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A Review on Moisture Measurement Technique in Agricultural Silos

IOP Conference Series: Materials Science and Engineering 2019年第1期705卷

作者： M S M Abdullah M H F Rahiman A Zakaria L M Kamarudin L Mohamed Centre of Excellence for Advanced Sensor Technology (CEASTech) Universiti Malaysia Perlis Pauh Putra Campus 02600 Arau Perlis Malaysia.

Moisture content (MC) is that the weight of water contained in paddy and other grans expressed in percent. Moisture content is typically mentioned the wet basis which means the whole weight of the grain including the water (MCwb). Accurate MC testing is very important in managing and selling paddy and rice because depending on the aim rice has completely different ideal MC. Inaccurate MC measurements lead to lower head rice once milled at wrong moisture content, additional drying cost and loss of quality if paddy is dried too much, spoilage if the grain is just too wet in storage, additional drying cost and harvesting loss if paddy is harvested wetter than necessary and Weight loss (loss in profit) if grain is sold too dry. This paper intends to review the available techniques of moisture content measurements, its principles and sources of inaccuracies. Relevant properties of cereal grain also are studied with their impact on moisture content, temperature, density and humidity. There are several ways of grain moisture detection such as drying technique, resistance technique, capacitance technique, microwave technique, neutron technique, V/F Conversion, Ftir spectroscopic technique and Microcontroller technique. Current MC of grains are based- on sampling and individual single point measurement, so far, there is no available overall measurement of MC in silo, but by using tomography method can measurement MC in whole silo and investigate the efficiency and accuracy of localization of moisture distributions sensing in agricultural silo by using Gaussian algorithm.

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Relay Selection Strategy (RSS) Design for In-Vehicle Storage (IVS) System

Relay Selection Strategy (RSS) Design for In-Vehicle Storage...

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IEEE Global Communications Conference

作者： Binbin Hu Rongqing Zhang Luoyang Fang Xiang Cheng Liuqing Yang State Key Laboratory of Advanced Optical Communication Systems & Networks School of EECS Peking University Beijing China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Software Engineering Tongji University Shanghai China Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

In recent years, autonomous driving has attracted a vast amount of attention from both industry and academia, which has introduced large amounts of region-related data. In order to release the burden in core networks caused by the communication demands for such data, various in-vehicle storage (IVS) systems have been widely studied to bring contents closer to users. To cope with the mobility issue hindering the realization of IVS systems, in this paper, we propose a relay selection strategy (RSS) consisting of the relay map construction (RMC) algorithm and the relay pair matching (RPM) algorithm with the assistance of the vehicle route information. By considering both the potential transmission amount and the waiting time, the proposed RSS generates an overall optimal relay assignment for the IVS system. The performance gain of the proposed RSS compared with the baseline is evaluated by a realistic simulator in terms of the relay failure ratio, the retrieval throughput, and the RSU consumption ratio. Simulation results show that the proposed RSS achieves higher efficiency and robustness than the baseline.

关键词： Relays Roads Robustness Prediction algorithms Mathematical model Wireless sensor networks Micromechanical devices

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Recent Advancements in Radio Frequency based Indoor Localization Techniques

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Journal of Physics: Conference Series 2021年第1期1755卷

作者： Kenny Fong Peng Wye Syed Muhammad Mamduh Syed Zakaria Latifah Munirah Kamarudin Ammar Zakaria Norhawati Binti Ahmad School of Microelectronic Engineering Universiti Malaysia Perlis (UniMAP) Kampus Pauh Putra Arau Perlis 02600 Malaysia Centre of Excellence for Advanced Sensor Technology (CEASTech) Universiti Malaysia Perlis (UniMAP) Kompleks Pengajian Jejawi II Arau Perlis 02600 Malaysia School of Computer Engineering Universiti Malaysia Perlis (UniMAP) Kampus Pauh Putra Arau Perlis 02600 Malaysia School of Mechatronic Engineering Universiti Malaysia Perlis (UniMAP) Kampus Pauh Putra Arau Perlis 02600 Malaysia

Recent developments in location-based services have heightened the needs for decent accuracy localization system for different applications. The Global Positioning System (GPS) provides adequate accuracy in the outdoor environment but suffers from poor localization accuracy in the complex and dynamic indoor environment. Therefore, the number of indoor localization researches to apply in different applications with different technologies have increased in recent years. The purpose of this paper is to summarize recent advancements in Radio Frequency (RF) based indoor localization techniques and provide insights in the indoor localization field especially in the range based localization. The range based localization is then categorized into few common algorithms such as AOA, TOA, TDOA and RSS. The discussion between algorithms in term of their advantages, disadvantages and improvement strategies to improve their accuracy are also present in this paper.

