Biblio
Filters: Author is Liew, Soung-Yue [Clear All Filters]
Inter-Batch Gap Filling Using Compressive Sampling for Low-Cost IoT Vibration Sensors. 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). :1—6.
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2021. To measure machinery vibration, a sensor system consisting of a 3-axis accelerometer, ADXL345, attached to a self-contained system-on-a-chip with integrated Wi-Fi capabilities, ESP8266, is a low-cost solution. In this work, we first show that in such a system, the widely used direct-read-and-send method which samples and sends individually acquired vibration data points to the server is not effective, especially using Wi-Fi connection. We show that the micro delays in each individual data transmission will limit the sensor sampling rate and will also affect the time of the acquired data points not evenly spaced. Then, we propose that vibration should be sampled in batches before sending the acquired data out from the sensor node. The vibration for each batch should be acquired continuously without any form of interruption in between the sampling process to ensure the data points are evenly spaced. To fill the data gaps between the batches, we propose the use of compressive sampling technique. Our experimental results show that the maximum sampling rate of the direct-read-and-send method is 350Hz with a standard uncertainty of 12.4, and the method loses more information compared to our proposed solution that can measure the vibration wirelessly and continuously up to 633Hz. The gaps filled using compressive sampling can achieve an accuracy in terms of mean absolute error (MAE) of up to 0.06 with a standard uncertainty of 0.002, making the low-cost vibration sensor node a cost-effective solution.
A Network Architecture Containing Both Push and Pull Semantics. 2021 7th International Conference on Computer and Communications (ICCC). :2211—2216.
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2021. Recently, network usage has evolved from resource sharing between hosts to content distribution and retrieval. Some emerging network architectures, like Named Data Networking (NDN), focus on the design of content-oriented network paradigm. However, these clean-slate network architectures are difficult to be deployed progressively and deal with the new communication requirements. Multi-Identifier Network (MIN) is a promising network architecture that contains push and pull communication semantics and supports the resolution, routing and extension of multiple network identifiers. MIN's original design was proposed in 2019, which has been improved over the past two years. In this paper, we present the current design and implementation of MIN. We also propose a fallback-based identifier extension scheme to improve the extensibility of the network. We demonstrate that MIN outperforms NDN in the scenario of progressive deployment via IP tunnel.