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Article
Ecology
Arunabha M. Roy et al.
Summary: In the face of climatic instability, ecological disturbances, and human actions, endangered wildlife species are under threat. An up-to-date and accurate detection process is crucial for protecting biodiversity losses, conservation, and ecosystem management. However, current wildlife detection models often lack superior feature extraction capability in complex environments, limiting the development of accurate and reliable models. To address this issue, WilDect-YOLO is proposed as a deep learning-based automated high-performance detection model for real-time endangered wildlife detection. By incorporating residual blocks, DenseNet blocks, Spatial Pyramid Pooling, and modified Path Aggregation Network, WilDect-YOLO achieves superior detection results under challenging environments. Evaluation on a custom endangered wildlife dataset shows that WilDect-YOLO outperforms current state-of-the-art models with a mean average precision of 96.89% and a detection rate of 59.20 FPS. This research provides an effective framework for highly accurate species-level localized bounding box prediction, contributing to the development of non-invasive, fully automated real-time animal observation systems.
ECOLOGICAL INFORMATICS
(2023)
Article
Robotics
Petar Radanliev et al.
Summary: This paper investigates the evolution of artificial intelligence in internet of things networks through exploring the use of new technologies in industrial systems and the correlation between academic literature and Industry 4.0 interdependencies. The novelty lies in introducing the concept of digital twin and applying grounded theory analysis to complex interconnected systems. By connecting human-computer interactions, the paper offers a summary of mechanisms for the evolution of artificial intelligence in IoT networks.
INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Sohaib A. Latif et al.
Summary: The Internet of Things (IoT) is an emerging technology crucial to many aspects of social life, but faces challenges such as interoperability, compatibility, security, and energy efficiency in its wide deployment.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Arunabha M. Roy et al.
Summary: This paper proposes a high-performance real-time fine-grain object detection framework for early identification and prevention of various plant diseases. The proposed model, based on an improved version of the YOLOv4 algorithm, outperforms existing state-of-the-art models in detection accuracy and speed, providing an effective and efficient method for detecting different plant diseases in complex scenarios.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Telecommunications
Rupali Verma
Summary: Smart healthcare cyber physical systems integrate the physical and cyber world for efficient medical processes. Technologies like Internet of Things, Machine learning and Artificial Intelligence have given birth to smart systems to address challenges in the healthcare sector.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Proceedings Paper
Computer Science, Hardware & Architecture
Zahra Jadidi et al.
Summary: With the rise of IoT and AI services, protecting CPS from cyber threats becomes challenging. Machine learning methods are being used for anomaly detection in CPS, but deep learning is vulnerable to adversarial attacks. This study focuses on the impact of adversarial attacks on deep learning-based anomaly detection in CPS and proposes a mitigation approach by retraining models with adversarial samples.
2022 31ST INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS (ICCCN 2022)
(2022)
Article
Computer Science, Theory & Methods
Hisham A. Kholidy
Summary: This paper discusses the increasing attacks and vulnerabilities in Cyber-Physical Systems (CPS) and the need for advanced security approaches. By introducing an Autonomous Response Controller (ARC), the CPS is shown to be able to effectively respond to attacks and recover to normal state.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Oceanography
Arezoo Nazerdeylami et al.
Summary: Human impact on coastal ecosystems is a global concern, and using artificial intelligence for coastal monitoring automation provides opportunities for effective governance and management of coastal areas. This study focuses on autonomous litter surveying and human activity monitoring, showcasing promising results for enhancing coastal management efficiency and accuracy.
OCEAN & COASTAL MANAGEMENT
(2021)
Editorial Material
Engineering, Electrical & Electronic
Sudip K. Mazumder et al.
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(2021)
Article
Computer Science, Theory & Methods
Zhihan Lv et al.
Summary: The combination of artificial intelligence and CPSs in buildings is explored to promote their use in the construction industry. A CPS-based indoor environment measurement and control system is designed, which shows excellent effectiveness and robustness with good temperature control capability.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Automation & Control Systems
Beibei Li et al.
Summary: The study introduces a novel federated deep learning scheme named DeepFed for detecting cyber threats against industrial CPSs. By designing a new intrusion detection model and federated learning framework, the research successfully achieves secure detection of various cyber threats.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Ahmad Ali AlZubi et al.
Summary: Cyber-physical systems in healthcare utilize a cognitive machine learning assisted Attack Detection Framework to securely share healthcare data for decision support, achieving high accuracy and efficiency in predicting cyber-attack behavior.
Article
Computer Science, Hardware & Architecture
Marwa Keshk et al.
Summary: The paper introduces a new privacy-preserving anomaly detection framework called PPAD-CPS, which protects confidential information and detects malicious observations in power systems and their network traffic. Experimental results show that the framework is more effective than four recent techniques and outperforms seven peer anomaly detection techniques in terms of detection rate, false positive rate, and computational time.
IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Petar Radanliev et al.
Summary: This article conducts a literature review of current and future challenges in the use of artificial intelligence in cyber physical systems, focusing on the conceptual framework for increasing resilience and decision-making evolution. The methodology of taxonomic analysis is applied to complex IoT interconnected systems. Increased attention is given to proposals on IoT models in academic and technical papers.
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SYSTEMS ENGINEERING
(2020)
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(2020)
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(2020)
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Dan Ye et al.
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(2019)
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Magdi S. Mahmoud et al.
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Tanushree Agarwal et al.
IET CYBER-PHYSICAL SYSTEMS: THEORY & APPLICATIONS
(2019)
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Computer Science, Interdisciplinary Applications
Azfar Khalid et al.
COMPUTERS IN INDUSTRY
(2018)
