Wavelet packet transform-based compression for teleoperation

Kuzu, Ahmet; Baran, Eray A.; Boğosyan, Seta; Gökaşan, Metin; Şabanoviç, Asif

doi:10.1177/0959651815575438

Cited by 6 publications

(4 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Apart from prediction, lossy kinesthetic data compression and decompression has also been achieved by using discrete cosine transform (DCT) [82], similarly to the JPEG codec, in a teleoperation system with force feedback with a compression ratio of 20%. Finally, another compression method that has been tested on 1-DoF haptic data is Wavelet Packet Transform (WPT) [83]. In this case, decompression is accomplished with the Inverse WPT (or IWPT).…”

Section: ) Statistical Schemesmentioning

confidence: 99%

Toward Haptic Communications Over the 5G Tactile Internet

Αντωνάκογλου

Steinbach

et al. 2018

IEEE Commun. Surv. Tutorials

215

125

View full text Add to dashboard Cite

show abstract

Section: ) Statistical Schemesmentioning

confidence: 99%

Toward Haptic Communications Over the 5G Tactile Internet

Αντωνάκογλου

Steinbach

et al. 2018

IEEE Commun. Surv. Tutorials

215

125

View full text Add to dashboard Cite

show abstract

“…WPT has excellent positional properties in both the time and frequency domains and is suitable for compression. Furthermore, proper selection of the wavelet function allows the same signal to be represented with smaller errors [21]. WPT is a well-known mathematical tool that has special advantages over the Fourier transformation in the analysis of unfixed signals because it provides an arbitrary time-frequency resolution with redundant base features.…”

Section: Preprocessing Methodsmentioning

confidence: 99%

LSTM-Autoencoder Based Anomaly Detection Using Vibration Data of Wind Turbines

Lee,

Park,

Kim

et al. 2024

Sensors

View full text Add to dashboard Cite

The problem of energy depletion has brought wind energy under consideration to replace oil- or chemical-based energy. However, the breakdown of wind turbines is a major concern. Accordingly, unsupervised learning was performed using the vibration signal of a wind power generator to achieve an outlier detection performance of 97%. We analyzed the vibration data through wavelet packet conversion and identified a specific frequency band that showed a large difference between the normal and abnormal data. To emphasize these specific frequency bands, high-pass filters were applied to maximize the difference. Subsequently, the dimensions of the data were reduced through principal component analysis, giving unique characteristics to the data preprocessing process. Normal data collected from a wind farm located in northern Sweden was first preprocessed, and a long short-term memory (LSTM) autoencoder, and outlier detection was performed. The LSTM Autoencoder is a model specialized for time-series data that learns the patterns of normal data and detects other data as outliers. Therefore, we propose a method for outlier detection through data preprocessing and unsupervised learning, utilizing the vibration signals from wind generators. This will facilitate the quick and accurate detection of wind power generator failures and provide alternatives to the problem of energy depletion.

show abstract

“…A motion copying experiment was organized to validate the proposed method. The work in [130] proposed Wave Packet Transformation (WPT) coding from image compressing for haptic data compression for teleoperation systems.…”

Section: Qos Qoementioning

confidence: 99%

QoS Provisioning: Key Drivers and Enablers Toward the Tactile Internet in Beyond 5G Era

et al. 2022

View full text Add to dashboard Cite

The Tactile Internet has become a revolution for Internet technology, greatly improving the transmission of skill sets (audio, video, text, and haptics) over communication channels compared with traditional triple-play data (audio, video, text). It is a strong candidate to support next-generation delay-sensitive and loss-intolerant smart applications. However, stringent requirements for the Tactile Internet, including ultra-low latency, ultra-high reliability, high availability, and ultra-security, present critical challenges to ensure Quality of Service (QoS). Consequently, several approaches have been proposed to meet these QoS requirements. This article reviews QoS provisioning approaches for the Tactile Internet. First, we present key concepts for the fifth-generation and beyond technologies, Tactile Internet, and haptic communication. Second, we discuss the Tactile Internet use cases along with strict QoS requirements. Third, we classify existing solutions, including haptic codecs, control system designs, hybrid schemes, and intelligent prediction models; provide in-depth discussion regarding these approaches to improve QoS for the Tactile Internet applications; and investigate strengths and weaknesses for each proposed solution. Finally, we present open research challenges and discuss potential future research avenues to realize the Tactile Internet services.

show abstract

Wavelet packet transform-based compression for teleoperation

Cited by 6 publications

References 42 publications

Toward Haptic Communications Over the 5G Tactile Internet

Toward Haptic Communications Over the 5G Tactile Internet

LSTM-Autoencoder Based Anomaly Detection Using Vibration Data of Wind Turbines

QoS Provisioning: Key Drivers and Enablers Toward the Tactile Internet in Beyond 5G Era

Contact Info

Product

Resources

About