs. It investigates the potential of smart manufacturing technologies to create employment opportunities, enhance income levels, and improve living conditions in low-income communities. By leveraging advanced technologies, smart manufacturing can facilitate the transformation of traditional industries, enable the growth of small and medium-sized enterprises (SMEs), and promote inclusive economic development. The study employs a multidisciplinary approach, drawing on literature from the fields of engineering, economics, and sustainable development. It explores case studies from various regions and industries to provide empirical evidence of the impact of smart manufacturing on poverty reduction. Also, it examines the challenges and barriers that need to be addressed to ensure that the benefits of smart manufacturing are equitably distributed and reach those most in need. The findings of this study contribute to both academia and policymaking. They provide insights into how smart manufacturing can be harnessed to achieve the SDGs, particularly the goal of poverty reduction. The study highlights the importance of technological innovation and its potential to create inclusive and sustainable economic growth. It also offers recommendations for policymakers, industry stakeholders, and development organizations on how to leverage smart manufacturing to address poverty and promote sustain

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HGraph: Parallel and distributed Tool for Large-Scale Graph Processing 1

HGraph: Parallel and Distributed Tool for Large-Scale Graph ...

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1st international conference on Artificial Intelligence and Data Analytics, CAIDA 2021

作者： Adoni, Wilfried Yves Hamilton Tarik, Nahhal Krichen, Moez El Byed, Abdeltif International University of Casablanca Hassan II University of Casablanca Casablanca Morocco Hassan II University of Casablanca Faculty of Science Casablanca Morocco University of Sfax Faculty of CSIT Albaha University KSA ReDCAD Laboratory Sfax Tunisia

ISBN: (纸本)9780738131771

Graph are ubiquitous because the fields of application are varied. Well-known examples are social networks, biological networks and path-finding in road networks. Real-world graphs processing is very challenging because of 4V characteristics related to big data. They are huge to process them on single-node and the time complexity is exponential. Unfortunately, due to the lack of research, only a few systems are able to ensure the storage and quick processing of large-scale graphs. In this paper, we propose HGraph, a parallel and distributed tool which handles large-scale graphs. HGraph is build on top of Hadoop and Spark frameworks. The proposed tool provides high scalability and is adapted to easily implement algorithms for various graph problems. Experimental tests performed on real-world graphs showed that HGraph is reliable and achieves significant gain time over the state of the art of graph processing systems. © 2021 ieee.

关键词： Big data

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Enhanced Bandwidth of Hexagonal Slotted UWB Textile Antenna sensor for Breast Cancer Detection System

Enhanced Bandwidth of Hexagonal Slotted UWB Textile Antenna ...

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Communication Engineering and Emerging Technologies (ICoCET), ieee international conference on

作者： Noor Syahirah Kamaruddin Hasliza A Rahim Samir Salem Omair Al-Bawri Faculty of Electronic Engineering & Technology Universiti Malaysia Perlis Arau Perlis Malaysia Compart Systems Technologies Sdn Bhd Kulim Kedah Malaysia Centre of Excellence for Advanced Communication Engineering (ACE) Kangar Perlis Malaysia Universiti Kebangsaan Malaysia Selangor Malaysia

ISBN: (数字)9798331504144

ISBN: (纸本)9798331504151

Breast cancer is the most common disease among women and has become one of the leading causes of death in women worldwide. Early breast cancer detection is very crucial to attain an optimum medical treatment. This paper presents a hexagonal slotted Ultra-Wideband (UWB) textile antenna for breast cancer detection systems. The proposed antenna has a dimension of $44\times 38\text{mm}_systems^systems$ , with a substrate made of felt material characterized by a relative permittivity, $\varepsilon_{r}$ of 1.44, a loss tangent, $tan\delta$ of 0.044, and a thickness, $h$ of 1.5 mm. The radiating element and ground plane of the antenna are using ShieldIt Super and the thickness is set to be 0.17 mm. The proposed antenna sensor consists of a hexagonal slotted monopole antenna and a partial ground plane. The partial ground plane technique is used to enhance the performance as well as to tune in the desired frequency range. The antenna operates from 2 to 10 GHz with a maximum gain of 3.62 dBi. In addition, the proposed textile antenna has a compact structure, wide bandwidth, lightweight, and flexible, thus meeting the requirements of breast cancer detection systems.

关键词： Slot antennas Resonant frequency Bandwidth Breast cancer Ultra wideband antennas Safety Textile antennas Antennas Substrates Gain

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(POstER) OVERTAKE: Opportunistic Routing and Concurrent Transmissions for TSCH 16

(POSTER) OVERTAKE: Opportunistic Routing and Concurrent Tran...

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16th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Harms, Oliver Landsiedel, Olaf Univ Kiel Kiel Germany Chalmers Univ Technol Gothenburg Sweden

ISBN: (数字)9781728143514

ISBN: (纸本)9781728143514

In this paper, we present OVERTAKE, an opportunistic routing protocol for Time-Slotted Channel Hopping (TSCH). OVERTAKE combines (1) opportunistic routing, (2) concurrent transmissions and (3) TSCH. We show that this novel combination enables low-latency, central scheduling withstanding node failures. Our initial results show its ability to withstand node failures of up to 40% of nodes of a flow while keeping minimal latency.

关键词： TSCH Opportunistic Routing Concurrent Transmissions Central Scheduling Wireless sensor-Actuator Networks (Industrial) Internet of Things

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Towards Prediction Model for IoT-Wireless sensor Network Packet Transmission Using Soft computing Technique 1

Towards Prediction Model for IoT-Wireless Sensor Network Pac...

