2,862 research outputs found
Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids
Smart grids incorporate diverse power equipment used for energy optimization in intelligent cities. This equipment may use Internet of Things (IoT) devices and services in the future. To ensure stable operation of smart grids, cybersecurity of IoT is paramount. To this end, use of cryptographic security methods is prevalent in existing IoT. Non-cryptographic methods such as radio frequency fingerprinting (RFF) have been on the horizon for a few decades but are limited to academic research or military interest. RFF is a physical layer security feature that leverages hardware impairments in radios of IoT devices for classification and rogue device detection. The article discusses the potential of RFF in wireless communication of IoT devices to augment the cybersecurity of smart grids. The characteristics of a deep learning (DL)-aided RFF system are presented. Subsequently, a deployment framework of RFF for smart grids is presented with implementation and regulatory aspects. The article culminates with a discussion of existing challenges and potential research directions for maturation of RFF.publishedVersio
Enabling Cyber Physical Systems with Wireless Sensor Networking Technologies
[[abstract]]Over the last few years, we have witnessed a growing interest in Cyber Physical Systems (CPSs) that rely on a strong synergy between computational and physical components. CPSs are expected to have a tremendous impact on many critical sectors (such as energy, manufacturing, healthcare, transportation, aerospace, etc) of the economy. CPSs have the ability to transform the way human-to-human, human-toobject, and object-to-object interactions take place in the physical and virtual worlds. The increasing pervasiveness of Wireless Sensor Networking (WSN) technologies in many applications make them an important component of emerging CPS designs. We present some of the most important design requirements of CPS architectures. We discuss key sensor network characteristics that can be leveraged in CPS designs. In addition, we also review a few well-known CPS application domains that depend on WSNs in their design architectures and implementations. Finally, we present some of the challenges that still need to be addressed to enable seamless integration of WSN with CPS designs.[[incitationindex]]SCI[[booktype]]็ด
Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3D Indoor Monitoring
As a result of extensive research over the past decade or so, wireless sensor networks (wsns) have evolved into a well established technology for industry, environmental and medical applications. However, traditional wsns employ such sensors as thermal or photo light resistors that are often modeled with simple omni-directional sensing ranges, which focus only on scalar data within the sensing environment. In contrast, the sensing range of a wireless video sensor is directional and capable of providing more detailed video information about the sensing field. Additionally, with the introduction of modern features in non-fixed focus cameras such as the pan, tilt and zoom (ptz), the sensing range of a video sensor can be further regarded as a fan-shape in 2d and pyramid-shape in 3d. Such uniqueness attributed to wireless video sensors and the challenges associated with deployment restrictions of indoor monitoring make the traditional sensor coverage, deployment and networked solutions in 2d sensing model environments for wsns ineffective and inapplicable in solving the wireless video sensor network (wvsn) issues for 3d indoor space, thus calling for novel solutions. In this dissertation, we propose optimization techniques and develop solutions that will address the coverage, deployment and network issues associated within wireless video sensor networks for a 3d indoor environment. We first model the general problem in a continuous 3d space to minimize the total number of required video sensors to monitor a given 3d indoor region. We then convert it into a discrete version problem by incorporating 3d grids, which can achieve arbitrary approximation precision by adjusting the grid granularity. Due in part to the uniqueness of the visual sensor directional sensing range, we propose to exploit the directional feature to determine the optimal angular-coverage of each deployed visual sensor. Thus, we propose to deploy the visual sensors from divergent directional angles and further extend k-coverage to ``k-angular-coverage\u27\u27, while ensuring connectivity within the network. We then propose a series of mechanisms to handle obstacles in the 3d environment. We develop efficient greedy heuristic solutions that integrate all these aforementioned considerations one by one and can yield high quality results. Based on this, we also propose enhanced depth first search (dfs) algorithms that can not only further improve the solution quality, but also return optimal results if given enough time. Our extensive simulations demonstrate the superiority of both our greedy heuristic and enhanced dfs solutions. Finally, this dissertation discusses some future research directions such as in-network traffic routing and scheduling issues