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SLAM-GDM Implementation on Robot Operating System for Gas Source Localization

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IOP Conference Series: Materials Science and Engineering 2019年第1期705卷

作者： K W Soo K Kamarudin V H Bennetts R Visvanathan A S Ali Yeon S M Mamduh A Zakaria School of Mechatronics Engineering Universiti Malaysia Perlis (UniMAP) Arau Malaysia Centre of Excellence for Advanced Sensor Technology (CEASTech) Universiti Malaysia Perlis Arau Malaysia Applied Autonomous Sensor systems Orebro University Orebro Sweden

Gas Distribution Mapping (GDM) can be defined as visualization for the spatial distribution of gas concentration in an unknown indoor environment. Recently, incidents of gas leakage have increased gradually worldwide. This will significantly increase the casualty rate at the workplace. This paper focusses on the implementation of Kernel DM based SLAM- GDM on Robot Operating System (ROS), a novel approach that will be useful in the effort of localizing the gas source during gas leakage inspection. This approach has been conducted successfully by using ROS-architecture implemented system, tested in simulation and on a mobile robot. The result shows that this implementation achieved average accuracy of 0.71m and 0.32m and therefore deemed suitable for gas source location prediction.

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RSS-based Fingerprinting Localization with Artificial Neural Network

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Journal of Physics: Conference Series 2021年第1期1755卷

作者： Kenny Fong Peng Wye Syed Muhammad Mamduh Syed Zakaria Latifah Munirah Kamarudin Ammar Zakaria Norhawati Binti Ahmad Kamarulzaman Kamarudin School of Microelectronic Engineering Universiti Malaysia Perlis (UniMAP) Kampus Pauh Putra Arau Perlis 02600 Malaysia Centre of Excellence for Advanced Sensor Technology (CEASTech) Universiti Malaysia Perlis (UniMAP) Kompleks Pengajian Jejawi II Arau Perlis 02600 Malaysia School of Computer Engineering Universiti Malaysia Perlis (UniMAP) Kampus Pauh Putra Arau Perlis 02600 Malaysia School of Mechatronic Engineering Universiti Malaysia Perlis (UniMAP) Kampus Pauh Putra Arau Perlis 02600 Malaysia

Radio Frequency (RF) based indoor is challenging due to the multipath effect in indoor signal propagation such as reflection, absorption, diffraction due to obstacles, interference and moving objects within the environments. The multipath effect phenomenon will be worsened if Received Signal Strength (RSS) is used as the localization measurement parameter. The advancement of Artificial Intelligence (AI) may hold the key for the improvement of RSS based localization. The Artificial Neural Network (ANN) in AI outperforms the traditional algorithms in indoor localization due to its capability to learn the unique features given in the training datasets. This paper discusses indoor fingerprinting localization with different architectures of ANN network to localize object of interest with the given indoor environment. The size of the experimental testbed is 14m x 8m and the testbed consists of four identical receivers that receive the signal from an active transmitter. All the tested ANN architectures have RSS as inputs and the Cartesian coordinates as outputs with different hidden layers and hidden nodes. The relationship between hidden nodes and layers in ANN and the regression losses is studied in this paper. The RSS-based fingerprinting with ANN in this paper is considered as a multi-output regression problem. The result shows that the ANN architecture with four layers with a total number of 800 hidden nodes has achieved an average of 6.01098 regression losses and a mean Euclidean Distance error of 2.54m.

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Ammonia, acetone and ethanol gas sensing characteristics of CuO thin films grown by sputtering 2

Ammonia, acetone and ethanol gas sensing characteristics of ...

