Relevant bibliographies by topics / Sensor parameters

Academic literature on the topic 'Sensor parameters'

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Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Sensor parameters"

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Nistor, P., and I. Orha. "Environmental Parameters Monitoring System." Carpathian Journal of Electronic and Computer Engineering 14, no. 2 (December 1, 2021): 6–10. http://dx.doi.org/10.2478/cjece-2021-0007.

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Abstract The project presents the development of a system for monitoring environmental parameters. At the base of this system is the ESP-32S board that collects, processes and transmits data from the three sensors to the two web interfaces. The role of these web interfaces is to display the data collected from the sensors. The local web interface consists of two windows, the first window contains the table of sensors that displays the data measured by the sensors at that time. In the second window you can see the data measured by the sensors through graphs. They store the sensor data, giving the user the ability to view previously measured data. The local web interface provides sensor data only in the Wi-Fi network coverage area, and its data is deleted when the server is closed. The global web interface displays data using graphs. At the base of this web interface is the ThingSpeak platform that allows the system to transmit data anywhere in the world, store data in the Cloud space and the possibility of using special analysis functions.
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Wang, Wei, Li, Du, and Zhang. "Optical Parameters Optimization for All-Time Star Sensor." Sensors 19, no. 13 (July 4, 2019): 2960. http://dx.doi.org/10.3390/s19132960.

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As an important development direction of star sensor technology, the All-Time star sensor technology can expand the application of star sensors to flight platforms inside the atmosphere. Due to intense atmospheric background radiation during the daytime, the commonly used star sensors operating in the visible wavelength range are significantly limited in their ability to detect stars, and hence the All-Time star sensor technology which is based on the shortwave infrared (SWIR) imaging system has become an effective research direction. All-Time star sensor detection capability is significantly affected by observation conditions and, therefore, an optimized selection of optical parameters, which mainly includes the field of view (FOV) and the detection wavelength band, can effectively improve the detection performance of All-Time star sensors under harsh observation conditions. This paper uses the model simulation method to analyze and optimize the optical parameters under various observation conditions in a high-altitude environment. A main parameter among those discussed is the analysis of detection band optimization based on the SWIR band. Due to the huge cost constraints of high-altitude experiments, we conducted experiments near the ground to verify the effectiveness of the detection band selection and the correctness of the SWIR star sensor detection model, which thereby proved that the optimization of the optical parameters for high altitudes was effective and could be used as a reference.
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Alexandr, Penin, and Sidorenko Anatolie. "NORMALIZED PARAMETERS OF A MAGNETORESISTIVE SENSOR IN BRIDGE CIRCUITS." Moldavian Journal of the Physical Sciences 20, no. 1 (July 2021): 94–104. http://dx.doi.org/10.53081/mjps.2021.20-1.08.

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Magnetoresistive sensors are considered as part of bridge circuits for measuring magnetic field strength and electric current value. Normalized or relative expressions are introduced to change the resistance of the sensor and the measured bridge voltage to increase the information content of the regime to provide the possibility of comparing the regimes of different sensors. To justify these expressions, a geometric interpretation of the bridge regimes, which leads to hyperbolic straight line geometry and a cross ratio of four points, is given. Upon a change in the sensor resistance, the bridge regime is quantified by the value of the cross ratio of four samples (three characteristic values and the current or real value) of voltage and resistance. The cross ratio, as a dimensionless value, is taken as a normalized expression for the bridge voltage and sensor resistance. Moreover, the cross ratio value is an invariant for voltage and resistance. The proposed approach considers linear and nonlinear dependences of measured voltage on sensor resistance from general positions.
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Singh, Ravinder, and Kuldeep Singh Nagla. "Comparative analysis of range sensors for the robust autonomous navigation – a review." Sensor Review 40, no. 1 (October 29, 2019): 17–41. http://dx.doi.org/10.1108/sr-01-2019-0029.

