EAI Endorsed Transactions on Internet of Things

Issue 30, 2022

Articles
Information

APP innovation to Control Projects Risks Management during Crises
Appears in:
IoT 22(30): e1

Author:
Rasha Abdulrazzak Waheeb

Abstract:
The goal of this study is to build an application that can be used in difficult cases and sudden circumstances during the pandemic and post-disaster state, which can be the development of digital risk management and mitigating the difficult impact of the epidemic through the improvement of IT and I…The goal of this study is to build an application that can be used in difficult cases and sudden circumstances during the pandemic and post-disaster state, which can be the development of digital risk management and mitigating the difficult impact of the epidemic through the improvement of IT and IoT that can be fine by finding initial solutions and make the world like a digital city that could be managed by the network. We provide this study to gain an overview of reasons for delayed and exceeded costs in a select of thirty Iraqi case projects by controlling the time and cost. The drivers of delay have been investigated in multiple countries/contexts. however, there is little country data available under the conditions that have characterized Iraq over the previous 10-20 years.
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Overview of 5G & Beyond Security
Appears in:
IoT 22(30): e2

Authors:
Fawad Shokoor, Wasswa Shafik, S. Mojtaba Matinkhah

Abstract:
Network security is a crucial concern when it comes to computation, concerns like threats can have high consequences, and critical information will be shared with unauthorized persons. This paper presents a detailed survey on Fifth Generation (5G) and security aspect. This is more predictable since…Network security is a crucial concern when it comes to computation, concerns like threats can have high consequences, and critical information will be shared with unauthorized persons. This paper presents a detailed survey on Fifth Generation (5G) and security aspect. This is more predictable since the core technology; the synonymous approach is possible with Fifth Generation (5G) and Beyond Technologies though with limited access. Many incidents have shown that the possibility of a hacked wireless network, not just impacts privacy and security worries, but also hinders the diverse dynamics of the ecosystem. Security attacks have grown in frequency and severity throughout the near past, making detection mechanisms harder.
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Smart Gardening: A Solution to Your Gardening Issues
Appears in:
IoT 22(30): e3

Authors:
Niloy Chakraborty, Adrika Mukherjee, Mayuri Bhadra

Abstract:
The technology which could make our lives prosper within the four walls could also help to create our own corner of nature nourish. In this paper, we propose a smart gardening system that utilizes the concept of the Internet of Things (IoT) [1]. The major goal of this project is to reduce water con…The technology which could make our lives prosper within the four walls could also help to create our own corner of nature nourish. In this paper, we propose a smart gardening system that utilizes the concept of the Internet of Things (IoT) [1]. The major goal of this project is to reduce water consumption when gardening and to maintain the garden remotely. Important plant data, like temperature, relative humidity, and soil moisture, are continuously stored in a relational database in this gardening system. Artificial Intelligence (AI) based planning [2] is used for watering the plants at regular intervals and providing appropriate illumination in the garden area for aesthetics and overall plant growth. Our proposed system reduces the effort due to manual intervention by around 59.3%. The real-time sensor status can be monitored which in turn allows the end-users of the garden to control the surrounding conditions optimal for plant growth, using the Telegram application. A plant recognition model has been introduced in this system, where a Convolutional Neural Network (CNN) [3] based deep learning algorithm classifies the plant categories with 95% accuracy. Moreover, an 98% accurate, deep learning-based, plant health identification model integrated with this gardening system also informs the end-user about the health of the plant.
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Detection of Sleep Paralysis by using IoT Based Device and Its Relationship Between Sleep Paralysis And Sleep Quality
Appears in:
IoT 22(30): e4

Authors:
Muhammad Shoaib Akhtar, Tao Feng

Abstract:
When a person wakes up in the middle of the night, they are paralyzed. Despite the fact that most episodes are associated with extreme terror and some might cause clinically significant suffering, little is understood about the experience. This study will analyze existing research on the relationsh…When a person wakes up in the middle of the night, they are paralyzed. Despite the fact that most episodes are associated with extreme terror and some might cause clinically significant suffering, little is understood about the experience. This study will analyze existing research on the relationship between sleep paralyses and sleep in general. Many studies have connected poor sleep quality to an increased risk of sleep paralysis. Awake yet unable to act, sleep paralysis occurs. This might happen between awake and sleeping. The problem is approached in three steps: Data collection, data storage, calculation and machine learning prediction of sleep paralysis. The data came from the Smart Device. The dataset has several (independent) and dependent variables (Outcome). This device has been put to the test. Each exam has its own set of features and predicted outcomes. To assess the system's validity, we executed a posture recognition accuracy test. The device was hidden on top of the bed. The controller is in charge of measurement and data collection. Experiments were conducted by collecting pressure data from a patient lying down. The person acted out his sleeping positions on a mat for a while. Machine learning has been used to predict sleep paralysis. By comparing sleep postures to the outcome, we were able to show the link between sleep qualities and sleep paralysis. Machine learning approaches have been used to predict sleep paralysis. Comparing sleeping positions with the results showed the link between sleep quality and sleep paralysis. Sleep paralysis correlates with poor sleep quality. The Random Forest model has the highest accuracy of 91.9 percent in predicting sleep paralysis in the given dataset. SVM with Linear Kernel was 80.49 percent accurate, RBF was 42.68 percent, and Polynomial was 47.56 percent. The accuracy of logistic regression was 76.83 percent. KNN had a dismal performance of 60.98%. Decision Trees and Gradient Boosting both fared well at 85.37 percent.
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Systematic Literature Review on the Accuracy of Face Recognition Algorithms
Appears in:
IoT 22(30): e5

