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Nanostructure Based Sensors for Gas Sensing: from Devices to Systems

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ISBN: 9783039216369 9783039216376 Year: Pages: 86 DOI: 10.3390/books978-3-03921-637-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 16:10:12
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The development of solid state gas sensors based on microtransducers and nanostructured sensing materials is the key point in the design of portable measurement systems able to reach sensing and identification performance comparable with analytical ones. In such a context several efforts must be spent of course in the development of the sensing material, but also in the choice of the transducer mechanism and its structure, in the electrical characterization of the performance and in the design of suitable measurement setups. This call for papers invites researchers worldwide to report about their novel results on the most recent advances and overview in design and measurements for applications in gas sensors, along with their relevant features and technological aspects. Original research papers are welcome (but not limited) on all aspects that focus on the most recent advances in: (i) basic principles and modeling of gas and VOCs sensors; (ii) new gas sensor principles and technologies; (iii) Characterization and measurements methodologies; (iv) transduction and sampling systems; (vi) package optimization; (vi) gas sensor based systems and applications.

Development of CMOS-MEMS/NEMS Devices

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ISBN: 9783039210688 9783039210695 Year: Pages: 165 DOI: 10.3390/books978-3-03921-069-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:07
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Micro and nano-electro-mechanical system (M/NEMS) devices constitute key technological building blocks to enable increased additional functionalities within Integrated Circuits (ICs) in the More-Than-Moore era, as described in the International Technology Roadmap for Semiconductors. The CMOS ICs and M/NEMS dies can be combined in the same package (SiP), or integrated within a single chip (SoC). In the SoC approach the M/NEMS devices are monolithically integrated together with CMOS circuitry allowing the development of compact and low-cost CMOS-M/NEMS devices for multiple applications (physical sensors, chemical sensors, biosensors, actuators, energy actuators, filters, mechanical relays, and others). On-chip CMOS electronics integration can overcome limitations related to the extremely low-level signals in sub-micrometer and nanometer scale electromechanical transducers enabling novel breakthrough applications. This Special Issue aims to gather high quality research contributions dealing with MEMS and NEMS devices monolithically integrated with CMOS, independently of the final application and fabrication approach adopted (MEMS-first, interleaved MEMS, MEMS-last or others).]

MEMS/NEMS Sensors: Fabrication and Application

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ISBN: 9783039216345 9783039216352 Year: Pages: 242 DOI: 10.3390/books978-3-03921-635-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 16:10:12
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Due to the ever-expanding applications of micro/nano-electromechanical systems (NEMS/MEMS) as sensors and actuators, interest in their development has rapidly expanded over the past decade. Encompassing various excitation and readout schemes, the MEMS/NEMS devices transduce physical parameter changes, such as temperature, mass or stress, caused by changes in desired measurands, to electrical signals that can be further processed. Some common examples of NEMS/MEMS sensors include pressure sensors, accelerometers, magnetic field sensors, microphones, radiation sensors, and particulate matter sensors. Despite a long history of development, fabrication of novel MEMS/NEMS devices still poses unique challenges due to their requirement for a suspended geometry; and many new fabrication techniques have been proposed to overcome these challenges. However, further development of these techniques is still necessary, as newer materials such as compound semiconductors, and 2-dimensional materials are finding their way in various MEMS/NEMS applications, with more complex structures and potentially smaller dimensions.

Keywords

thermoelectric power sensor --- wideband --- GaAs MMIC --- MEMS --- floating slug --- back cavity --- microwave measurement --- MEMS --- high temperature pressure sensors --- AlGaN/GaN circular HFETs --- GaN diaphragm --- adaptive control --- backstepping approach --- tracking performance --- microgyroscope --- resonant frequency --- resistance parameter --- micro fluidic --- oil detection --- MEMS --- microactuator --- magnetic --- micro-NIR spectrometer --- scanning grating mirror --- deflection position detector --- dual-mass MEMS gyroscope --- frequency tuning --- frequency split --- quadrature modulation signal --- frequency mismatch --- suspended micro hotplate --- single-layer SiO2 --- temperature uniformity --- power consumption --- infrared image --- MEMS (micro-electro-mechanical system) --- inertial switch --- acceleration switch --- threshold accuracy --- squeeze-film damping --- photonic crystal cavity --- photonic crystal nanobeam cavity --- optical sensor --- refractive index sensor --- nanoparticle sensor --- optomechanical sensor --- temperature sensor --- Accelerometer readout --- low noise --- low zero-g offset --- microfluidic --- femtosecond laser --- rapid fabrication --- glass welding --- bonding strength --- accelerometer design --- spring design --- analytical model --- gas sensor --- micropellistor --- microdroplet --- pulse inertia force --- methane --- tetramethylammonium hydroxide (TMAH) --- wet etching --- silicon --- 3D simulation --- level-set method --- single crystal silicon --- anisotropy --- vibrating ring gyroscope --- frequency split --- accelerometer --- tunnel magnetoresistive effect --- electrostatic force feedback --- n/a

Sensors in Agriculture

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ISBN: 9783038974123 9783038974130 Year: Pages: 346 DOI: 10.3390/books978-3-03897-413-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Sensors in Agriculture

Author:
ISBN: 9783038977445 9783038977452 Year: Pages: 354 DOI: 10.3390/books978-3-03897-745-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

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2019 (5)