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1st international conference on Multidisciplinary Engineering and Applied Science, ICMEAS 2021

作者： Agajo, James Thomas, Sadiq Gafai, Najashi Lukman, Ajao Adewale Ali Obadiah, N. Okafor, K.C. Federal University of Technology Computer Engineering Department Minna Nigeria Nile Univerisity of Nigeria Computer Engineering Department Abuja Nigeria Baze University Electrical Electronics/Computer Engineering Department Abuja Nigeria Federal University of Technology Mechatronics Engineering Department Owerri Nigeria

ISBN: (纸本)9781665434935

Packet transmission is a function of signal strength and distance in a wireless sensor network (WSN). The interval between the source node and sink node is of high significance in a wireless sensor network. This work developed a soft computing model that relates distance, signal strength, packet received and packet transmitted. An experiment was carried out using the CC2430 module for data acquisition. A learning process is carried out using the neural network (NN) tool toolbox. The entire datasets for training, testing, and validation are 60%, 25%, and 15% respectively. Regression result from training, testing, and validation was realized with R yielding 0.99972, 0.99974 and 0.99954 respectively. The summation of R gave 0.99869 in the work. The significance of the R value is that when it tends towards 1, the result demonstrates the accuracy of the model. This means that when the output of the trained and the test data are compared, it shows closeness symmetry. The closeness depicts how well the model performs. At convergence, the result shows that the coefficient for transmitted packet, distance and signal strength are predicted as 0.9969, 1.10800, and 0.7 respectively. © 2021 ieee.

关键词： Machine learning

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Industrial turing test: Concept and practice 1

Industrial turing test: Concept and practice

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1st ieee international conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Shao, Zhijiang Yang, Guanghui Xu, Zuhua Zhejiang University Department of Control Science and Engineering Hangzhou China

ISBN: (纸本)9781665433372

Intelligence is an abstract topic and Turing test, as an external behavior detection method, provides a scientific method to test representational artificial intelligence. In this work, we briefly discuss the categories of artificial intelligence in nature. Then, according to the characteristics of the process industry, we propose a new Turing test paradigm that is suitable for process operation practice from the perspective of behaviorism and pragmatism, called Industrial Turing Test. We designed a digital twin system of air separation process using virtual distributed control system technology and dynamic process modeling theory. Furthermore, we implemented the digital twin system and the prototype of the industrial Turing test in the industrial gas industry. Industrial practice shows that the proposed industrial Turing test provides an approach to test the effectiveness of the process industrial digital twin system. © 2021 ieee.

关键词： distributed parameter control systems

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IoT in Automobile Industry - A Smart sensor Based Collision Avoidance Parking system 1

IoT in Automobile Industry - A Smart Sensor Based Collision ...

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1st ieee international conference on Artificial Intelligence and Machine Vision, AIMV 2021

作者： Jani, Vishva Sutaria, Kush Patel, Samir Pandit Deendayal Petroleum University Dept. of Computer Engineering Gujarat Gandhinagar India

ISBN: (纸本)9781665442114

The automobile industry is one of the most thriving and rapidly growing industries in the modern world and with the recent advancement in technologies, it is inevitable to avoid the merger of different technological sectors for creating more efficient systems. Automobile manufacturers have understood the plethora of features and advancements IoT provides and especially in the safety of the vehicle and its passengers and as the cars become bigger and longer, the safety of the vehicle has become a major concern for the manufacturers as bigger support pillars introduce more hindrance in the driver's field of view. It becomes even more difficult for amateur drivers and geriatric people to handle such vehicles, as they are not able to get a proper judgment of the size of the car making them unable to maneuver the car properly. So far, only a few cost-effective systems are available in the market which assists the driver in avoiding a front-head collision. In this paper, an android application has been built that incorporates all of the above-mentioned components and helps to avoid head-on accidents utilising the Raspberry Pi, motioneyeOS, cameras, Arduino, ultrasonic sensor, and LCD screen. The cameras are placed in front of the vehicle which will assist the driver in avoiding the obstacles which are in front of the car. The prototype system has shown promising results and the components and the technology implemented are quite feasible and cost-effective. © 2021 ieee.

关键词： Internet of things

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Reinforcement Learning for Sustainable Combustion in Thermal Power Plant

Reinforcement Learning for Sustainable Combustion in Thermal...

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Smart and Sustainable Developments in Electrical Engineering (SSDEE), ieee international conference on

作者： S.M.A.K. Azad Sri Ramya Siraparapu Department of Electronics and Communication Engineering Sri Venkateswara College of Engineering Tirupati Andhra Pradesh India School of Electronics Engineering VIT-AP University Amaravati Andhra Pradesh India

ISBN: (数字)9798331542108

ISBN: (纸本)9798331542115

In recent years, the optimization of thermal power plants has become a critical area of research, driven by the urgent need to enhance energy efficiency and reduce emissions. This paper proposes a novel approach leveraging Reinforcement Learning (RL) techniques to optimize the operation of thermal power plants in real-time. RL, a branch of machine learning, offers a promising framework for decision-making in dynamic and uncertain environments, making it well-suited for the complex and nonlinear nature of power plant operations. By integrating RL algorithms with streaming data from sensors and control systems, our proposed methodology enables adaptive and autonomous control of key parameters such as air-fuel ratio and combustion temperature. This approach not only maximizes combustion efficiency but also minimizes emissions of harmful pollutants such as NOx, SOx, and particulate matter. Through simulation studies and real-world experiments, we demonstrate the effectiveness of our proposed approach, paving the way for the next generation of intelligent and sustainable power plant operation. We present a conceptual framework for RL-based control of thermal power plants highlighting potential benefits such as combustion efficiency, improved environmental performance, and enhanced operational flexibility.

关键词： Temperature sensors Temperature distribution Thermal engineering Reinforcement learning Combustion sensor systems Temperature control sensors Sustainable development Power generation

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