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Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities

Submission Deadline: 30 September 2021 (closed)

Guest Editors

Dr. Shabir Ahmad, Gachon University, South Korea.
Dr. Muhammad Fayaz, University of Central Asia, Russia.
Dr. Faheem Khan, University of Laki Marwat, Pakistan.

Summary

The Internet of Things (IoT) has been playing a vital role in adding value to human lives. In recent years, IoT applications have been coupled with Machine Learning techniques to form Intelligent IoT applications. However, for intelligent IoT nodes, the machine learning technologies should be lightweight to meet the constrained capabilities of the embedded hardware. This Special Issue aims to highlight advances in the open research topics in this field, which include, but are not limited to, the following:

1. Optimize Existing Machine Learning architecture for embedded IoT devices;

2. Lightweight Machine Learning architecture and frameworks;

3. Distributed Predictive Optimization;

4. Communication network design and optimization;

5. Energy saving and energy harvesting methods and techniques;

6. Blockchain for security and privacy;

7. Data collection and management methods (big data and data retrieval);

8. Data replication and distribution management on IoT edge nodes;

9. Lightweight Intelligent IoT service orchestration;

10. Intelligent IoT for lightweight driver assistance systems in Electric Vehicles.


Keywords

Model Optimization
Smart Cities
Internet of Things
Blockchain
Service Orchestration
Computer Vision
Medical Image Processing
Digital Twin
Virtualization

Published Papers


  • Open Access

    ARTICLE

    An Efficient and Reliable Multicasting for Smart Cities

    Faheem Khan, Muhammad Zahid, Hüseyin Gürüler, Ilhan Tarimer, Taegkeun Whangbo
    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 663-678, 2022, DOI:10.32604/cmc.2022.022934
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract The Internet of thing (IoT) is a growing concept for smart cities, and it is compulsory to communicate data between different networks and devices. In the IoT, communication should be rapid with less delay and overhead. For this purpose, flooding is used for reliable data communication in a smart cities concept but at the cost of higher overhead, energy consumption and packet drop etc. This paper aims to increase the efficiency in term of overhead and reliability in term of delay by using multicasting and unicasting instead of flooding during packet forwarding in a smart city using the IoT concept.… More >

  • Open Access

    ARTICLE

    Optimal Resource Allocation in Fog Computing for Healthcare Applications

    Salman Khan, Ibrar Ali Shah, Nasser Tairan, Habib Shah, Muhammad Faisal Nadeem
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6147-6163, 2022, DOI:10.32604/cmc.2022.023234
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract In recent years, the significant growth in the Internet of Things (IoT) technology has brought a lot of attention to information and communication industry. Various IoT paradigms like the Internet of Vehicle Things (IoVT) and the Internet of Health Things (IoHT) create massive volumes of data every day which consume a lot of bandwidth and storage. However, to process such large volumes of data, the existing cloud computing platforms offer limited resources due to their distance from IoT devices. Consequently, cloud-computing systems produce intolerable latency problems for latency-sensitive real-time applications. Therefore, a new paradigm called fog computing makes use of… More >

  • Open Access

    ARTICLE

    Edge Metric Dimension of Honeycomb and Hexagonal Networks for IoT

    Sohail Abbas, Zahid Raza, Nida Siddiqui, Faheem Khan, Taegkeun Whangbo
    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2683-2695, 2022, DOI:10.32604/cmc.2022.023003
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract Wireless Sensor Network (WSN) is considered to be one of the fundamental technologies employed in the Internet of things (IoT); hence, enabling diverse applications for carrying out real-time observations. Robot navigation in such networks was the main motivation for the introduction of the concept of landmarks. A robot can identify its own location by sending signals to obtain the distances between itself and the landmarks. Considering networks to be a type of graph, this concept was redefined as metric dimension of a graph which is the minimum number of nodes needed to identify all the nodes of the graph. This… More >

  • Open Access

    ARTICLE

    Hybrid Renewable Energy Resources Management for Optimal Energy Operation in Nano-Grid