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Purpose The purpose of this research is to provide the necessarily and resourceful information regarding range sensors to select the best fit sensor for robust autonomous navigation. Autonomous navigation is an emerging segment in the field of mobile robot in which the mobile robot navigates in the environment with high level of autonomy by lacking human interactions. Sensor-based perception is a prevailing aspect in the autonomous navigation of mobile robot along with localization and path planning. Various range sensors are used to get the efficient perception of the environment, but selecting the best-fit sensor to solve the navigation problem is still a vital assignment. Design/methodology/approach Autonomous navigation relies on the sensory information of various sensors, and each sensor relies on various operational parameters/characteristic for the reliable functioning. A simple strategy shown in this proposed study to select the best-fit sensor based on various parameters such as environment, 2 D/3D navigation, accuracy, speed, environmental conditions, etc. for the reliable autonomous navigation of a mobile robot. Findings This paper provides a comparative analysis for the diverse range sensors used in mobile robotics with respect to various aspects such as accuracy, computational load, 2D/3D navigation, environmental conditions, etc. to opt the best-fit sensors for achieving robust navigation of autonomous mobile robot. Originality/value This paper provides a straightforward platform for the researchers to select the best range sensor for the diverse robotics application.
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Vasiljevic, Dragana, Cedo Zlebic, Goran Stojanovic, Mitar Simic, Libu Manjakkal, and Zoran Stamenkovic. "Cost-effective sensors and sensor nodes for monitoring environmental parameters." Facta universitatis - series: Electronics and Energetics 31, no. 1 (2018): 11–23. http://dx.doi.org/10.2298/fuee1801011v.

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This paper reviews the design and characterization of humidity and pH sensors manufactured in the printed circuit board (PCB), ink-jet, and screen printing technologies. The first one (PCB technology) provides robust sensors with PET film which can be exposed to harsh environment. The second (ink-jet technology) can manufacture sensors on flexible substrates (foils and papers). The third (screen printing technology) has been used to implement a thick-film sensor. In addition to this, a multi-sensor cloud-based electronic system with autonomous power supply (solar panels) for air and water quality monitoring has been described. Finally, a flexible and modular hardware platform for remote and reliable sensing of environmental parameters has been presented.
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Ibrahim, M., J. Claudel, D. Kourtiche, and M. Nadi. "Geometric parameters optimization of planar interdigitated electrodes for bioimpedance spectroscopy." Journal of Electrical Bioimpedance 4, no. 1 (July 28, 2019): 13–22. http://dx.doi.org/10.5617/jeb.304.

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Abstract This paper is concerned with a physical model of an interdigitated sensor working in a frequency range from 100 Hz to 10 MHz. A theoretical approach is proposed to optimize the use of the sensor for bioimpedance spectroscopy. The correlation between design parameters and frequency behavior in coplanar impedance sensors are described. CoventorWare® software was used to model the biological medium loaded interdigital sensor in three dimensions to measure its electrical impedance. Complete system simulation by a finite element method (FEM) was used for sensor sensitivity optimization. The influence of geometrical parameters (number of fingers, width of the electrodes) on the impedance spectroscopy of the biological medium was studied. The simulation results are in agreement with the theoretical equations of optimization. Thus, it is possible to design a priori such sensor by taking into account the biological medium of interest that will load the sensor.
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Loose, Harald, and Katja Orlowski. "Model Based Determination of Gait Parameters Using IMU Sensor Data." Solid State Phenomena 251 (July 2016): 61–67. http://dx.doi.org/10.4028/www.scientific.net/ssp.251.61.

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The paper deals with the determination of gait parameters using inertial measurement units (IMU). An IMU sensor incorporates three microelectromechanical sensors - triple-axis gyroscope, accelerometer and magnetometer. A standard experimental setup for the observation of the locomotion system using seven Xsens MTw sensors was developed. They are applied to the lower limbs and the pelvis of the subject. The synchronization of data from all sensor components (gyroscope, accelerometer and magnetometer) as well as the onboard estimation of the orientation is provided by the Xsens and Adwinda hard-and software. The strapped down data are received with a rate of 60 Hz. The output data of a single IMU sensor allow motion analysis of the sensor unit itself as well as the motion of the limb where the sensor is mounted to. Stable and reliable algorithms processing the gait data and calculating gait features of a single sensor are developed and evaluated. These algorithms are based on precise determination of each gait cycle. In the middle of stance phase the foot is not moving. It stands on the floor and, following, the initial conditions for the calculation of foot velocities and distances by integration are predetermined. Various features of the gait cycle as well as e.g. dependencies in between features or on the gait velocities are investigated. The application of seven sensors to the limbs of the locomotion system provides measurements of their 3D motion observed in an inertial coordinate system. The limbs are parts of skeleton and interconnected by joints. Introducing a skeleton model, the quality of measurements is evaluated and improved. Joint angles, symmetry ratios and other gait parameters are determined. These results can be used for analysis of the gait of any subject as well as of any cohort.
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Li, Cunli, Cuiling Jiang, Guangwei Zhu, Wei Zou, Mengyuan Zhu, Hai Xu, Pengcheng Shi, and Wenyi Da. "Estimation of Water Quality Parameters with High-Frequency Sensors Data in a Large and Deep Reservoir." Water 12, no. 9 (September 21, 2020): 2632. http://dx.doi.org/10.3390/w12092632.

