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  • 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

    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. Thus to predict the occurrence… 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

    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 paper presents Oppositional Shark Shell… 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

    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 controlled and accessed remotely through… 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

    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 using the remote control along… 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

    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 communication cost through the collaborative… More >

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