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  • Open Access

    ARTICLE

    Design of Machine Learning Based Smart Irrigation System for Precision Agriculture

    Khalil Ibrahim Mohammad Abuzanouneh1, Fahd N. Al-Wesabi2, Amani Abdulrahman Albraikan3, Mesfer Al Duhayyim4, M. Al-Shabi5, Anwer Mustafa Hilal6, Manar Ahmed Hamza6,*, Abu Sarwar Zamani6, K. Muthulakshmi7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 109-124, 2022, DOI:10.32604/cmc.2022.022648 - 24 February 2022

    Abstract Agriculture 4.0, as the future of farming technology, comprises numerous key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. To achieve effective water resource usage and automated irrigation in precision agriculture, recent technologies like machine learning (ML) can be employed. With this motivation, this paper design an IoT and ML enabled smart irrigation system (IoTML-SIS) for precision agriculture. The proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for… More >

  • Open Access

    ARTICLE

    A Novel Approach for Deciphering Big Data Value Using Dark Data

    Surbhi Bhatia*, Mohammed Alojail

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1261-1271, 2022, DOI:10.32604/iasc.2022.023501 - 08 February 2022

    Abstract The last decade has seen a rapid increase in big data, which has led to a need for more tools that can help organizations in their data management and decision making. Business intelligence tools have removed many of the obstacles to data visibility, and numerous data mining technologies are playing an essential role in this visibility. However, the increase in big data has also led to an increase in ‘dark data’, data that does not have any predefined structure and is not generated intentionally. In this paper, we show how dark data can be mined… More >

  • Open Access

    ARTICLE

    Situation Awareness Data Fusion Method Based on Library Events

    Haixu Xi1,2, Wei Gao2,*, Gyun Yeol Park3

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1047-1061, 2022, DOI:10.32604/csse.2022.022051 - 08 February 2022

    Abstract Microelectronic technology and communication technology are developed in deep manner; the computing mode has been transferred from traditional computer-centered to human centered pervasive. So, the concept of Internet of things (IoT) is gradually put forward, which allows people to access information about their surroundings on demand through different terminals. The library is the major public space for human to read and learn. How to provide a more comfortable library environment to better meet people’s learning requirements is a place where the Internet of things plays its role. The purpose of this paper is to solve… More >

  • Open Access

    ARTICLE

    Deep Learning Convolutional Neural Network for ECG Signal Classification Aggregated Using IoT

    S. Karthiga*, A. M. Abirami

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 851-866, 2022, DOI:10.32604/csse.2022.021935 - 08 February 2022

    Abstract Much attention has been given to the Internet of Things (IoT) by citizens, industries, governments, and universities for applications like smart buildings, environmental monitoring, health care and so on. With IoT, network connectivity is facilitated between smart devices from anyplace and anytime. IoT-based health monitoring systems are gaining popularity and acceptance for continuous monitoring and detect health abnormalities from the data collected. Electrocardiographic (ECG) signals are widely used for heart diseases detection. A novel method has been proposed in this work for ECG monitoring using IoT techniques. In this work, a two-stage approach is employed.… More >

  • Open Access

    ARTICLE

    Accurate Location Estimation of Smart Dusts Using Machine Learning

    Shariq Bashir1,*, Owais Ahmed Malik2, Daphne Teck Ching Lai2

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6165-6181, 2022, DOI:10.32604/cmc.2022.024269 - 14 January 2022

    Abstract Traditional wireless sensor networks (WSNs) are not suitable for rough terrains that are difficult or impossible to access by humans. Smart dust is a technology that works with the combination of many tiny sensors which is highly useful for obtaining remote sensing information from rough terrains. The tiny sensors are sprinkled in large numbers on rough terrains using airborne distribution through drones or aircraft without manually setting their locations. Although it is clear that a number of remote sensing applications can benefit from this technology, but the small size of smart dust fundamentally restricts the… More >

  • Open Access

    ARTICLE

    Machine Learning-based Optimal Framework for Internet of Things Networks

    Moath Alsafasfeh1,*, Zaid A. Arida2, Omar A. Saraereh3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5355-5380, 2022, DOI:10.32604/cmc.2022.024093 - 14 January 2022