    Faiza Qayyum, Faisal Jamil, Shabir Ahmad, Do-Hyeun Kim
    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2091-2105, 2022, DOI:10.32604/cmc.2022.019898
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract Renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment, unlike non-renewable energy resources. However, they often fail to meet energy requirements in unfavorable weather conditions. The concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy load. In this paper, an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid infrastructure. An actual data set comprising… More >

  • Open Access

    ARTICLE

    Blockchain Based Secured Load Balanced Task Scheduling Approach for Fitness Service

    Muhammad Ibrahim, Faisal Jamil, YunJung Lee, DoHyeun Kim
    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2599-2616, 2022, DOI:10.32604/cmc.2022.019534
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract In recent times, the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security features. The IoT has shown wide adoption in various applications including smart cities, healthcare, trade, business, etc. Among these applications, fitness applications have been widely considered for smart fitness systems. The users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness facilities. Thus, scheduling such a huge number of requests for fitness exercise is a big challenge. Secondly, the user fitness data is critical thus securing… More >

  • Open Access

    ARTICLE

    An Energy-Efficient Mobile Agent-Based Data Aggregation Scheme for Wireless Body Area Networks

    Gulzar Mehmood, Muhammad Zahid Khan, Muhammad Fayaz, Mohammad Faisal, Haseeb Ur Rahman, Jeonghwan Gwak
    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5929-5948, 2022, DOI:10.32604/cmc.2022.020546
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract Due to the advancement in wireless technology and miniaturization, Wireless Body Area Networks (WBANs) have gained enormous popularity, having various applications, especially in the healthcare sector. WBANs are intrinsically resource-constrained; therefore, they have specific design and development requirements. One such highly desirable requirement is an energy-efficient and reliable Data Aggregation (DA) mechanism for WBANs. The efficient and reliable DA may ultimately push the network to operate without much human intervention and further extend the network lifetime. The conventional client-server DA paradigm becomes unsuitable and inefficient for WBANs when a large amount of data is generated in the network. Similarly, in… More >

  • Open Access

    ARTICLE

    EEG-Based Neonatal Sleep Stage Classification Using Ensemble Learning

    Saadullah Farooq Abbasi, Harun Jamil, Wei Chen
    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4619-4633, 2022, DOI:10.32604/cmc.2022.020318
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract Sleep stage classification can provide important information regarding neonatal brain development and maturation. Visual annotation, using polysomnography (PSG), is considered as a gold standard for neonatal sleep stage classification. However, visual annotation is time consuming and needs professional neurologists. For this reason, an internet of things and ensemble-based automatic sleep stage classification has been proposed in this study. 12 EEG features, from 9 bipolar channels, were used to train and test the base classifiers including convolutional neural network, support vector machine, and multilayer perceptron. Bagging and stacking ensembles are then used to combine the outputs for final classification. The proposed… More >

  • Open Access

    ARTICLE

    Fuzzy-Based Automatic Epileptic Seizure Detection Framework

    Aayesha, Muhammad Bilal Qureshi, Muhammad Afzaal, Muhammad Shuaib Qureshi, Jeonghwan Gwak
    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5601-5630, 2022, DOI:10.32604/cmc.2022.020348
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract Detection of epileptic seizures on the basis of Electroencephalogram (EEG) recordings is a challenging task due to the complex, non-stationary and non-linear nature of these biomedical signals. In the existing literature, a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning algorithms. Some characterizing features of epileptic and non-epileptic EEG signals overlap; therefore, it requires that analysis of signals must be performed from diverse perspectives. Few studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG signals. To pose the challenge mentioned… More >

  • Open Access

    ARTICLE

    Blockchain and Machine Learning for Intelligent Multiple Factor-Based Ride-Hailing Services

