• Title/Summary/Keyword: IoST

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Design and Evaluation of the Internet-Of-Small-Things Prototype Powered by a Solar Panel Integrated with a Supercapacitor

  • Park, Sangsoo
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.11
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    • pp.11-19
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    • 2021
  • In this paper, we propose a prototype platform combined with the power management system using, as an auxiliary power storage device, a supercapacitor that can be fast charged and discharged with high power efficiency as well as semi-permanent charge and discharge cycle life. For the proposed platform, we designed a technique which is capable of detecting the state of power cutoff or resumption of power supplied from the solar panel in accordance with physical environment changes through an interrupt attached to the micro-controller was developed. To prevent data loss in a computing environment in which continuous power supply is not guaranteed, we implemented a low-level system software in the micro-controller to transfer program context and data in volatile memory to nonvolatile memory when power supply is cut off. Experimental results shows that supercapacitors effectively supply temporary power as auxiliary power storage devices. Various benchmarks also confirm that power state detection and transfer of program context and data from volatile memory to nonvolatile memory have low overhead.

A semi-supervised interpretable machine learning framework for sensor fault detection

  • Martakis, Panagiotis;Movsessian, Artur;Reuland, Yves;Pai, Sai G.S.;Quqa, Said;Cava, David Garcia;Tcherniak, Dmitri;Chatzi, Eleni
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.251-266
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    • 2022
  • Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

Process Standardization for the Construction of Job-Exposure Matrix Using the Work Environment Measurement Database (작업환경측정 결과 데이터베이스를 활용한 직무노출매트릭스 구축을 위한 공정 표준화)

  • Sangjun Choi;Ju-Hyun Park;Dong-Hee Koh;Donguk Park;Hwan-Cheol Kim;Dae Sung Lim;Yeji Sung;Kyoung Yoon Ko;Ji Seon Lim;Hoekyeong Seo
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.33 no.1
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    • pp.78-90
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    • 2023
  • Objectives: The purpose of this study is to standardize the process code of the work environment measurement database (WEMD) for the construction of a job-exposure matrix (JEM). Methods: The standard process code (SPC) was reclassified based on process similarity and drawing upon the code used in the existing K2B. It was supplemented through review by industrial hygiene experts. In addition, an index word database related to SPC was created and used for SPC search. A pilot evaluation project was conducted by experts to evaluate the validity of the newly reclassified standard process code. Results: A total of 70 final SPCs were developed, including 31 processes related to the construction industry. Using the Shiny program, we developed a standard code finder that can be used on the web (https://kscf.shinyapps.io/scf_app/). As a result of the pilot evaluation, it was determined that it was easier to search for standard codes than previous codes, so it was highly utilized. Conclusions: It is expected that JEM construction using industry-process information drawing on WEMD data will be possible using the 70 newly standardized process codes.