Unlocking Solar Power For Surveillance A Review Of Solar Powered CCTV And Surveillance Technologies
Solar-powered surveillance technologies have gained prominence for their sustainable, autonomous, and
versatile solutions. This comprehensive review explores three key solar-powered surveillance technologies:
solar-powered CCTV cameras, solar drones, and solar-powered sensor networks. Each technology offers
distinct strengths and weaknesses, making them suitable for various applications. Solar-powered CCTV
cameras provide adaptability, energy independence, and rapid deployment, while solar drones offer an aerial
perspective, extended endurance, and versatility. Solar-powered sensor networks excel in localized
environmental monitoring. The choice of technology depends on factors such as the surveillance
environment, budget constraints, required surveillance range, and specific monitoring needs. Organizations
can benefit from hybrid solutions that integrate multiple technologies for comprehensive coverage. Future
trends include advanced energy storage solutions, AI integration, enhanced power efficiency, and cloud-based
data analytics, promising to improve performance and sustainability. Public-private collaborations and
sustainable urban planning initiatives will drive further adoption and integration. Solar-powered
surveillance technologies empower effective and environmentally sustainable surveillance solutions,
contributing to a safer and more sustainable future
Internet Predictions
More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section
Practical applications of multi-agent systems in electric power systems
The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur
Proceedings of Abstracts Engineering and Computer Science Research Conference 2019
ยฉ 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is ยฉ 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care
Approximation algorithms for mobile multi-agent sensing problem
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ผ๋ฌธ (์์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณต๊ณผ๋ํ ์ฐ์
๊ณตํ๊ณผ, 2020. 8. ๋ฌธ์ผ๊ฒฝ.Multi-agent systems are generally applicable in a wide diversity of domains, such as robot engineering, computer science, the military, and smart cities. In particular, the mobile multi-agent sensing problem can be defined as a problem of detecting events occurring in a large number of nodes using moving agents. In this thesis, we introduce a mobile multi-agent sensing problem and present a mathematical formulation. The model can be represented as a submodular maximization problem under a partition matroid constraint, which is NP-hard in general. The optimal solution of the model can be considered computationally intractable. Therefore, we propose two approximation algorithms based on the greedy approach, which are global greedy and sequential greedy algorithms, respectively. We present new approximation ratios of the sequential greedy algorithm and prove tightness of the ratios. Moreover, we show that the sequential greedy algorithm is competitive with the global greedy algorithm and has advantages of computation times. Finally, we demonstrate the performances of our results through numerical experiments.๋ค์ค ์์ด์ ํธ ์์คํ
์ ์ผ๋ฐ์ ์ผ๋ก ๋ก๋ด ๊ณตํ, ์ปดํจํฐ ๊ณผํ, ๊ตฐ์ฌ ๋ฐ ์ค๋งํธ ๋์์ ๊ฐ์ ๋ค์ํ ๋ถ์ผ์ ์ ์ฉํ ์ ์๋ค. ํนํ, ๋ชจ๋ฐ์ผ ๋ค์ค ์์ด์ ํธ ๊ฐ์ง ๋ฌธ์ ๋ ์์ง์ด๋ ์์ด์ ํธ๋ฅผ ์ด์ฉํด ๋ง์ ์์ ๋
ธ๋์์ ๋ฐ์ํ๋ ์ด๋ฒคํธ๋ฅผ ๊ฐ์งํ๋ ๋ฌธ์ ๋ก ์ ์ํ ์ ์๋ค. ๋ณธ ๋
ผ๋ฌธ์์๋ ๋ชจ๋ฐ์ผ ๋ค์ค ์์ด์ ํธ ๊ฐ์ง ๋ฌธ์ ์ ์ํ์ ๊ณต์์ ์ ์ํ๋ค. ์ด ๋ฌธ์ ๋ ์ผ๋ฐ์ ์ผ๋ก NP-๋ํด ๋ฌธ์ ์ธ ๋ถํ ๋งคํธ๋ก์ด๋ ์ ์ฝ ํ์์ ํ์ ๋ชจ๋ ํจ์์ ์ต๋ํ ๋ฌธ์ ๋ก ํํํ ์ ์๋ค. ๋ฌธ์ ์ ์ต์ ํด๋ ์
๋ ฅ ๋ฐ์ดํฐ์ ํฌ๊ธฐ๊ฐ ์ปค์ง์๋ก ๋ณดํต ํฉ๋ฆฌ์ ์ธ ์๊ฐ ์ด๋ด์ ๊ณ์ฐํ๊ธฐ ์ด๋ ต๋ค. ๋ฐ๋ผ์ ๋ณธ ๋
ผ๋ฌธ์์๋ ํ์์ ์ ๊ทผ ๋ฐฉ์์ ๊ธฐ์ดํ ๋ ๊ฐ์ง ๊ทผ์ฌ ์๊ณ ๋ฆฌ์ฆ (์ ์ญ ํ์ ์๊ณ ๋ฆฌ์ฆ, ์์ฐจ ํ์ ์๊ณ ๋ฆฌ์ฆ)์ ์ ์ํ๋ค. ๋ํ, ์์ฐจ ํ์ ์๊ณ ๋ฆฌ์ฆ์ ์๋ก์ด ๊ทผ์ฌ ๋น์จ์ ์ฆ๋ช
ํ๊ณ ๊ทผ์ฌ ๋น์จ์ ์ ํํ๊ฒ ์ผ์นํ๋ ์ธ์คํด์ค๋ฅผ ์ ์ํ๋ค. ๋ํ, ์์น ์คํ ๊ฒฐ๊ณผ๋ก ์์ฐจ ํ์ ์๊ณ ๋ฆฌ์ฆ์ ํจ๊ณผ์ ์ธ ํด๋ฅผ ์ฐพ์์ค ๋ฟ ์๋๋ผ, ์ ์ญ ํ์ ์๊ณ ๋ฆฌ์ฆ๊ณผ ๋น๊ตํด ๊ณ์ฐ ์๊ฐ์ ์ด์ ์ ๊ฐ์ง๊ณ ์์์ ํ์ธํ๋ค.Chapter 1 Introduction 1
Chapter 2 Literature Review 4
Chapter 3 Problem statement 7
Chapter 4 Algorithms and approximation ratios 11
Chapter 5 Computational Experiments 22
Chapter 6 Conclusions 30
Bibliography 31
๊ตญ๋ฌธ์ด๋ก 40Maste
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