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High-frequency sensors can monitor water quality with high temporal resolution and without environmental influence. However, sensors for detecting key water quality parameters, such as total nitrogen(TN), total phosphorus(TP), and other water environmental parameters, are either not yet available or have attracted limited usage. By using a large number of high-frequency sensor and manual monitoring data, this study establishes regression equations that measure high-frequency sensor and key water quality parameters through multiple regression analysis. Results show that a high-frequency sensor can quickly and accurately estimate dynamic key water quality parameters by evaluating seven water quality parameters. An evaluation of the flux of four chemical parameters further proves that the multi-parameter sensor can efficiently estimate the key water quality parameters. However, due to the different optical properties and ecological bases of these parameters, the high-frequency sensor shows a better prediction performance for chemical parameters than for physical and biological parameters. Nevertheless, these results indicate that combining high-frequency sensor monitoring with regression equations can provide real-time and accurate water quality information that can meet the needs in water environment management and realize early warning functions.
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FIEDKIEWICZ, Łukasz, and Ireneusz PIELECHA. "Selection of ion sensor operating parameters in quasi-static conditions." Combustion Engines 179, no. 4 (October 1, 2019): 254–58. http://dx.doi.org/10.19206/ce-2019-442.

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Evaluating combustion quality using sensors that allow continuous assessment of the process is one of the modern methods of engine sensory diagnostics. The proper calibration of such systems is a task that requires many studies to determine the conditions and quantities affecting the process. The analysis of significance of quantities related to the ionization signal was carried out in the article. The magnitude of the voltage generating the electric field, the type of spark plug used, the distance of the spark plug electrodes and the dynamic factor – spark plug operating temperature – were all tested. The tests were carried out using a CNG burner (with an excess air ratio of lambda = 1) and four spark plugs. As a result of the ionization signal research, the following relationships were obtained: regarding the impact of the sensor position on the amount of generated voltage (the smaller the distance the greater the value of the signal), the effect of temperature on the sensor resistance (non-linear relationship: increase in temperature decreases resistance, with R2 = 0.9997) effect of system voltage on the ionization signal (linear relationship: voltage increase increases the ionization current signal with a determination coefficient of R2 = 0.9803). In addition, it was found that using an iridium electrode candle had the best effects on the ionization current, regardless of the electrode’s geometrical parameters.
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Jeon, Taehyeong, Proloy Taran Das, Mijin Kim, Changyeop Jeon, Byeonghwa Lim, Ivan Soldatov, and CheolGi Kim. "Operational Parameters for Sub-Nano Tesla Field Resolution of PHMR Sensors in Harsh Environments." Sensors 21, no. 20 (October 18, 2021): 6891. http://dx.doi.org/10.3390/s21206891.

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The resolution of planar-Hall magnetoresistive (PHMR) sensors was investigated in the frequency range from 0.5 Hz to 200 Hz in terms of its sensitivity, average noise level, and detectivity. Analysis of the sensor sensitivity and voltage noise response was performed by varying operational parameters such as sensor geometrical architectures, sensor configurations, sensing currents, and temperature. All the measurements of PHMR sensors were carried out under both constant current (CC) and constant voltage (CV) modes. In the present study, Barkhausen noise was revealed in 1/f noise component and found less significant in the PHMR sensor configuration. Under measured noise spectral density at optimized conditions, the best magnetic field detectivity was achieved better than 550 pT/√Hz at 100 Hz and close to 1.1 nT/√Hz at 10 Hz for a tri-layer multi-ring PHMR sensor in an unshielded environment. Furthermore, the promising feasibility and possible routes for further improvement of the sensor resolution are discussed.
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Dissertations / Theses on the topic "Sensor parameters"

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Shaun, Ferdous Jahan. "Multi-Parameters Miniature Sensor for Water Network Management." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1138/document.

