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  • Open Access

    ARTICLE

    Neural Network-Based State of Charge Estimation Method for Lithium-ion Batteries Based on Temperature

    Donghun Wang, Jonghyun Lee, Minchan Kim, Insoo Lee*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2025-2040, 2023, DOI:10.32604/iasc.2023.034749 - 05 January 2023

    Abstract Lithium-ion batteries are commonly used in electric vehicles, mobile phones, and laptops. These batteries demonstrate several advantages, such as environmental friendliness, high energy density, and long life. However, battery overcharging and overdischarging may occur if the batteries are not monitored continuously. Overcharging causes fire and explosion casualties, and overdischarging causes a reduction in the battery capacity and life. In addition, the internal resistance of such batteries varies depending on their external temperature, electrolyte, cathode material, and other factors; the capacity of the batteries decreases with temperature. In this study, we develop a method for estimating… More >

  • Open Access

    ARTICLE

    Optimal Routing with Spatial-Temporal Dependencies for Traffic Flow Control in Intelligent Transportation Systems

    R. B. Sarooraj*, S. Prayla Shyry

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2071-2084, 2023, DOI:10.32604/iasc.2023.034716 - 05 January 2023

    Abstract In Intelligent Transportation Systems (ITS), controlling the traffic flow of a region in a city is the major challenge. Particularly, allocation of the traffic-free route to the taxi drivers during peak hours is one of the challenges to control the traffic flow. So, in this paper, the route between the taxi driver and pickup location or hotspot with the spatial-temporal dependencies is optimized. Initially, the hotspots in a region are clustered using the density-based spatial clustering of applications with noise (DBSCAN) algorithm to find the hot spots at the peak hours in an urban area.… More >

  • Open Access

    ARTICLE

    Drone for Dynamic Monitoring and Tracking with Intelligent Image Analysis

    Ching-Bang Yao1, Chang-Yi Kao2,*, Jiong-Ting Lin3

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2233-2252, 2023, DOI:10.32604/iasc.2023.034488 - 05 January 2023

    Abstract Traditional monitoring systems that are used in shopping malls or community management, mostly use a remote control to monitor and track specific objects; therefore, it is often impossible to effectively monitor the entire environment. When finding a suspicious person, the tracked object cannot be locked in time for tracking. This research replaces the traditional fixed-point monitor with the intelligent drone and combines the image processing technology and automatic judgment for the movements of the monitored person. This intelligent system can effectively improve the shortcomings of low efficiency and high cost of the traditional monitor system.… More >

  • Open Access

    ARTICLE

    Intelligent Risk-Identification Algorithm with Vision and 3D LiDAR Patterns at Damaged Buildings

    Dahyeon Kim1, Jiyoung Min1, Yongwoo Song1, Chulsu Kim2, Junho Ahn1,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2315-2331, 2023, DOI:10.32604/iasc.2023.034394 - 05 January 2023

    Abstract Existing firefighting robots are focused on simple storage or fire suppression outside buildings rather than detection or recognition. Utilizing a large number of robots using expensive equipment is challenging. This study aims to increase the efficiency of search and rescue operations and the safety of firefighters by detecting and identifying the disaster site by recognizing collapsed areas, obstacles, and rescuers on-site. A fusion algorithm combining a camera and three-dimension light detection and ranging (3D LiDAR) is proposed to detect and localize the interiors of disaster sites. The algorithm detects obstacles by analyzing floor segmentation and… More >

  • Open Access

    ARTICLE

    Federated Blockchain Model for Cyber Intrusion Analysis in Smart Grid Networks

    N. Sundareswaran*, S. Sasirekha

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2129-2143, 2023, DOI:10.32604/iasc.2023.034381 - 05 January 2023

    Abstract Smart internet of things (IoT) devices are used to manage domestic and industrial energy needs using sustainable and renewable energy sources. Due to cyber infiltration and a lack of transparency, the traditional transaction process is inefficient, unsafe and expensive. Smart grid systems are now efficient, safe and transparent owing to the development of blockchain (BC) technology and its smart contract (SC) solution. In this study, federated learning extreme gradient boosting (FL-XGB) framework has been developed along with BC to learn the intrusion inside the smart energy system. FL is best suited for a decentralized BC-enabled… More >

