2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)最新文献_第3页

Real-Time Outdoor Air Quality Monitoring System 实时室外空气质量监测系统

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526332

S. M. Abiduzzaman, H. Mansor, T. Gunawan, R. Ahmad

{"title":"Real-Time Outdoor Air Quality Monitoring System","authors":"S. M. Abiduzzaman, H. Mansor, T. Gunawan, R. Ahmad","doi":"10.1109/ICSIMA50015.2021.9526332","DOIUrl":"https://doi.org/10.1109/ICSIMA50015.2021.9526332","url":null,"abstract":"Air pollution has harmed human health as a human cannot live without breathing. Even more worrying is that air pollution seems to be increasing day by day due to man-made pollution or natural pollution like a massive forest fire. Due to no real-time monitoring device being implemented, the authorities are unaware of the real-time conditions of air quality. Therefore, this project is aimed to give real-time air quality and location data by designing and developing a portable device and mobile app capable of producing and broadcasting real-time Air Pollutant Index (API) and GPS coordinates. In this work, various air pollutant gases and problems of the present air quality monitoring system have been reviewed. Two different pollutant gas sensors, i.e., Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) sensors, and NEO-6M Global Positioning System (GPS) module, have been proposed. Air Pollutant Index (API) value and location data are determined by the system and uploaded to the cloud database. The developed mobile app retrieves the data, and anyone with the mobile app can get information about the location and its air quality in real-time. The system has been tested at two different places, and the results were compared with existing air-quality websites that were available online. Results showed that the system provides a 92.3% accuracy that is 5.1% more accurate than other systems. The proposed system could provide an important building block for smart city development.","PeriodicalId":404811,"journal":{"name":"2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131442390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A PXI Modules-Based Voltage Injection System for AC Resistors Calibration 基于PXI模块的交流电阻器电压注入标定系统

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526291

M. Ouameur, R. Vasconcellos, M. Agazar

引用次数: 1

The Performance of 2.4GHz and 5GHz Wi-Fi Router Placement for Signal Strength Optimization Using Altair WinProp 利用Altair WinProp优化2.4GHz和5GHz Wi-Fi路由器放置信号强度的性能

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526299

Ain Shazleen Haron, Z. Mansor, Izanoordina Ahmad, S. M. Maharum

{"title":"The Performance of 2.4GHz and 5GHz Wi-Fi Router Placement for Signal Strength Optimization Using Altair WinProp","authors":"Ain Shazleen Haron, Z. Mansor, Izanoordina Ahmad, S. M. Maharum","doi":"10.1109/ICSIMA50015.2021.9526299","DOIUrl":"https://doi.org/10.1109/ICSIMA50015.2021.9526299","url":null,"abstract":"The performance of 2.4GHz and 5GHz Wi-Fi router placement in the Communication Technology laboratories area at Universiti Kuala Lumpur British Malaysian Institute is investigated to address the intermittent connectivity problem observed in some areas. Altair WinProp is a wave propagation simulation tool that can simulate the interior of the building and examine wave propagation with a highly accurate result in a short amount of time. Using WinProp ProMan, the omnidirectional antenna patterns are placed at several locations within the focused area, and the propagation of each of the antennas is computed. The layout of the Communication Section laboratory is initially modelled. The specifications of the construction materials are assigned using WinProp WallMan. The router’s performance is evaluated based on the received signal strength. The procedure is repeated using a different frequency. These antennas’ performances are then compared to determine the optimum placement for the WiFi system at the Communication Technology laboratory area. In addition, the simulation results obtained using WinProp ProMan is validated by measuring the received signal strength using InSSIDer in the real environment. Finally, the optimum location for a radio signal to be broadcast from is identified. The results indicate that the wave propagation pattern can cover the entire Labs area in one go, with better signal strength at this position. The number of current access points can be reduced due to this optimisation, resulting in lower equipment costs and lower electricity bills.","PeriodicalId":404811,"journal":{"name":"2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131911810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Taguchi Optimisation of Piezoelectric Design for Hybrid Energy Harvesting of GPS Tracker Device GPS跟踪器混合能量采集压电设计的田口优化