Authors:
Marcos Agenor Lazarini, Rogério Rossi, Kechi Hirama

Abstract:
Real-time facial recognition systems have been increasingly used, making it relevant to address the accuracy of these systems given the credibility and trust they must offer. Therefore, this article seeks to identify the algorithms currently used by facial recognition systems through a Systematic L…Real-time facial recognition systems have been increasingly used, making it relevant to address the accuracy of these systems given the credibility and trust they must offer. Therefore, this article seeks to identify the algorithms currently used by facial recognition systems through a Systematic Literature Review that considers recent scientific articles, published between 2018 and 2021. From the initial collection of ninety-three articles, a subset of thirteen was selected after applying the inclusion and exclusion procedures. One of the outstanding results of this research corresponds to the use of algorithms based on Artificial Neural Networks (ANN) considered in 21% of the solutions, highlighting the use of Convolutional Neural Network (CNN). Another relevant result is the identification of the use of the Viola-Jones algorithm, present in 19% of the solutions. In addition, from this research, two specific facial recognition solutions associated with access control were found considering the principles of the Internet of Things, one being applied to access control to environments and the other applied to smart cities.
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Scope

EAI Endorsed Transactions on Internet of Things is open access, a peer-reviewed scholarly journal focused on all areas related to the technologies and application fields related to the Internet of Things. The journal publishes research articles, review articles, commentaries, editorials, technical …

Topics

The scope of the Transactions encompasses latest advances in the growing field of the Internet of Things (IoT), with the topics of interest being:

Technologies & Protocols: sensors, energy harvesters, RFID, machine-type communications, medium access protocols, radio resource management, indust…

The scope of the Transactions encompasses latest advances in the growing field of the Internet of Things (IoT), with the topics of interest being:

Technologies & Protocols: sensors, energy harvesters, RFID, machine-type communications, medium access protocols, radio resource management, industrial control, real-time systems, embedded software design.
Architectures & Services: cloud-based platforms, big data processing engines, security, privacy, device management, CPS/SCADA platforms, innovative/open service architectures, data mining, service middleware, semantic service management.
Applications & Use Cases: smart cities, smart buildings, smart traffic, industrial internet of things, smart metering, smart agriculture, etc.
Standardisation Landscape: IEEE, IETF, 3GPP, ETSI, and various alliances.
Experimentation & Prototypes: real-world deployments at scale, industrial deployments, experiences with prototypes (including what didn’t work), etc.

Scopus
DOAJ
CrossRef
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Editors-in-Chief
Shancang Li, University of the West of England - UWE Bristol, UK
Der Jiunn Deng, National Changhua University of Education, Taiwan
Area Editors
Ahmet Çağdaş Seçkin, Aydın Adnan Menderes University, Turkey
Antonella Molinaro, University Mediterranea of Reggio Calabr…

Editors-in-Chief
Shancang Li, University of the West of England - UWE Bristol, UK
Der Jiunn Deng, National Changhua University of Education, Taiwan
Area Editors
Ahmet Çağdaş Seçkin, Aydın Adnan Menderes University, Turkey
Antonella Molinaro, University Mediterranea of Reggio Calabria, Italy
Atta Quddus, University of Surrey, UK
Joachim Sachs, Ericsson, Sweden
Chih-Heng Ke, National Quemoy University, Taiwan
Kan Zheng, BUPT, China
Kamran Ali, Beijing University of Posts & Telecommunications, China
Liljana Gavrilovska, University Sts. Cyril and Methodius, Macedonia
Maria Rita Palattella, University of Luxembourg, Luxembourg
Ming-Huang Guo, Shih-Hsin university, Taiwan
Muddesar Iqbal, London South Bank University, UK
Pietro Manzoni, Universitat Politècnica de València, Spain
Qindong Sun, Xi’an Jiaotong University, China
Rafael Romero-Carazas, Research Directorate of the College of Public Accountants of Arequipa, Peru
Ripon Patgiri, National Institute of Technology Silchar, India
Rose Qingyang Hu, Utah State University, USA
Shanshan Zhao, University of West England, UK
Thomas Watteyne, INRIA, France; Linear Technologies, USA
Xavi Vilajosana, UOC, Spain; Worldsensing, Spain
Xuan Liu, Future Network Research Center, Southeast University, China
Yun Zhao, Shanxi Agricultural University, China
Yu-Liang Liu, Overseas Chinese University, Taiwan

Journal Blurb

Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/iot/index

Publisher: EAI
ISSN: 2414-1399
Volume: 8

Published: 2022-09-12

APP innovation to Control Projects Risks Management during Crises

Overview of 5G & Beyond Security

Smart Gardening: A Solution to Your Gardening Issues

Detection of Sleep Paralysis by using IoT Based Device and Its Relationship Between Sleep Paralysis And Sleep Quality

Systematic Literature Review on the Accuracy of Face Recognition Algorithms

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