2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT)最新文献_第5页

Trajectory Planing for Cooperating Unmanned Aerial Vehicles in the IoT 物联网中协同无人机的轨迹规划

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-02-24 DOI: 10.3390/iot3010010

Emmanuel Tuyishimire, A. Bagula, S. Rekhis, N. Boudriga

{"title":"Trajectory Planing for Cooperating Unmanned Aerial Vehicles in the IoT","authors":"Emmanuel Tuyishimire, A. Bagula, S. Rekhis, N. Boudriga","doi":"10.3390/iot3010010","DOIUrl":"https://doi.org/10.3390/iot3010010","url":null,"abstract":"The use of Unmanned Aerial Vehicles (UAVs) in data transport has attracted a lot of attention and applications, as a modern traffic engineering technique used in data sensing, transport, and delivery to where infrastructure is available for its interpretation. Due to UAVs’ constraints such as limited power lifetime, it has been necessary to assist them with ground sensors to gather local data, which has to be transferred to UAVs upon visiting the sensors. The management of such ground sensor communication together with a team of flying UAVs constitutes an interesting data muling problem, which still deserves to be addressed and investigated. This paper revisits the issue of traffic engineering in Internet-of-Things (IoT) settings, to assess the relevance of using UAVs for the persistent collection of sensor readings from the sensor nodes located in an environment and their delivery to base stations where further processing is performed. We propose a persistent path planning and UAV allocation model, where a team of heterogeneous UAVs coming from various base stations are used to collect data from ground sensors and deliver the collected information to their closest base stations. This problem is mathematically formalised as a real-time constrained optimisation model, and proven to be NP-hard. The paper proposes a heuristic solution to the problem and evaluates its relative efficiency through performing experiments on both artificial and real sensors networks, using various scenarios of UAVs settings.","PeriodicalId":6745,"journal":{"name":"2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT)","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88463793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Emerging Trends and Challenges in Fog and Edge Computing for the Internet of Things 物联网雾和边缘计算的新趋势和挑战

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-02-16 DOI: 10.3390/iot3010009

Bastien Confais, B. Parrein

引用次数: 1

Assessing Feature Representations for Instance-Based Cross-Domain Anomaly Detection in Cloud Services Univariate Time Series Data 评估云服务单变量时间序列数据中基于实例的跨域异常检测的特征表示

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-29 DOI: 10.3390/iot3010008

Rahul Agrahari, Matthew Nicholson, Clare Conran, H. Assem, John D. Kelleher

引用次数: 2

Acknowledgment to Reviewers of IoT in 2021 向2021年物联网审稿人致谢

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-28 DOI: 10.3390/iot3010007

引用次数: 1

Will the Internet of Things Be Perovskite Powered? Energy Yield Measurement and Real-World Performance of Perovskite Solar Cells in Ambient Light Conditions 物联网将由钙钛矿供电吗?环境光条件下钙钛矿太阳能电池的能量产率测量和实际性能

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-18 DOI: 10.3390/iot3010006

Suzanne K. Thomas, A. Pockett, K. Seunarine, Michael Spence, D. Raptis, S. Meroni, T. Watson, Matt Jones, Matthew J. Carnie

{"title":"Will the Internet of Things Be Perovskite Powered? Energy Yield Measurement and Real-World Performance of Perovskite Solar Cells in Ambient Light Conditions","authors":"Suzanne K. Thomas, A. Pockett, K. Seunarine, Michael Spence, D. Raptis, S. Meroni, T. Watson, Matt Jones, Matthew J. Carnie","doi":"10.3390/iot3010006","DOIUrl":"https://doi.org/10.3390/iot3010006","url":null,"abstract":"The number of interconnected devices, often referred to as the Internet of Things (IoT), is increasing at a considerable rate. It is inevitable therefore that so too will the energy demand. IoT describes a range of technologies such as sensors, software, smart meters, wearable devices, and communication beacons for the purpose of connecting and exchanging data with other devices and systems over the internet. Often not located near a mains supply power source, these devices may be reliant on primary battery cells. To avoid the need to periodically replace these batteries, it makes sense to integrate the technologies with a photovoltaic (PV) cell to harvest ambient light, so that the technologies can be said to be self-powered. Perovskite solar cells have proven extremely efficient in low-light conditions but in the absence of ambient and low-light testing standards, or even a consensus on what is defined by “ambient light”, it is difficult to estimate the energy yield of a given PV technology in a given scenario. Ambient light harvesting is complex, subject to spectral considerations, and whether the light source is directly incident on the PV cell. Here, we present a realistic scenario-driven method for measuring the energy yield for a given PV technology in various situations in which an IoT device may be found. Furthermore, we show that laboratory-built p-i-n perovskite devices, for many scenarios, produce energy yields close to that of commercial GaAs solar cells. Finally, we demonstrate an IoT device, powered by a mesoporous carbon perovskite solar module and supercapacitor, and operating through several day–night cycles.","PeriodicalId":6745,"journal":{"name":"2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT)","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76086981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

How Does Green Robotics Differ from Conventional Robotics: Comparative Analysis 绿色机器人与传统机器人有何不同:比较分析

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-01 DOI: 10.1007/978-3-030-79496-5_31

O. Pichkov, A. A. Ulanov, Olga S. Vinokurova

引用次数: 1

Not for “Green”: Risks of Inflating a “New-Bubble” by Applying Traditional Financial Mechanisms 不是为了“绿色”:运用传统金融机制吹大“新泡沫”的风险

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-01 DOI: 10.1007/978-3-030-79496-5_25

Vitaly V. Demidov

引用次数: 0

Mechanism of Implementation of “Green” Investment-Innovative Initiatives in “Smart” Production Under the Control of Artificial Intelligence in the Interests of Environmental Safety of the Region 基于区域环境安全的人工智能控制下“绿色”投资创新在“智能”生产中的实施机制

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-01 DOI: 10.1007/978-3-030-79496-5_42

O. Karpovich, Murat A. Bulgarov, Nelia Deberdeeva, E. Abashin

引用次数: 0

Managing Industry 4 Technology and Innovation 管理工业4技术和创新

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-01 DOI: 10.1007/978-3-030-79496-5_32

Jeff Schubert

引用次数: 0

Brazil’s Green Energy: Today and Tomorrow 巴西的绿色能源:今天和明天

2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT) Pub Date : 2022-01-01 DOI: 10.1007/978-3-030-79496-5_13

E. Khartukov, Ellen E. Starostina

引用次数: 0