    Zeinab Shahbazi, Yung-Cheol Byun
    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4429-4446, 2022, DOI:10.32604/cmc.2022.019755
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract One of the common transportation systems in Korea is calling taxis through online applications, which is more convenient for passengers and drivers in the modern area. However, the driver's passenger taxi request can be rejected based on the driver's location and distance. Therefore, there is a need to specify driver's acceptance and rejection of the received request. The security of this system is another main core to save the transaction information and safety of passengers and drivers. In this study, the origin and destination of the Jeju island South Korea were captured from T-map and processed based on machine learning… More >

  • Open Access

    ARTICLE

    Improved Sequencing Heuristic DSDV Protocol Using Nomadic Mobility Model for FANETS

    Inam Ullah Khan, Muhammad Abul Hassan, Muhammad Fayaz, Jeonghwan Gwak, Muhammad Adnan Aziz
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3653-3666, 2022, DOI:10.32604/cmc.2022.020697
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract Most interesting area is the growing demand of flying-IoT mergers with smart cities. However, aerial vehicles, especially unmanned aerial vehicles (UAVs), have limited capabilities for maintaining node energy efficiency. In order to communicate effectively, IoT is a key element for smart cities. While improving network performance, routing protocols can be deployed in flying-IoT to improve latency, packet drop rate, packet delivery, power utilization, and average-end-to-end delay. Furthermore, in literature, proposed techniques are very much complex which cannot be easily implemented in real-world applications. This issue leads to the development of lightweight energy-efficient routing in flying-IoT networks. This paper addresses the… More >

  • Open Access

    ARTICLE

    IoT Devices Authentication Using Artificial Neural Network

    Syed Shabih Ul Hasan, Anwar Ghani, Ikram Ud Din, Ahmad Almogren, Ayman Altameem
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3701-3716, 2022, DOI:10.32604/cmc.2022.020624
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract User authentication is one of the critical concerns of information security. Users tend to use strong textual passwords, but remembering complex passwords is hard as they often write it on a piece of paper or save it in their mobile phones. Textual passwords are slightly unprotected and are easily attackable. The attacks include dictionary, shoulder surfing, and brute force. Graphical passwords overcome the shortcomings of textual passwords and are designed to aid memorability and ease of use. This paper proposes a Process-based Pattern Authentication (PPA) system for Internet of Things (IoT) devices that does not require a server to maintain… More >

  • Open Access

    ARTICLE

    Earthquake Risk Assessment Approach Using Multiple Spatial Parameters for Shelter Demands

    Wenquan Jin, Naeem Iqbal, Hee-Cheal Kang, Dohyeun Kim
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3763-3780, 2022, DOI:10.32604/cmc.2022.020336
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract The earthquake is considered one of the most devastating disasters in any area of the world due to its potentially destructive force. Based on the various earthquake-related parameters, the risk assessment is enabled in advance to prevent future earthquake disasters. In this paper, for providing the shelter space demands to reduce the damage level and prevention costs, an earthquake risk assessment approach is proposed for deriving the risk index based on multiple spatial parameters in the gridded map. The proposed assessment approach is comprised of pre-processing, methodology model, and data visualization. The risk index model derives the earthquake risk index… More >

  • Open Access

    ARTICLE

    Intelligent Microservice Based on Blockchain for Healthcare Applications

    Faisal Jamil, Faiza Qayyum, Soha Alhelaly, Farjeel Javed, Ammar Muthanna
    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2513-2530, 2021, DOI:10.32604/cmc.2021.018809
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract Nowadays, the blockchain, Internet of Things, and artificial intelligence technology revolutionize the traditional way of data mining with the enhanced data preprocessing, and analytics approaches, including improved service platforms. Nevertheless, one of the main challenges is designing a combined approach that provides the analytics functionality for diverse data and sustains IoT applications with robust and modular blockchain-enabled services in a diverse environment. Improved data analytics model not only provides support insights in IoT data but also fosters process productivity. Designing a robust IoT-based secure analytic model is challenging for several purposes, such as data from diverse sources, increasing data size,… More >

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