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2nd International Conference on Materials Science and technology, ICMST 2016

作者： Anna Jacob, Anju Balakrishnan, L. Meher, S.R. Sivacoumar, R. Shambavi, K. Alex, Z.C. School of Electronics Engineering VIT University Vellore632 014 India Department of Physics Government College of Technology Coimbatore641 013 India Department of Physics School of Advanced Sciences VIT University Vellore632 014 India Department of Sensor and Biomedical Technology School of Electronics Engineering VIT University Vellore632 014 India Department of Communication School of Electronics Engineering VIT University Vellore632 014 India

Here, we have reported the sensing characteristics of CuO thin films towards volatile gases like ammonia, acetone and ethanol. The CuO films were deposited on glass substrate by RF magnetron sputtering at 350 °C and 400 °C. The characteristics of CuO thin films grown at both temperatures were analyzed using X-ray diffractometer (XRD), UV-Vis spectrometer, atomic force microscope (AFM), scanning electron microscope (SEM) and Fourier transform infrared spectrometer (FTIR). The thin films showed mesoporous morphology with average crystallite size of 78 nm and 36 nm for films grown at 350 °C and 400 °C, respectively. As the film grown at 400 °C showed better properties, it has been preferred for the gas sensing analysis. Gas sensing properties of the film towards different concentration (50-250 ppm) of ammonia, acetone and ethanol were studied in chemi-resistive mode. As expected, an increase in resistance with concentration of gases was observed due to the p-type nature of CuO thin films. Further, the film showed comparatively better sensitivity towards ethanol than other gases. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Thin films

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Horizontal Transport in Ti3C2TxMXene for Highly Efficient Osmotic Energy Conversion from Saline-Alkali Environments

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Angewandte Chemie 2024年第48期136卷

作者： Han Qian Puguang Peng Hongzhao Fan Zhe Yang Lixue Yang Prof. Yanguang Zhou Prof. Dan Tan Feiyao Yang Prof. Morten Willatzen Prof. Gehan Amaratunga Prof. Zhonglin Wang Prof. Di Wei Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing 101400 People's Republic of China School of Nanoscience and Engineering University of Chinese Academy of Sciences Beijing 100049 People's Republic of China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong SAR People's Republic of China School of Advanced Materials and Nanotechnology Xidian University Xi'an 710126 People's Republic of China Zhejiang University—University of Illinois at Urbana Champagne Institute (ZJUI) and School of Information Science and Electronics Zhejiang University International Campus Haining China Electrical Engineering Division Dept. of Engineering University of Cambridge Cambridge CB3 0FA UK School of Materials Science and Engineering Georgia Institute of Technology Atlanta GA 30332 USA Beijing Key Laboratory of Micro-Nano Energy and Sensor Center for High-Entropy Energy and Systems Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing 101400 People's Republic of China Centre for Photonic Devices and Sensors University of Cambridge 9 JJ Thomson Avenue Cambridge CB3 0FA UK

Osmotic energy from the ocean has been thoroughly studied, but that from saline-alkali lakes is constrained by the ion-exchange membranes due to the trade-off between permeability and selectivity, stemming from the unfavorable structure of nanoconfined channels, pH tolerance, and chemical stability of the membranes. Inspired by the rapid water transport in xylem conduit structures, we propose a horizontal transport MXene (H-MXene) with ionic sequential transport nanochannels, designed to endure extreme saline-alkali conditions while enhancing ion selectivity and permeability. The H-MXene demonstrates superior ion conductivity of 20.67 S m −1 in 1 M NaCl solution and a diffusion current density of 308 A m −2 at a 10-fold salinity gradient of NaCl solution, significantly outperforming the conventional vertical transport MXene (V-MXene). Both experimental and simulation studies have confirmed that H-MXene represents a novel approach to circumventing the permeability-selectivity trade-off. Moreover, it exhibits efficient ion transport capabilities, addressing the gap in saline-alkali osmotic power generation.

关键词： Ti3C2Tx MXene Osmotic Energy Nanoconfined Channels Horizontal Transport Saline-alkali Environments

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Effect of Poly Ethylene Glycol (PEG) on Structural, Thermal and Photoluminescence Properties of CdO Nanoparticles For Optoelectronic Applications

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Materials Today: Proceedings 2019年 9卷 175-183页

作者： P Lokanatha Reddy Kalim Deshmukh K. Chidambaram Basheer Ahamed Kishor Kumar Sadasivuni Deepalekshmi Ponnamma Rajasekhar Lakshmipathy Desagani Dayananda S.K. Khadheer Pasha Sensor Laboratory Materials Physics Division School of Advanced Sciences VIT University Vellore Tamil Nadu 632014 India Department of Physics B.S. Abdur Rahman University Chennai 600 048 TN India Mechanical & Industrial Engineering Department Qatar University P.O. Box 2713 Doha Qatar Center for Advanced Materials Qatar University P.O. Box 2713 Doha Qatar Centre for Material Science KCG College of Technology Chennai Tamil Nadu India Department of SSCU IISC Bangalore Karnataka 560012 India Department of Physics VIT-AP University Amaravati Campus Guntur 522501 Andhra Pradesh India