  • Open Access

    ARTICLE

    Deep Learning Framework for Landslide Severity Prediction and Susceptibility Mapping

    G. Bhargavi*, J. Arunnehru

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1257-1272, 2023, DOI:10.32604/iasc.2023.034335 - 05 January 2023

    Abstract Landslides are a natural hazard that is unpredictable, but we can prevent them. The Landslide Susceptibility Index reduces the uncertainty of living with landslides significantly. Planning and managing landslide-prone areas is critical. Using the most optimistic deep neural network techniques, the proposed work classifies and analyses the severity of the landslide. The selected experimental study area is Kerala’s Idukki district. A total of 3363 points were considered for this experiment using historic landslide points, field surveys, and literature searches. The primary triggering factors slope degree, slope aspect, elevation (altitude), normalized difference vegetation index (NDVI), and… More >

  • Open Access

    ARTICLE

    Smart Nutrient Deficiency Prediction System for Groundnut Leaf

    Janani Malaisamy*, Jebakumar Rethnaraj

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1845-1862, 2023, DOI:10.32604/iasc.2023.034280 - 05 January 2023

    Abstract Prediction of the nutrient deficiency range and control of it through application of an appropriate amount of fertiliser at all growth stages is critical to achieving a qualitative and quantitative yield. Distributing fertiliser in optimum amounts will protect the environment’s condition and human health risks. Early identification also prevents the disease’s occurrence in groundnut crops. A convolutional neural network is a computer vision algorithm that can be replaced in the place of human experts and laboratory methods to predict groundnut crop nitrogen nutrient deficiency through image features. Since chlorophyll and nitrogen are proportionate to one… More >

  • Open Access

    ARTICLE

    ProbD: Faulty Path Detection Based on Probability in Software-Defined Networking

    Jiangyuan Yao1, Jiawen Wang1, Shuhua Weng1, Minrui Wang1, Deshun Li1,*, Yahui Li2, Xingcan Cao3

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1783-1796, 2023, DOI:10.32604/iasc.2023.034265 - 05 January 2023

    Abstract With the increasing number of switches in Software-Defined Networking (SDN), there are more and more faults rising in the data plane. However, due to the existence of link redundancy and multi-path forwarding mechanisms, these problems cannot be detected in time. The current faulty path detection mechanisms have problems such as the large scale of detection and low efficiency, which is difficult to meet the requirements of efficient faulty path detection in large-scale SDN. Concerning this issue, we propose an efficient network path fault testing model ProbD based on probability detection. This model achieves a high… More >

  • Open Access

    ARTICLE

    Human Factors While Using Head-Up-Display in Low Visibility Flying Conditions

    Jhulan Kumar1,2, Surender Singh Saini1,2, Divya Agrawal1,2, Vinod Karar1,2,*, Aman Kataria2

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2411-2423, 2023, DOI:10.32604/iasc.2023.034203 - 05 January 2023

    Abstract Flying an aircraft in low visibility is still a challenging task for the pilot. It requires precise and accurate situational awareness (SA) in real-time. A Head-up Display (HUD) is used to project collimated internal and external flight information on a transparent screen in the pilot’s forward field of view, which eliminates the change of eye position between Head-Down-Display (HDD) instruments and outer view through the windshield. Implementation of HUD increases the SA and reduces the workload for the pilot. But to provide a better flying capability for the pilot, projecting extensive information on HUD causes More >

  • Open Access

    ARTICLE

    A Joint Optimization Algorithm for Renewable Energy System

    Imran Khan1, Firdaus Muhammad-Sukki2, Jorge Alfredo Ardila Rey3, Abdullahi Abubakar Mas’ud4, Saud Jazaa Alshammari4, Dag Øivind Madsen5,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1979-1989, 2023, DOI:10.32604/iasc.2023.034106 - 05 January 2023

    Abstract Energy sustainability is a hot topic in both scientific and political circles. To date, two alternative approaches to this issue are being taken. Some people believe that increasing power consumption is necessary for countries’ economic and social progress, while others are more concerned with maintaining carbon consumption under set limitations. To establish a secure, sustainable, and economical energy system while mitigating the consequences of climate change, most governments are currently pushing renewable growth policies. Energy markets are meant to provide consumers with dependable electricity at the lowest possible cost. A profit-maximization optimal decision model is… More >

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