Wireless Sensors for Analysis Transport Systems

Panayotova, Galina; Димитров, Георги; Dimitrov, Dimitar A.

doi:10.12720/jcm.13.1.40-44

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…5 demonstrates how increasing image quality influence on result file size, the most interesting thing is that relation for both image sizes is close to identical. Also, it is quite easy to see that for all [1,100], PSNR PSNR   there is such a value that for all less SSIM  is growing much faster and for all greater vice versa. This is a clear indication that once you achieve some level of quality, getting more is going to cost doubling network traffic and as a result making whole technology useless.…”

Section: Jpeg 2000 Experimental Resultsmentioning

confidence: 99%

“…Massive IoT applications, on the other hand, refers to applications which are less latency-sensitive and have lower throughput requirements but require many low-cost, low-energy consumption devices on a network with excellent coverage. 1 The growing popularity of IoT has driven up the demand for massive IoT technologies and the number of smart devices worldwide continues to increase at a dramatic pace. The key requirements for massive IoT are long battery life, good coverage, low cost, and performance flexibility.…”

Section: Introductionmentioning

confidence: 99%

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Adopting Machine Learning for Images Transferred with LoRaWAN

Brazhenenko¹,

Shevchenko²,

Bychkov³

et al. 2020

ISIJ

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LPWAN (Low-power Wide-area network) networks are well-known since the 1980s, but due to low efficiency were not in active use for a long time. Modern LPWAN is a game-changing technology with true power in network coverage, cost efficiency, and low operational expenses. LPWAN services' most frequent market is in smart cities, agriculture, healthcare, and civil defence systems. LoRa is considered one of the market leaders in LPWAN; however, the low bandwidth of its physical layer makes it unsuitable for high-speed transmission. The provision of integrity, availability, and confidentiality in IoT networks is still of major concern. Data accuracy and lack of control over the transmission of personal information prevents the active use of the technology in regulated industries, such as healthcare and civil defence. In this article, we adopt LoRa for the transmission of media content, with an ability to regulate the quality of data and achieve desired level of integrity and availability. This allows the system to self-configure (train) via more reliable machine learning techniques.

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Section: Jpeg 2000 Experimental Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adopting Machine Learning for Images Transferred with LoRaWAN

Brazhenenko¹,

Shevchenko²,

Bychkov³

et al. 2020

ISIJ

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“…1 Sensors are used for Big Data collecting and measurement tasks (temperature, pressure, flow rate, etc. ), 2; 3 analysis, 4 scanning, 5 detecting. 6 Also, sensors are parts and widely used in the Internet of Things and Industrial Internet of Things concepts.…”

Section: Introductionmentioning

confidence: 99%

Information Technology for Big Data Sensor Networks Stability Estimation

Petrivskyi¹,

Димитров²,

Shevchenko³

et al. 2020

ISIJ

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Sensors and sensor networks are widely used in various industries and human activities and main components of the Internet of Things and Industrial Internet of Things concepts. Nowadays, huge amounts of data, called Big Data, can be transported and collected using sensor networks. This article presents approaches for providing sensor networks' stability estimation for transporting Big Data and collecting respective use cases. The proposed estimation method allows to detect sensor network's components that decrease data transport system stability. Consequently, additional connections or sensors can be added to increase stability. In the case of data collection, the solution consists of finding the most vulnerable sensor and an optimal position for the additional sensor with given intersection levels with other sensors. Simulation results confirm the feasibility and effectiveness of the proposed approaches.

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“…The wireless sensor network(WSN) consists of a large number of micro sensor nodes using wireless adhoc mode [1], [2], it is known as one of the most important technology of the 21st century and widely used [3], such as utilities, environmental monitoring, patient health monitoring, smart home, etc.…”

Section: Introductionmentioning

confidence: 99%

The Research on Time Synchronization Protocol of Lightweight for Wireless Sensor Network

2018

Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering

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Time synchronization technology is a challenging area of research in wireless sensor network. The diversity of wireless sensor network leads to the diversity of demands on the time synchronization mechanism; therefore, it is impossible to use one kind of time synchronization mechanism to satisfy all application requirements. Due to its own characteristics, wireless sensor network needs special requirements in synchronization precision, synchronization scope, and energy consumption etc. This paper presents a lightweight and active time synchronization protocol for wireless sensor network, being called LATS for short. It ensures that the synchronization accuracy in practical applications meets the circumstances while reducing the energy costs as far as possible. Finally, the performance of this protocol is proved by experiment.

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Wireless Sensors for Analysis Transport Systems

Cited by 4 publications

References 8 publications

Adopting Machine Learning for Images Transferred with LoRaWAN

Adopting Machine Learning for Images Transferred with LoRaWAN

Information Technology for Big Data Sensor Networks Stability Estimation

The Research on Time Synchronization Protocol of Lightweight for Wireless Sensor Network

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