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526325

Mohd Ismifaizul Mohd Ismail, R. Dziyauddin, R. Ahmad, A. Hamid, Shazlan Anwar

{"title":"Taguchi Optimisation of Piezoelectric Design for Hybrid Energy Harvesting of GPS Tracker Device","authors":"Mohd Ismifaizul Mohd Ismail, R. Dziyauddin, R. Ahmad, A. Hamid, Shazlan Anwar","doi":"10.1109/ICSIMA50015.2021.9526325","DOIUrl":"https://doi.org/10.1109/ICSIMA50015.2021.9526325","url":null,"abstract":"Wireless Sensor Node (WSN) of Global Positioning System (GPS) has a disadvantage in terms of high-power consumption. Energy harvesting is a technique that collects unused light, kinetic, thermal, mechanical, chemical, wind, acoustic and hybrid, and then converts them into usable electrical energy. The main objective of the current work is to explore an energy harvesting system using piezoelectric and solar energy harvesters for a sustainable hybrid GPS sensor tracker. The Taguchi method was used to determine the optimum design of the piezoelectric transducer. The output of the piezoelectric harvester was measured by vibration (time), while solar power harvesting depended on light sensitivity (lux). The Self-Powered GPS device (SP-Tracker), was tested in the laboratory as well as at the site. The results showed that the piezoelectric energy harvesting system that analysed using the DOE Taguchi method, reflected the measurements of voltage and optimum power outputs. The optimum piezoelectric device design obtained is 3 cm and 1 g for distance and weight, respectively, with a maximum power output of 217 mW. On the other hand, the ideal size and weight of a piezoelectric device are 3 cm and 1 g. Between 108.7 and 312 mW of electricity will be generated by the hybrid energy harvesting device for both purposes. The following effort will be directed toward creating and constructing low-power Lora sensor nodes.","PeriodicalId":404811,"journal":{"name":"2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","volume":"109 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131057448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Keynote 1: Radar and Magnetic Field Imaging of Hidden Objects 主题演讲1:隐藏物体的雷达和磁场成像

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/icsima50015.2021.9525937

A. B. Suksmono

引用次数: 0

Stiffness Measuring Device for Human Limb 人体肢体刚度测量装置

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526334

Osama Ahmad, Abdul Rehman, Abdurrehman Akhtar, Ayisha Nayyar

引用次数: 0

Impact of GSG Probe to Pads Contact Repeatability for On-Wafer RF Measurements 在晶圆射频测量中，GSG探针对焊盘接触可重复性的影响

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526303

Cerine Mokhtari, M. Sebbache, V. Avramovic, C. Boyaval, G. Dambrine, K. Haddadi

{"title":"Impact of GSG Probe to Pads Contact Repeatability for On-Wafer RF Measurements","authors":"Cerine Mokhtari, M. Sebbache, V. Avramovic, C. Boyaval, G. Dambrine, K. Haddadi","doi":"10.1109/ICSIMA50015.2021.9526303","DOIUrl":"https://doi.org/10.1109/ICSIMA50015.2021.9526303","url":null,"abstract":"Improving the contact repeatability for on-wafer measurements is required to address accurate characterization of microwave and millimeter-wave extreme impedance devices foreseen in future RF semi-conductor industry. In this effort, residual error terms introduced by conventional on-wafer probe measurements are quantified in the frequency range 50 MHz – 67 GHz. In particular, two sets of measurements considering movements of the probes in the Z-direction only and in X-Y-Z directions are considered. Controlling the probe in the XY axis showed better results in terms of repeatability, more than 10 times à 10 GHz and more than 5 times à 60 GHz. The residual error terms are propagated to determine the measurement uncertainty on the complex impedance of capacitances theoretically tested. Capacitance value of 1 fF measured at 10 GHz was measured with an error around 80 %. Moving the probe on the Z-direction only demonstrated that, if the X and Y movements of the probe are theoretically controlled, the error could be reduced to $sim 7$%. In addition, preliminary design and fabrication of a new compact on-wafer probe station built up with nanorobotics is proposed. Both chuck and RF probes are equipped with nano-positioning stages operating in close loop operation.","PeriodicalId":404811,"journal":{"name":"2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129747840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Development of Image-Based Emotion Recognition using Convolutional Neural Networks 基于图像的卷积神经网络情感识别的发展