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L’eau est une ressource vitale, indispensable à la vie sur terre. A l’instar de nombreuses autres ressources naturelles, l’eau propre à la consommation est soumise à une forte pression à cause de l’impact de l’activité humaine d’une part et de l’augmentation continue de la population mondiale d’autre part. Une pression tellement forte que l’eau propre représente l’un des 17 objectifs de développement durable des Nations Unies. Dans ce contexte, une gestion rationnelle et durable de la ressource s’avère indispensable. Dans ce but, un système intelligent de supervision des réseaux d’eau potable peut s’avérer très utile. Les systèmes existant sont toutefois peu intégrés et compacts, nécessitent souvent une alimentation externe, et restent relativement chers pour un déploiement massif sur les réseaux. La présente thèse s’inscrit dans le cadre d’un projet de recherche européen, PROTEUS, visant à pallier ces différents problèmes en mettant au point un système de mesure pour la supervision de la ressource en eau permettant la mesure de 9 paramètres physico-chimiques, reconfigurable, et énergétiquement autonome. La contribution de la présente thèse à ce projet porte sur la conception et l’optimisation des différents capteurs physiques (conductivité électrique, pression, température et débit) ainsi qu’à leur co-intégration sur une même puce. Le système proposé montre des performances au moins égales à celle de l’état de l’art en ce qui concerne la robustesse, assurée par la redondance de nombreux éléments sensibles, le domaine de sensibilité et la consommation énergétique. Le présent manuscrit est par conséquent construit comme suit : le premier chapitre est une introduction générale à la supervision de grandeurs environnementales et à la puce multi-capteurs. Le second chapitre décrit la structure de la puce multi-capteurs ainsi que les méthodes de fabrication utilisées, avec une attention particulière accordée aux capteurs de pression et de conductivité électrique. Le troisième chapitre porte sur l’utilisation de résistances électriques pour la mesure de diverses grandeurs physiques, notamment la température. Le dernier chapitre s’attarde plus particulièrement sur l’utilisation de ce type de résistances pour la mesure de débit avant de conclure et de proposer des perspectives pour des travaux futurs
Water is a vital element for every living being on the earth. Like many other dwindling natural resources, clean water faces a strong pressure because of human activity and the rapid growth of global population. The situation is so critical that clean water has been identified as one of the seventeenth sustainable development goals of the United Nations. Under these conditions, a sustainable management of water resources is necessary. For this purpose, a smart solution for water networks monitoring can be very helpful. However, commercially available solutions lack compactness, self-powering capabilities cost competitiveness, necessary to enable the large rollout over water networks. The present thesis takes place in the framework of a European research project, PROTEUS, which addresses these different problems by designing and fabricating a multi-parameter sensor chip (MPSC) for water resources monitoring. The MPSC enables the measurement of 9 physical and chemical parameters, is reconfigurable and self-powered. The present thesis addresses more precisely physical sensors, their design, optimization and co-integration on the MPSC. The developed device exhibits state of the art or larger performances with regard to its redundancy, turn-down ratio and power consumption. The present manuscript is split into two main parts: Part-I and Part-II. Part-I deals with non-thermal aspects of the MPSC, the pressure and conductivity sensor for instance, as well as the fabrication process of the whole device (Chapter 1 and 2). The background of environmental monitoring is presented in Chapter 1 along with the State of Art review. Chapter 2 describes fabrication methods of the MPSC. Preliminary characterization results of non-thermal sensors are also reported in this chapter. Chapter 3 and 4, included in Part-II, deal with thermal sensors (temperature and flow-rate). Chapter 3 describes the many possible uses of electric resistances for sensing applications. Finally, in chapter four, we focus on flowrate sensors before concluding and making a few suggestions for future works
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Bergmark, Giesler Linn. "Investigating construction and design parameters of an embroidered resistive pressure sensor." Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-26450.

