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  • Open Access

    ARTICLE

    PanopticUAV: Panoptic Segmentation of UAV Images for Marine Environment Monitoring

    Yuling Dou1, Fengqin Yao1, Xiandong Wang1, Liang Qu2, Long Chen3, Zhiwei Xu4, Laihui Ding4, Leon Bevan Bullock1, Guoqiang Zhong1, Shengke Wang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 1001-1014, 2024, DOI:10.32604/cmes.2023.027764 - 22 September 2023

    Abstract UAV marine monitoring plays an essential role in marine environmental protection because of its flexibility and convenience, low cost and convenient maintenance. In marine environmental monitoring, the similarity between objects such as oil spill and sea surface, Spartina alterniflora and algae is high, and the effect of the general segmentation algorithm is poor, which brings new challenges to the segmentation of UAV marine images. Panoramic segmentation can do object detection and semantic segmentation at the same time, which can well solve the polymorphism problem of objects in UAV ocean images. Currently, there are few studies on… More >

  • Open Access

    ARTICLE

    Fusion-Based Deep Learning Model for Automated Forest Fire Detection

    Mesfer Al Duhayyim1, Majdy M. Eltahir2, Ola Abdelgney Omer Ali3, Amani Abdulrahman Albraikan4, Fahd N. Al-Wesabi2, Anwer Mustafa Hilal5,*, Manar Ahmed Hamza5, Mohammed Rizwanullah5

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1355-1371, 2023, DOI:10.32604/cmc.2023.024198 - 31 October 2023

    Abstract Earth resource and environmental monitoring are essential areas that can be used to investigate the environmental conditions and natural resources supporting sustainable policy development, regulatory measures, and their implementation elevating the environment. Large-scale forest fire is considered a major harmful hazard that affects climate change and life over the globe. Therefore, the early identification of forest fires using automated tools is essential to avoid the spread of fire to a large extent. Therefore, this paper focuses on the design of automated forest fire detection using a fusion-based deep learning (AFFD-FDL) model for environmental monitoring. The… More >

  • Open Access

    ARTICLE

    Multisensor Information Fusion for Condition Based Environment Monitoring

    A. Reyana1,*, P. Vijayalakshmi2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1013-1025, 2023, DOI:10.32604/iasc.2023.032538 - 29 September 2022

    Abstract Destructive wildfires are becoming an annual event, similar to climate change, resulting in catastrophes that wreak havoc on both humans and the environment. The result, however, is disastrous, causing irreversible damage to the ecosystem. The location of the incident and the hotspot can sometimes have an impact on early fire detection systems. With the advancement of intelligent sensor-based control technologies, the multi-sensor data fusion technique integrates data from multiple sensor nodes. The primary objective to avoid wildfire is to identify the exact location of wildfire occurrence, allowing fire units to respond as soon as possible. More >

  • Open Access

    ARTICLE

    Hybrid Deep Learning Enabled Air Pollution Monitoring in ITS Environment

    Ashit Kumar Dutta1, Jenyfal Sampson2, Sultan Ahmad3, T. Avudaiappan4, Kanagaraj Narayanasamy5,*, Irina V. Pustokhina6, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1157-1172, 2022, DOI:10.32604/cmc.2022.024109 - 24 February 2022

    Abstract Intelligent Transportation Systems (ITS) have become a vital part in improving human lives and modern economy. It aims at enhancing road safety and environmental quality. There is a tremendous increase observed in the number of vehicles in recent years, owing to increasing population. Each vehicle has its own individual emission rate; however, the issue arises when the emission rate crosses a standard value. Owing to the technological advances made in Artificial Intelligence (AI) techniques, it is easy to leverage it to develop prediction approaches so as to monitor and control air pollution. The current research… More >

  • Open Access

    ARTICLE

    IoT-EMS: An Internet of Things Based Environment Monitoring System in Volunteer Computing Environment

    Sourav Kumar Bhoi1, Sanjaya Kumar Panda2, Kalyan Kumar Jena1, Kshira Sagar Sahoo3, N. Z. Jhanjhi4,*, Mehedi Masud5, Sultan Aljahdali5

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1493-1507, 2022, DOI:10.32604/iasc.2022.022833 - 09 December 2021

    Abstract Environment monitoring is an important area apart from environmental safety and pollution control. Such monitoring performed by the physical models of the atmosphere is unstable and inaccurate. Machine Learning (ML) techniques on the other hand are more robust in capturing the dynamics in the environment. In this paper, a novel approach is proposed to build a cost-effective standardized environment monitoring system (IoT-EMS) in volunteer computing environment. In volunteer computing, the volunteers (people) share their resources for distributed computing to perform a task (environment monitoring). The system is based on the Internet of Things and is… More >

  • Open Access

    ARTICLE

    A Cost-Efficient Environment Monitoring Robotic Vehicle for Smart Industries

    Arfat Ahmad Khan1, Chitapong Wechtaisong1,*, Faizan Ahmed Khan2, Nadeem Ahmad3

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 473-487, 2022, DOI:10.32604/cmc.2022.020903 - 03 November 2021

    Abstract Environmental monitoring is essential for accessing and avoiding the undesirable situations in industries along with ensuring the safety of workers. Moreover, inspecting and monitoring of environmental parameters by humans lead to various health concerns, which in turn brings to the requirement of monitoring the environment by robotics. In this paper, we have designed and implemented a cost-efficient robotic vehicle for the computation of various environmental parameters such as temperature, radiation, smoke, and pressure with the help of sensors. Furthermore, the robotic vehicle is designed in such a way that it can be dually controlled by… More >

  • Open Access

    ARTICLE

    A Multi-Agent System for Environmental Monitoring Using Boolean Networks and Reinforcement Learning

    Hanzhong Zheng1, Dejie Shi2,*

    Journal of Cyber Security, Vol.2, No.2, pp. 85-96, 2020, DOI:10.32604/jcs.2020.010086 - 14 July 2020

    Abstract Distributed wireless sensor networks have been shown to be effective for environmental monitoring tasks, in which multiple sensors are deployed in a wide range of the environments to collect information or monitor a particular event, Wireless sensor networks, consisting of a large number of interacting sensors, have been successful in a variety of applications where they are able to share information using different transmission protocols through the communication network. However, the irregular and dynamic environment requires traditional wireless sensor networks to have frequent communications to exchange the most recent information, which can easily generate high… More >

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