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526329

Atiya Latif, T. Gunawan, M. Kartiwi, F. Arifin, H. Mansor

引用次数: 2

Aloha-NOMA for Ambient Backscatter M2M Communication in IoT Networks with Random Power Levels and Frequency Channel Assignment 随机功率和信道分配的物联网环境后向散射M2M通信Aloha-NOMA

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9525940

A. Halbouni, Muhammad Afiq Bin Abdul Ghani, M. H. Habaebi

{"title":"Aloha-NOMA for Ambient Backscatter M2M Communication in IoT Networks with Random Power Levels and Frequency Channel Assignment","authors":"A. Halbouni, Muhammad Afiq Bin Abdul Ghani, M. H. Habaebi","doi":"10.1109/ICSIMA50015.2021.9525940","DOIUrl":"https://doi.org/10.1109/ICSIMA50015.2021.9525940","url":null,"abstract":"Internet of Things as known as IoT is a network pointing to a series of interconnected devices that are communicating with each other. M2M communication protocol is integral part of IoT to allowing multiple devices to communicate smoothly. Aloha-NOMA for ambient backscatter M2M communication can provide high throughput matched with low complexity of Aloha-NOMA while leveraging on the low power and cost of ambient backscatter communication links. This paper critically studies the application of Aloha-NOMA for backscatter M2M communication utilizing multichannel and random power levels. In this paper, multichannel Aloha-NOMA throughput analysis had been done in order to observe the impact of adding sub channels. Throughput increased directly proportional as number of sub channels. Then, Aloha-NOMA performances are compared against Ambient Backscatter Aloha-NOMA in which more channels on the line with backscatter channels. Results indicate the combination of random power levels selection with random frequency channel selection yields significant throughput improvement.","PeriodicalId":404811,"journal":{"name":"2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122037751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning-Based Stress Level Detection from EEG Signals 基于机器学习的脑电信号应力水平检测

2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) Pub Date : 2021-08-23 DOI: 10.1109/ICSIMA50015.2021.9526333

Ali Nirabi, F. A. Rahman, M. H. Habaebi, K. Sidek, S. Yusoff

{"title":"Machine Learning-Based Stress Level Detection from EEG Signals","authors":"Ali Nirabi, F. A. Rahman, M. H. Habaebi, K. Sidek, S. Yusoff","doi":"10.1109/ICSIMA50015.2021.9526333","DOIUrl":"https://doi.org/10.1109/ICSIMA50015.2021.9526333","url":null,"abstract":"Recent statistical studies indicate an increase in mental stress in human beings around the world. Due to the recent pandemic and the subsequent lockdowns, people are suffering from different types of stress for being jobless, financially damaged, loss of business, deterioration of personal/family relationships, etc. Stress could be a severe factor for many common disorders if experienced for a long time. Stress is associated with the brain activities of human beings that can be scanned by electroencephalogram (EEG) signals which is very complex and often challenging to understand the signal’s pattern. This paper presented a system to detect the stress level from the EEG signals using machine learning algorithms. The proposed method, at first, removed physiological noises from the EEG signal applying a band-pass FIR filter. A discrete wavelet transform (DWT) method was used for features extraction from the filtered EEG signal. The features were classified using a set of classifiers those are k-nearest neighbors (kNN), support vector machine (SVM), Naïve Bayes, and linear discriminant analysis (LDA). Two levels of stressed EEG data were considered and found the classification accuracy of 86.3%, 91.0%, 81.7%, and 90.0%. The highest classification accuracy, the SVM classifier, outperforms the current state of the art by 15.8%.","PeriodicalId":404811,"journal":{"name":"2021 IEEE 7th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","volume":"226 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120940612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4