    Abstract Deep neural networks (DNN) are widely employed in a wide range of intelligent applications, including image and video recognition. However, due to the enormous amount of computations required by DNN. Therefore, performing DNN inference tasks locally is problematic for resource-constrained Internet of Things (IoT) devices. Existing cloud approaches are sensitive to problems like erratic communication delays and unreliable remote server performance. The utilization of IoT device collaboration to create distributed and scalable DNN task inference is a very promising strategy. The existing research, on the other hand, exclusively looks at the static split method in… More >

  • Open Access

    ARTICLE

    Energy-Efficient Scheduling for a Cognitive IoT-Based Early Warning System

    Saeed Ahmed1,2, Noor Gul1,3, Jahangir Khan4, Junsu Kim1, Su Min Kim1,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5061-5082, 2022, DOI:10.32604/cmc.2022.023639 - 14 January 2022

    Abstract Flash floods are deemed the most fatal and disastrous natural hazards globally due to their prompt onset that requires a short prime time for emergency response. Cognitive Internet of things (CIoT) technologies including inherent characteristics of cognitive radio (CR) are potential candidates to develop a monitoring and early warning system (MEWS) that helps in efficiently utilizing the short response time to save lives during flash floods. However, most CIoT devices are battery-limited and thus, it reduces the lifetime of the MEWS. To tackle these problems, we propose a CIoT-based MEWS to slash the fatalities of… More >

  • Open Access

    ARTICLE

    Man Overboard Detection System Using IoT for Navigation Model

    Hüseyin Gürüler1, Murat Altun1, Faheem Khan2, Taegkeun Whangbo2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4955-4969, 2022, DOI:10.32604/cmc.2022.023556 - 14 January 2022

    Abstract Security measures and contingency plans have been established in order to ensure human safety especially in the floating elements like ferry, ro-ro, catamaran, frigate, yacht that are the vehicles services for the purpose of logistic and passenger transport. In this paper, all processes in the event of Man overboard (MOB)are initiated for smart transportation. In MOB the falling person is totally dependent on the person who first saw the falling person. The main objective of this paper is to develop a solution to this significant problem. If a staff member or a passenger does not… More >

  • Open Access

    ARTICLE

    Design of Intelligent Alzheimer Disease Diagnosis Model on CIoT Environment

    Anwer Mustafa Hilal1, Fahd N. Al-Wesabi2,3, Mohamed Tahar Ben Othman4, Khaled Mohamad Almustafa5, Nadhem Nemri6, Mesfer Al Duhayyim7, Manar Ahmed Hamza1,*, Abu Sarwar Zamani1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5979-5994, 2022, DOI:10.32604/cmc.2022.022686 - 14 January 2022

    Abstract Presently, cognitive Internet of Things (CIoT) with cloud computing (CC) enabled intelligent healthcare models are developed, which enables communication with intelligent devices, sensor modules, and other stakeholders in the healthcare sector to avail effective decision making. On the other hand, Alzheimer disease (AD) is an advanced and degenerative illness which injures the brain cells, and its earlier detection is necessary for suitable interference by healthcare professional. In this aspect, this paper presents a new Oriented Features from Accelerated Segment Test (FAST) with Rotated Binary Robust Independent Elementary Features (BRIEF) Detector (ORB) with optimal artificial neural network… More >

  • Open Access

    ARTICLE

    Drone-based AI/IoT Framework for Monitoring, Tracking and Fighting Pandemics

    Abdelhamied A. Ateya1,2, Abeer D. Algarni1, Andrey Koucheryavy3, Naglaa. F. Soliman1,2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4677-4699, 2022, DOI:10.32604/cmc.2022.021850 - 14 January 2022

    Abstract Since World Health Organization (WHO) has declared the Coronavirus disease (COVID-19) a global pandemic, the world has changed. All life's fields and daily habits have moved to adapt to this new situation. According to WHO, the probability of such virus pandemics in the future is high, and recommends preparing for worse situations. To this end, this work provides a framework for monitoring, tracking, and fighting COVID-19 and future pandemics. The proposed framework deploys unmanned aerial vehicles (UAVs), e.g.; quadcopter and drone, integrated with artificial intelligence (AI) and Internet of Things (IoT) to monitor and fight… More >

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