Wireless Sensing and Networking for the Internet of Things

Lin, Zihuai; Wang, Xiang

doi:10.3390/s23031461

Cited by 3 publications

(3 citation statements)

References 18 publications

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“…Scientists are investigating clustering methods to enhance data forwarding in LoRa networks, achieving a balance between energy efficiency and dependable communication [15]. In addition, there has been a development of comprehensive sensor energy analysis and modeling techniques to assist developers in optimizing LoRaWAN deployments that are tailored to specific applications [16].…”

Section: Literature Reviewmentioning

confidence: 99%

Enabling The E-NOSE: Evaluating Network Technologies for Optimized Odor Data Transmission in IoT and Edge Computing Applications

Ayad A. Al-Ani

2024

jes

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Electronic Noses (e-noses) are advanced sensors that are being increasingly used in the Internet of Things (IoT) field. They have various applications in environmental monitoring and medical diagnostics. Optimal transmission of odor-related data is essential for fully harnessing the capabilities of these electronic noses in various network environments. This research paper examines the issue of transmitting odor data in Internet of Things (IoT) applications by assessing recent progress in communication and network technologies. A thorough analysis of various network alternatives, such as Ethernet, cellular (4G/5G), Wi-Fi, Bluetooth, Zigbee, and LoRa, is provided, accompanied by an elaborate table displaying precise technical specifications. The analysis of LoRa, a Low-Power Wide-Area Network (LPWAN) technology, encompasses an investigation into its architecture, modulation method, device classifications, and protocols such as LoRaWAN. The analysis of Edge Computing and cloud-based approaches for managing odor data in IoT culminates in a tabular presentation that succinctly outlines their advantages and disadvantages. This study provides valuable information to enhance the efficiency of transmitting odor data and effectively utilize electronic nose technology in different emerging applications in the Internet of Things (IoT) field.

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Section: Literature Reviewmentioning

confidence: 99%

Enabling The E-NOSE: Evaluating Network Technologies for Optimized Odor Data Transmission in IoT and Edge Computing Applications

Ayad A. Al-Ani

2024

jes

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“…We multiply the PDF in (12) and the differential volume in ( 14) and then substitute d from (13). Therefore, we can get the expression for Φ(α),…”

Section: Performance Analysismentioning

confidence: 99%

“…Internet of Things (IoT) [9]- [12] and the fifth Generation (5G) communication system [13]- [19] need to balance between low latency and high accuracy. An RIS is a panel, typically square or circular, composed of numerous reflecting elements.…”

Section: Introductionmentioning

confidence: 99%

Probability of Error for Optimal Codes in a Reconfigurable Intelligent Surface Aided URLLC System

Sui

Lin

2023

IEEE Commun. Lett.

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The lower bound on the decoding error probability for the optimal code given a signal-to-noise ratio and a code rate are investigated in this letter for the reconfigurable intelligent surface (RIS) communication system over a Rician fading channel at the short blocklength regime, which is the key characteristic of ultra-reliable low-latency communications (URLLC) to meet the need for strict adherence to quality of service (QoS) requirements. Sphere packing technique is used to derive our main results. The Wald sequential t-test lemma and the Gaussian-Chebyshev quadrature are the main tools to obtain the closed-form expression for the lower bound. Numerical results are provided to validate our results and demonstrate the tightness of our results compared to the Polyanskiy-Poor-Verdu (PPV) bound.

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Advancements in Metal‐Organic, Enzymatic, and Nanocomposite Platforms for Wireless Sensors of the Next Generation

Mohan,

Virender,

Gupta

et al. 2024

Adv Funct Materials

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Advanced wireless sensors, incorporating metal‐organic frameworks (MOFs), enzymatic systems, and nanocomposites, offer unparalleled solutions for monitoring analytes and human physiological signals. These cutting‐edge sensors, when used with external devices, enable real‐time monitoring of analytes and physicochemical processes within the human body, thereby enhancing the understanding of complex biological systems. This study presents advancements in sensor development, fabrication techniques, and user‐friendly protocols. The performance of these sensors is evaluated based on their selectivity, sensitivity, and detection limits. Moreover, this article explores limitations, challenges, and key strategies to enhance analyte recognition from onsite environmental and biological species, ensuring human point‐of‐care safety.

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Wireless Sensing and Networking for the Internet of Things

Cited by 3 publications

References 18 publications

Enabling The E-NOSE: Evaluating Network Technologies for Optimized Odor Data Transmission in IoT and Edge Computing Applications

Enabling The E-NOSE: Evaluating Network Technologies for Optimized Odor Data Transmission in IoT and Edge Computing Applications

Probability of Error for Optimal Codes in a Reconfigurable Intelligent Surface Aided URLLC System

Advancements in Metal‐Organic, Enzymatic, and Nanocomposite Platforms for Wireless Sensors of the Next Generation

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