Internet of Things Application for Online Surveillance and Control of Attacks by Sea Lice

2021 ◽  
pp. 253-261
Author(s):  
Nhut Tran-Minh ◽  
Bard Haug ◽  
Bendik Fyhn Terjesen ◽  
Frank Karlsen
Keyword(s):  
Internet Of Things ◽  
Sea Lice ◽  
And Control

scholarly journals A Conceptual Model of Measurement Uncertainty in IoT Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1827
Author(s):  
Piotr Cofta ◽  
Kostas Karatzas ◽  
Cezary Orłowski
Keyword(s):  
Sensor Networks ◽  
Internet Of Things ◽  
Reference Model ◽  
Primary Objective ◽  
Theory And Practice ◽  
Fitness For Purpose ◽  
Industrial Practice ◽  
Control Networks ◽  
And Control ◽  
Measurement And Control

The growing popularity of inexpensive IoT (Internet of Things) sensor networks makes their uncertainty an important aspect of their adoption. The uncertainty determines their fitness for purpose, their perceived quality and the usefulness of information they provide. Nevertheless, neither the theory nor the industrial practice of uncertainty offer a coherent answer on how to address uncertainty of networks of this type and their components. The primary objective of this paper is to facilitate the discussion of what progress should be made regarding the theory and the practice of uncertainty of IoT sensor networks to satisfy current needs. This paper provides a structured overview of uncertainty, specifically focusing on IoT sensor networks. It positions IoT sensor networks as contrasted with professional measurement and control networks and presents their conceptual sociotechnical reference model. The reference model advises on the taxonomy of uncertainty proposed in this paper that demonstrates semantic differences between various views on uncertainty. This model also allows for identifying key challenges that should be addressed to improve the theory and practice of uncertainty in IoT sensor networks.

IoT-based Precision Agriculture Platform: A Review

2021 ◽  
Vol 9 (9) ◽  
pp. 1419-1421
Author(s):  
Rutvik Solanki
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Agricultural Sector ◽  
Disease Outbreaks ◽  
Iot Platforms ◽  
High Level ◽  
New Applications ◽  
And Control ◽  
Use Of Internet ◽  
The Internet Of Things

Abstract: Technological advancements such as the Internet of Things (IoT) and Artificial Intelligence (AI) are helping to boost the global agricultural sector as it is expected to grow by around seventy percent in the next two decades. There are sensor-based systems in place to keep track of the plants and the surrounding environment. This technology allows farmers to watch and control farm operations from afar, but it has a few limitations. For farmers, these technologies are prohibitively expensive and demand a high level of technological competence. Besides, Climate change has a significant impact on crops because increased temperatures and changes in precipitation patterns increase the likelihood of disease outbreaks, resulting in crop losses and potentially irreversible plant destruction. Because of recent advancements in IoT and Cloud Computing, new applications built on highly innovative and scalable service platforms are now being developed. The use of Internet of Things (IoT) solutions has enormous promise for improving the quality and safety of agricultural products. Precision farming's telemonitoring system relies heavily on Internet of Things (IoT) platforms; therefore, this article quickly reviews the most common IoT platforms used in precision agriculture, highlighting both their key benefits and drawbacks

Application of Internet of Things intelligent image-positioning studio classroom in English teaching

2021 ◽  
pp. 1-11
Author(s):  
Jie Chen ◽  
Yukun Chen ◽  
Jiaxin Lin
Keyword(s):  
Internet Of Things ◽  
Language Learning ◽  
Learning Strategies ◽  
English Teaching ◽  
Classroom Activities ◽  
Post Test ◽  
Studio Classroom ◽  
And Control ◽  
Self Learning ◽  
Intelligent Positioning

The purpose is to minimize color overflow and color patch generation in intelligent images and promote the application of the Internet of Things (IoT) intelligent image-positioning studio classroom in English teaching. Here, the Convolutional Neural Network (CNN) algorithm is introduced to extract and classify features for intelligent images. Then, the extracted features can position images in real-time. Afterward, the performance of the CNN algorithm is verified through training. Subsequently, two classes in senior high school are selected for experiments, and the influences of IoT intelligent image-positioning studio classroom on students’ performance in the experimental class and control class are analyzed and compared. The results show that the introduction of the CNN algorithm can optimize the intelligent image, accelerate the image classification, reduce color overflow, brighten edge color, and reduce color patches, facilitating intelligent image editing and dissemination. The feasibility analysis proves the effectiveness of the IoT intelligent image-positioning studio classroom, which is in line with students’ language learning rules and interests and can involve students in classroom activities and encourage self-learning. Meanwhile, interaction and cooperation can help students master learning strategies efficiently. The experimental class taught with the IoT intelligent positioning studio has made significant progress in academic performance, especially, in the post-test. In short, the CNN algorithm can promote IoT technologies and is feasible in English teaching.

Caligids-potential pathogens for marine finfish aquaculture in Mexico?

2017 ◽  
Vol 44 (3) ◽  
pp. 433-441
Author(s):  
Francisco Neptalí Morales-Serna ◽  
Juan Manuel Martínez-Brown ◽  
Rosa Maria Medina-Guerrero ◽  
Emma Josefina Fajer-Ávila
Keyword(s):  
Coastal Waters ◽  
Host Location ◽  
Current Knowledge ◽  
Control Strategies ◽  
Sea Lice ◽  
Ecological Studies ◽  
Parasitic Copepods ◽  
The Family ◽  
And Control ◽  
Finfish Aquaculture

Parasitic copepods of the family Caligidae, the so-called sea lice, may be deleterious to marine or brackish finfish aquaculture. To date, biological and ecological studies of sea lice have been mostly restricted to species from cold or temperate regions. In Mexico there are some records of sea lice species on marine fishes; however, the research regarding their biology and ecology has been scarce. It is possible that a high biodiversity of sea lice is distributed in coastal waters of Mexico; therefore, their significance as pathogenic parasites should increase. The purpose of this review is to outline the current knowledge of the life cycle, host location, ecology, effect on fish health, and control strategies of sea lice in order to establish supportive basis for natural resource management and control of parasites and diseases of marine fish cultured in Mexico.

Sectional Data Acquisition and Control System for Solar Street Lamps Based on Internet of Things

2013 ◽  
Vol 773 ◽  
pp. 148-153 ◽  
Author(s):  
Juan Zhou ◽  
Bing Yan Chen ◽  
Meng Ni Zhang ◽  
Ying Ying Tang
Keyword(s):  
Control System ◽  
Internet Of Things ◽  
Data Acquisition ◽  
Real Time ◽  
Network Flow ◽  
Short Interval ◽  
Management Problem ◽  
Time Data ◽  
Control Centre ◽  
And Control

Aiming at the management problem of real-time data created while intelligent solar street lamps working, sectional data acquisition and control system based on internet of things is introduced in the paper. Communication protocol with unified form and flexible function is designed in the system, and communication address is composed of sectional address and subsection address. Three-level data structure is built in the polling algorithm to trace real-time state of lamps and to detect malfunction in time, which is suitable for sectional lamps management characteristics. The system reflects necessary statistic data and exception information to remote control centre through GPRS to short interval expend on transmission and procession and save network flow and system energy. The result shows the system brings improved management affection and accords with the idea of energy-saving and environmental protection.

scholarly journals Device-Based Security to Improve User Privacy in the Internet of Things †

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2664 ◽  
Author(s):  
Luis Belem Pacheco ◽  
Eduardo Pelinson Alchieri ◽  
Priscila Mendez Barreto
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Single Point ◽  
Data Access ◽  
Cloud Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Privacy And Security ◽  
Iot Devices ◽  
And Control

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

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