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Carlo Ciaponi, Enrico Creaco, Armando Di Nardo, Michele Di Natale, Carlo Giudicianni, Dino Musmarra and Giovanni Francesco Santonastaso
This paper proposes a combined management strategy for monitoring water distribution networks (WDNs). This strategy is based on the application of water network partitioning (WNP) for the creation of district metered areas (DMAs) and on the installation ...
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Kexiang Qian, Hongyu Yang, Ruyu Li, Weizhe Chen, Xi Luo and Lihua Yin
With the rapid growth of IoT devices, the threat of botnets is becoming increasingly worrying. There are more and more intelligent detection solutions for botnets that have been proposed with the development of artificial intelligence. However, due to th...
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Mohamed Shenify, Fokrul Alom Mazarbhuiya and A. S. Wungreiphi
There are many applications of anomaly detection in the Internet of Things domain. IoT technology consists of a large number of interconnecting digital devices not only generating huge data continuously but also making real-time computations. Since IoT d...
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Haedam Kim, Suhyun Park, Hyemin Hong, Jieun Park and Seongmin Kim
As the size of the IoT solutions and services market proliferates, industrial fields utilizing IoT devices are also diversifying. However, the proliferation of IoT devices, often intertwined with users? personal information and privacy, has led to a cont...
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Oscar Leonardo García-Navarrete, Adriana Correa-Guimaraes and Luis Manuel Navas-Gracia
Weeds are unwanted and invasive plants that proliferate and compete for resources such as space, water, nutrients, and sunlight, affecting the quality and productivity of the desired crops. Weed detection is crucial for the application of precision agric...
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Yunsong Jia, Qingxin Zhao, Yi Xiong, Xin Chen and Xiang Li
The issues of inadequate digital proficiency among agricultural practitioners and the suboptimal image quality captured using mobile smart devices have been addressed by providing appropriate guidance to photographers to properly position their mobile de...
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Ruicheng Gao, Zhancai Dong, Yuqi Wang, Zhuowen Cui, Muyang Ye, Bowen Dong, Yuchun Lu, Xuaner Wang, Yihong Song and Shuo Yan
In this study, a deep-learning-based intelligent detection model was designed and implemented to rapidly detect cotton pests and diseases. The model integrates cutting-edge Transformer technology and knowledge graphs, effectively enhancing pest and disea...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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Xinyi Meng and Daofeng Li
The explosive growth of malware targeting Android devices has resulted in the demand for the acquisition and integration of comprehensive information to enable effective, robust, and user-friendly malware detection. In response to this challenge, this pa...
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Cheolhyeon Kwon and Donghyun Kang
Recently, the technologies of on-device AI have been accelerated with the development of new hardware and software platforms. Therefore, many researchers and engineers focus on how to enable ML technologies on mobile devices with limited hardware resourc...
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