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Electronic textiles, or smart textiles, is a field that is growing due to the opportunities it provides. Textile integrated electronics enables soft, flexible, lightweight electronic devices that enable long term monitoring within the medical field. Pressure sensors is one device within this field that has been researched. A textile integrated pressure sensor enables monitoring of heart rate, muscle activity, posture, gait phases and finger movements. In this project a resistive pressure sensor has been produced using embroidery with the purpose of investigating how construction and design parameters influence the resistance-pressure relationship. The study consisted in different phases where in Phase I parameters such as fabric substrate, stitch length and yarn type was examined. Phase II investigated design parameters like electrode pattern design, sensor shape, trace distance and size. In the design phase a new electrode pattern and sensor shape was tested. Finally in Phase III a sensor matix and sensor chain was constructed in order to evaluate the possibility of obtaining touch location. The findings in this study showed that the shape, size and yarn type had the most distinct influence on the sensor performance in regards to the resistance-pressure relationship. In an additional recovery test the results indicated that both textile substrate and stitch length could influence the ability to recover to its original shape after applying cyclic pressure. It was also found that the new pattern design performed equally to the conventional pattern designs and at the same time reduced material consumption as well as the embroidery time. The sensor matrix and sensor chain could display a change in resistance when applying a weight at each sensing element, implying that touch location could be detected, but would need further development in construction before potential implementation.
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Statz, C., J. Küttner, D. Plettemeier, and Thomas Herlitzius. "SEBIMO - Microwave-based Measurement of Soil Parameters." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-229895.

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Kailayanathan, Subaharan, and Saji Kamdod. "Development of Generic Communication Middleware for Embedded Sensor Systems Transmitting Health Parameters." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-49017.

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Health technology or e-Health is one of the most rapidly growing areas in healthcare today and it has been an important requirement as a new concept of healthcare industry. Since global society has been changed to aging society and the healthcare cost has been increasing in the 21st century since 2007. As the total number of people aged 65 or older is expected to increase from 12% to 22% in 2050 which is double the rate, and at the same time there is a decrease in in-fertility rates and increase in life expectancy due to the increase in life quality, there is a need to investigate the needs and requirements of an intelligent embedded sensor systems in health applications, and to develop a new communication protocol or set of protocols that can be used to send data collected from a hub within a house, home-care or a complex and send it securely and reliably to a central database where the gathered data can be monitored by a medical professional to make decisions for further interventions. The employed communication protocol should also be able to securely transmit confidential parameters from the hospital network to a central server outside of the hospital network. The final protocol must be inline with the regulations of the EU. This thesis is done in collaboration with Tjeders AB, Stille AB, and Embedded Sensor Systems for Health Plus (ESS-H+) research profile at Mälardalen University. In this thesis, different communication protocols such as IPSec and TLS and algorithms such as AES and RSA are examined and based on the requirements provided by the companies certain of these protocols and algorithms will be used in the final implementation. Different performance metrics such as overhead, round trip delay and throughput will be measured for the chosen communication protocols and recommendations will be given on which of the protocols and algorithms needs to be used to obtain an optimized, secure and reliable network.
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Chaudhari, Qasim Mahmood. "Estimation of clock parameters and performance benchmarks for synchronization in wireless sensor networks." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2945.

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OKUMA, Shigeru, Tatsuya SUZUKI, Takashi MUTOU, and Eiji KONAKA. "Optimal Design of Sensor Parameters in PLC-Based Control System Using Mixed Integer Programming." Institute of Electronics, Information and Communication Engineers, 2005. http://hdl.handle.net/2237/14990.

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Cao, Huiyi. "Remote Gait Monitoring Mobile System Enabled by Wearable Sensor Technology." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1587042096284549.

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Bäcklund, Tomas. "Development and validation of a system for clinical assessment of gait cycle parameter in patients with idiopathic normal pressure hydocephalus." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-82891.

