RSS stabilization techniques for a real-time passive UHF RFID pipe monitoring system for smart shipyards

Fraga‐Lamas, Paula; Fernández‐Caramés, Tiago M.; Noceda-Davila, Diego; Vilar-Montesinos, Miguel

doi:10.1109/rfid.2017.7945603

Cited by 36 publications

(30 citation statements)

References 14 publications

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“…In the past, researchers have used diverse technologies for connecting remote outdoor IoT nodes with smart campus platforms. Note that such technologies may differ a great deal from one scenario to another, as the distance to be covered and the kind obstacles found in the environment (especially, metallic objects [136]), severely condition signal propagation.…”

Section: Communications Technologiesmentioning

confidence: 99%

Towards Next Generation Teaching, Learning, and Context-Aware Applications for Higher Education: A Review on Blockchain, IoT, Fog and Edge Computing Enabled Smart Campuses and Universities

2019

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Smart campuses and smart universities make use of IT infrastructure that is similar to the one required by smart cities, which take advantage of Internet of Things (IoT) and cloud computing solutions to monitor and actuate on the multiple systems of a university. As a consequence, smart campuses and universities need to provide connectivity to IoT nodes and gateways, and deploy architectures that allow for offering not only a good communications range through the latest wireless and wired technologies, but also reduced energy consumption to maximize IoT node battery life. In addition, such architectures have to consider the use of technologies like blockchain, which are able to deliver accountability, transparency, cyber-security and redundancy to the processes and data managed by a university. This article reviews the state of the start on the application of the latest key technologies for the development of smart campuses and universities. After defining the essential characteristics of a smart campus/university, the latest communications architectures and technologies are detailed and the most relevant smart campus deployments are analyzed. Moreover, the use of blockchain in higher education applications is studied. Therefore, this article provides useful guidelines to the university planners, IoT vendors and developers that will be responsible for creating the next generation of smart campuses and universities.

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Section: Communications Technologiesmentioning

confidence: 99%

Towards Next Generation Teaching, Learning, and Context-Aware Applications for Higher Education: A Review on Blockchain, IoT, Fog and Edge Computing Enabled Smart Campuses and Universities

2019

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“…Nonetheless, positioning a user indoors is more difficult [94], so it is required to study the scenario and make use of specific location techniques that can be applied to most of the communications technologies cited in the previous subsection. Among such techniques, the ones based on Received Signal Strength Indicator (RSSI) or Received Signal Strength (RSS) can provide good accuracy when positioning in limited areas [95][96][97], but their heavily depend on the scenario and on the used hardware [98].…”

Section: Communications Subsystemmentioning

confidence: 99%

Towards The Internet of Smart Clothing: A Review on IoT Wearables and Garments for Creating Intelligent Connected E-Textiles

2018

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Technology has become ubiquitous, it is all around us and is becoming part of us. Together with the rise of the Internet-of-Things (IoT) paradigm and enabling technologies (e.g., Augmented Reality (AR), Cyber-Physical Systems, Artificial Intelligence (AI), blockchain or edge computing), smart wearables and IoT-based garments can potentially have a lot of influence by harmonizing functionality and the delight created by fashion. Thus, smart clothes look for a balance among fashion, engineering, interaction, user experience, cybersecurity, design and science to reinvent technologies that can anticipate needs and desires. Nowadays, the rapid convergence of textile and electronics is enabling the seamless and massive integration of sensors into textiles and the development of conductive yarn. The potential of smart fabrics, which can communicate with smartphones to process biometric information such as heart rate, temperature, breathing, stress, movement, acceleration, or even hormone levels, promises a new era for retail. This article reviews the main requirements for developing smart IoT-enabled garments and shows smart clothing potential impact on business models in the medium-term. Specifically, a global IoT architecture is proposed, the main types and components of smart IoT wearables and garments are presented, their main requirements are analyzed and some of the most recent smart clothing applications are studied. In this way, this article reviews the past and present of smart garments in order to provide guidelines for the future developers of a network where garments will be connected like other IoT objects: the Internet-of-Smart-Clothing.

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“…Among the different available indoor location techniques, those based on Received Signal Strength Indicator (RSSI) or Received Signal Strength (RSS) have proved their accuracy when positioning in limited areas [101,102], but their heavily depend on characteristics of the scenario (e.g., presence of metallic objects) and on the used UAV hardware (e.g., antennas) [103]. There are also positioning techniques based on computing the Angle of Arrival (AoA) of the received signals [104], or their time of arrival (through Time of Arrival (ToA) and Time Difference of Arrival (TDoA) techniques) [105].…”

Section: Positioning Subsystemmentioning

confidence: 99%

A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance

et al. 2019

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Advances in Unmanned Aerial Vehicles (UAVs), also known as drones, offer unprecedented opportunities to boost a wide array of large-scale Internet of Things (IoT) applications. Nevertheless, UAV platforms still face important limitations mainly related to autonomy and weight that impact their remote sensing capabilities when capturing and processing the data required for developing autonomous and robust real-time obstacle detection and avoidance systems. In this regard, Deep Learning (DL) techniques have arisen as a promising alternative for improving real-time obstacle detection and collision avoidance for highly autonomous UAVs. This article reviews the most recent developments on DL Unmanned Aerial Systems (UASs) and provides a detailed explanation on the main DL techniques. Moreover, the latest DL-UAV communication architectures are studied and their most common hardware is analyzed. Furthermore, this article enumerates the most relevant open challenges for current DL-UAV solutions, thus allowing future researchers to define a roadmap for devising the new generation affordable autonomous DL-UAV IoT solutions.

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RSS stabilization techniques for a real-time passive UHF RFID pipe monitoring system for smart shipyards

Cited by 36 publications

References 14 publications

Towards Next Generation Teaching, Learning, and Context-Aware Applications for Higher Education: A Review on Blockchain, IoT, Fog and Edge Computing Enabled Smart Campuses and Universities

Towards Next Generation Teaching, Learning, and Context-Aware Applications for Higher Education: A Review on Blockchain, IoT, Fog and Edge Computing Enabled Smart Campuses and Universities

Towards The Internet of Smart Clothing: A Review on IoT Wearables and Garments for Creating Intelligent Connected E-Textiles

A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance

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