Dr Sanaullah Jan's Outputs (29)

CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning (2021)
Journal Article
Saeed, U., Lee, Y.-D., Jan, S. U., & Koo, I. (2021). CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning. Sensors, 21(2), Article 617. https://doi.org/10.3390/s21020617

Sensors’ existence as a key component of Cyber-Physical Systems makes it susceptible to failures due to complex environments, low-quality production, and aging. When defective, sensors either stop communicating or convey incorrect information. These... Read More about CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning.

Fault diagnosis based on extremely randomized trees in wireless sensor networks (2020)
Journal Article
Saeed, U., Jan, S. U., Lee, Y.-D., & Koo, I. (2021). Fault diagnosis based on extremely randomized trees in wireless sensor networks. Reliability Engineering and System Safety, 205, Article 107284. https://doi.org/10.1016/j.ress.2020.107284

Wireless Sensor Network (WSN) being highly diversified cyber–physical system makes it vulnerable to numerous failures, which can cause devastation towards safety, economy, and systems’ reliability. Precise detection and diagnosis of failures or fault... Read More about Fault diagnosis based on extremely randomized trees in wireless sensor networks.

A distributed sensor-fault detection and diagnosis framework using machine learning (2020)
Journal Article
Jan, S. U., Lee, Y. D., & Koo, I. S. (2021). A distributed sensor-fault detection and diagnosis framework using machine learning. Information Sciences, 547, 777-796. https://doi.org/10.1016/j.ins.2020.08.068

The objective of this work is to design a sensor-fault detection and diagnosis system for the Internet of Things and Cyber-Physical Systems. The challenge is, however, achieving this objective within the limited computation, memory, and energy resour... Read More about A distributed sensor-fault detection and diagnosis framework using machine learning.

Toward a Lightweight Intrusion Detection System for the Internet of Things (2019)
Journal Article
Jan, S. U., Ahmed, S., Shakhov, V., & Koo, I. (2019). Toward a Lightweight Intrusion Detection System for the Internet of Things. IEEE Access, 7, 42450-42471. https://doi.org/10.1109/access.2019.2907965

Integration of the Internet into the entities of the different domains of human society (such as smart homes, health care, smart grids, manufacturing processes, product supply chains, and environmental monitoring) is emerging as a new paradigm called... Read More about Toward a Lightweight Intrusion Detection System for the Internet of Things.

A Novel Feature Selection Scheme and a Diversified-Input SVM-Based Classifier for Sensor Fault Classification (2018)
Journal Article
Jan, S. U., & Koo, I. (2018). A Novel Feature Selection Scheme and a Diversified-Input SVM-Based Classifier for Sensor Fault Classification. Journal of Sensors, 2018, Article 7467418. https://doi.org/10.1155/2018/7467418

The efficiency of a binary support vector machine- (SVM-) based classifier depends on the combination and the number of input features extracted from raw signals. Sometimes, a combination of individual good features does not perform well in discrimin... Read More about A Novel Feature Selection Scheme and a Diversified-Input SVM-Based Classifier for Sensor Fault Classification.

Throughput Maximization Using an SVM for Multi-Class Hypothesis-Based Spectrum Sensing in Cognitive Radio (2018)
Journal Article
Jan, S. U., Vu, V.-H., & Koo, I. (2018). Throughput Maximization Using an SVM for Multi-Class Hypothesis-Based Spectrum Sensing in Cognitive Radio. Applied Sciences, 8(3), Article 421. https://doi.org/10.3390/app8030421

A framework of spectrum sensing with a multi-class hypothesis is proposed to maximize the achievable throughput in cognitive radio networks. The energy range of a sensing signal under the hypothesis that the primary user is absent (in a conventional... Read More about Throughput Maximization Using an SVM for Multi-Class Hypothesis-Based Spectrum Sensing in Cognitive Radio.

Sensor Fault Classification Based on Support Vector Machine and Statistical Time-Domain Features (2017)
Journal Article
Jan, S. U., Lee, Y.-D., Shin, J., & Koo, I. (2017). Sensor Fault Classification Based on Support Vector Machine and Statistical Time-Domain Features. IEEE Access, 5, 8682-8690. https://doi.org/10.1109/access.2017.2705644

This paper deals with the problem of fault detection and diagnosis in sensors considering erratic, drift, hard-over, spike, and stuck faults. The data set containing samples of the above mentioned fault signals was acquired as follows: normal data si... Read More about Sensor Fault Classification Based on Support Vector Machine and Statistical Time-Domain Features.

Application of Navigating System based on Bluetooth Smart (2017)
Journal Article
Lee, Y., Jan, S. U., & Koo, I. (2017). Application of Navigating System based on Bluetooth Smart. Journal of the Institute of Internet, Broadcasting and Communication, 17(1), 69-76. https://doi.org/10.7236/jiibc.2017.17.1.69

Bluetooth Low Energy (BLE), also known as Bluetooth Smart, has ultra-low power consumption; in fact, BLE-enabled devices can run on a single coin cell battery for several years. In addition, BLE can estimate the approximate distance between two devi... Read More about Application of Navigating System based on Bluetooth Smart.

Modeling and Analysis of DIPPM: A New Modulation Scheme for Visible Light Communications (2015)
Journal Article
Jan, S. U., Lee, Y.-D., & Koo, I. (2015). Modeling and Analysis of DIPPM: A New Modulation Scheme for Visible Light Communications. Journal of Sensors, 2015, Article 963296. https://doi.org/10.1155/2015/963296

Visible Light Communication (VLC) uses an Intensity-Modulation and Direct-Detection (IM/DD) scheme to transmit data. However, the light source used in VLC systems is continuously switched on and off quickly, resulting in flickering. In addition, rece... Read More about Modeling and Analysis of DIPPM: A New Modulation Scheme for Visible Light Communications.