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A number of parameters have been identified as characteristic of the walking pattern in patients with INPH. Most of these have been identified through qualitative surveys and manually conducted test batteries. In order to obtain quantitative, standardized and objective measures, which enable studies based on larger patient populations and comparable results, there is a need for a user-friendly system that can measure specific key parameters over time in a reliable manner in everyday clinical work. Step height, width and the variability in the gait cycle are such parameters which are interesting research areas for this group of patient. Problems with balance and gait are very common in other patient groups as well, particularly in neurological diseases such as Parkinson's disease, multiple sclerosis and stroke. This is the reason that the development of this gait analyzer is performed. Giving access to a simple and objective method for estimating gait and balance ability in clinical routine investigations would increase the ability to provide the right kind of treatment, confirm treatment results, and conducting larger research studies. Therefore, this equipment can contribute to the assessment of diseases which contain impaired gait. As a first test of the usability and for the validation of accuracy and repeatability of the equipment a group of healthy volunteers was used. Results from tests on healthy subjects show god repeatability between measurements, for step width at normal gait the difference was -0,2 ±0,34 cm (mean, ±SD) and step height 0,69 ±3,34 cm. The stride time variability in the healthy group where very small 0,00048 ±0,00028 s2 with a difference between test of 0,000019 ±0,00038 s2. Three pilot patients have been tested where we have clearly seen indications of increased stride time variability and reduced step height.
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Atalay, Ozgur. "Development and investigation of weft knitted strain sensor." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/development-and-investigation-of-weft-knitted-strain-sensor(54fffacb-d1d7-4e9e-9d8f-7f33d4b90d66).html.

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This thesis presents a study of the sensing properties exhibited by textile-based knitted strain sensors. Sensing fabrics were manufactured from silver-plated conductive nylon and non-conducting elastomeric yarns. The component yarns offered similar diameters, bending characteristics and surface friction, but their production parameters differed in respect of the yarn input tension, the number of conductive courses in the sensing structure and the elastomeric yarn extension characteristics. The knitted sensors were manufactured using flat-bed knitting technology, and electro-mechanical tests were performed on the specimens using a tensile testing machine to apply strain whilst the sensor was incorporated into a Wheatstone bridge arrangement to allow electrical monitoring. The novel operational principle relies on the separation under strain of adjacent conducting knitted loops which are normally held in contact by the elastomeric yarn. The results confirm that production parameters play a fundamental role in determining the physical behaviour and the sensing properties of knitted sensors and the response could be engineered by varying the production parameters of specific designs. Results showed that the knitted structures could be manipulated to produce gauge factor values between 2.26 and 0.23 for sensors with working ranges of 8.4 % and 3.3 % respectively when the elastomeric yarn had 8 cN input tension. The generated signals were stable and repeatable, and under cyclic testing proved to be substantially free from long-term drift. A textile-based strain sensor was developed to create a respiration belt; this was realised by bringing together the extensible knitted sensor and a relatively inelastic textile strap. Machine simulations and real time measurements on a human subject were performed to calculate average breathing frequencies under different static and dynamic conditions. Various respiration rates were monitored to simulate different medical conditions and with the belt located either round the torso or in the abdominal area, the sensor yielded a satisfactory response. However, body motion artefacts affected the signal quality under dynamic conditions and an additional signal-processing step was added to separate unwanted interference from the breathing signal. Electro-mechanical modelling was developed by exploiting Peirce`s loop model in order to describe the fabric geometry under static and dynamic conditions. Kirchhoff`s node and loop equations were employed to create a generalised solution for the equivalent electrical resistance of the textile sensor for a given knitted loop geometry and for a specified number of loops. Experimental results were obtained from the sensor for strain levels up to 40% and these correlate well with the modelled data; a maximum error of 2.13 % was found between the experimental and modelled resistance-strain relationships.
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Li, Zeyuan. "Target localization using RSS measurements in wireless sensor networks." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31356.