Current study deals with capped / uncapped Cadmium Oxide Nanoparticles (CdO NPs) synthesized by chemical precipitation technique. Structural, morphological, thermal and optical properties of these samples were investigated by XRD, TGA, TEM and PL spectra. XRD revealed the face centered cubic structure of CdO which was depicted at 400 ° C for both samples. The calculated XRD values were in good consistent with the predicted values of TEM analysis and also with Thermogravimetric analysis. Intense emission peaks at 474 nm and 615 nm were observed in PL spectra at 325 nm excitation wavelengths in uncapped CdO NPs, while capped CdO NPs showed peaks with less intensity. These emissions may be due to the indirect near band gap emission and excitonic transition of CdO NPs. Hence based on these results it could be concluded that capping agent (PEG) tuned CdO NPs can be used for optoelectronic device applications.

关键词： Cadmium oxide Nanoparticles (CdO NPs) Polyethylene glycol (PEG) Transition Electron Microscopy (TEM) Photoluminescence (PL)

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Development of MOX Gas sensors Module for Indoor Air Contaminant Measurement

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IOP Conference Series: Materials Science and Engineering 2019年第1期705卷

作者： A N Abdullah K Kamarudin S M Mamduh A H Adom School of Mechatronics Engineering Universiti Malaysia perlis (UniMAP) Arau Malaysia Centre of Excellence for Advanced Sensor Technology (CEASTech) Universiti Malaysia Perlis Arau Malaysia

This paper presents the development of gas sensor module consisting of metal oxide (MOX) gas sensors for indoor air contaminant measurement. The first phase of the studies involves the design of PCBs board for six different metal oxide (MOX) gas sensors particularly CCS803, MiCS5524, GM-402B, GM-502B, GM-702B and MiCS6814. Next, the main board consisting of temperature, humidity and another two MOX gas sensors (i.e TGS2600 and TGS2602) was developed for the acquisition of the sensors. A partially closed chamber was designed and fabricated to fit the main board and allows inflow and outflow of gases. The responses of the gas sensors were measured in a closed room, with the air conditioner turned on and off periodically. The results show that all the MOX gas sensor used are affected by temperature and humidity of the environment. Therefore, the sensor response drift needs to be corrected in order to obtain reliable indoor air contaminant measurement.

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Fuzzy K-Nearest Neighbour (FkNN) Based Early Stage Fire Source Classification in Building

Fuzzy K-Nearest Neighbour (FkNN) Based Early Stage Fire Sour...

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IEEE Conference on Systems, Process & Control (ICSPC)

作者： A. M. Andrew A. Y. M. Shakaff A. Zakaria R. Gunasagaran E. Kanagaraj S. M. Saad Centre of Excellence for Advanced Sensor Technology (CEASTech) Universiti Malaysia Perlis (UniMAP) Arau Perlis Malaysia Department of Applied Mechanics and Design Universiti Teknologi Malaysia (UTM) Skudai Johor Malaysia

ISBN: (纸本)9781538663288;9781538663271

Assessing the smell of burning is vital, as it can help to further detect and prevent early fire. In this paper, an early stage fire detection algorithm has been introduced using Fuzzy k- Nearest Neighbour (FkNN). The tests were made on normally available seven fire sources and three building structure resources. All the test samples were scorched in a vacuum oven at various temperature points, pushed out using vacuum pumps to be sniffed by the electronic nose. The experiments were done in a confined room with monitored temperature and humidity level. Time domain data were sampled. Prior to be given to the classifier, the smellprints were normalised and the features were extracted. Experimental classification results show that the integration of fuzzy logic into conventional kNN has enhanced the accuracy of the classifier and gave excellent consistency, nonetheless of humidity and temperature disparity, baseline sensor errors, the diverse emission concentration range and varied scorching temperature levels. The average classification precision for the classification system is 96.15%.

关键词： Fires Buildings Electronic noses Temperature sensors Feature extraction Humidity Gas detectors

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