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The subject of this thesis is the development of localization algorithms for target localization in wireless sensor networks using received signal strength (RSS) measurements or Quantized RSS (QRSS) measurements. In chapter 3 of the thesis, target localization using RSS measurements is investigated. Many existing works on RSS localization assumes that the shadowing components are uncorrelated. However, here, shadowing is assumed to be spatially correlated. It can be shown that localization accuracy can be improved with the consideration of correlation between pairs of RSS measurements. By linearizing the corresponding Maximum Likelihood (ML) objective function, a weighted least squares (WLS) algorithm is formulated to obtain the target location. An iterative technique based on Newtons method is utilized to give a solution. Numerical simulations show that the proposed algorithms achieves better performance than existing algorithms with reasonable complexity. In chapter 4, target localization with an unknown path loss model parameter is investigated. Most published work estimates location and these parameters jointly using iterative methods with a good initialization of path loss exponent (PLE). To avoid finding an initialization, a global optimization algorithm, particle swarm optimization (PSO) is employed to optimize the ML objective function. By combining PSO with a consensus algorithm, the centralized estimation problem is extended to a distributed version so that can be implemented in distributed WSN. Although suboptimal, the distributed approach is very suitable for implementation in real sensor networks, as it is scalable, robust against changing of network topology and requires only local communication. Numerical simulations show that the accuracy of centralized PSO can attain the Cramer Rao Lower Bound (CRLB). Also, as expected, there is some degradation in performance of the distributed PSO with respect to the centralized PSO. In chapter 5, a distributed gradient algorithm for RSS based target localization using only quantized data is proposed. The ML of the Quantized RSS is derived and PSO is used to provide an initial estimate for the gradient algorithm. A practical quantization threshold designer is presented for RSS data. To derive a distributed algorithm using only the quantized signal, the local estimate at each node is also quantized. The RSS measurements and the local estimate at each sensor node are quantized in different ways. By using a quantization elimination scheme, a quantized distributed gradient method is proposed. In the distributed algorithm, the quantization noise in the local estimate is gradually eliminated with each iteration. Simulations show that the performance of the centralized algorithm can reach the CRLB. The proposed distributed algorithm using a small number of bits can achieve the performance of the distributed gradient algorithm using unquantized data.
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Books on the topic "Sensor parameters"

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Tatnall, Christopher Rhoads. An investigation of candidate sensor-observable wake vortex strength parameters for the NASA Aircraft Vortex Spacing System (AVOSS). Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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Patan, Maciej. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Patan, Maciej. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28230-0.

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M, Chaudhari Qasim, ed. Synchronization in wireless sensor networks: Parameter estimation, performance benchmarks, and protocols. Cambridge: Cambridge University Press, 2009.

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Jai, A. El. Sensors and controls in the analysis of distributed systems. Chichester, England: E. Horwood, 1988.

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Reina, Gerard J. AUV dive control system development including sensor bias compensation and parameter estimation. Monterey, Calif: Naval Postgraduate School, 1988.

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Sallinen, Mikko. Modelling and estimation of spatial relationships in sensor-based robot workcells. Espoo [Finland]: VTT Technical Research Centre of Finland, 2003.

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Lehrasab, Nadeem. A generic fault detection and isolation approach for single-throw mechanical equipment. Birmingham: University of Birmingham, 1999.

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Pazmany, Andrew L. Millimeter-wave radar field measurements and inversion of cloud parameters for the 1999 Mt. Washington Icing Sensors Project: [final report]. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2001.

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Dreeling, Niamh. Optimisation of formulation and processing parameters for low-fat comminuted beef products with particular emphasis on sensory and instrumental texture assessment. Dublin: University College Dublin, 1998.

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Book chapters on the topic "Sensor parameters"

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Tabib-Azar, M. "Sensor Parameters." In Sensors, 17–43. Weinheim, Germany: Wiley-VCH Verlag GmbH, 2008. http://dx.doi.org/10.1002/9783527620128.ch2.

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de Silva, Clarence W. "Performance Specification and Rating Parameters." In Sensor Systems, 195–235. Boca Raton : Taylor & Francis, CRC Press, 2017.: CRC Press, 2016. http://dx.doi.org/10.1201/9781315371160-5.

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Vora, Aditya M. "Theoretical Investigation of Superconducting State Parameters of Bulk Metallic Glasses." In Advanced Sensor and Detection Materials, 413–38. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118774038.ch12.

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Cuevas-Martinez, J. C., J. Canada-Bago, J. A. Fernández-Prieto, and M. A. Gadeo-Martos. "Propagation of Agent Performance Parameters in Wireless Sensor Networks." In Advances in Intelligent and Soft Computing, 213–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19917-2_26.

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Chen, Ding-Horng, Rong-Show Shen, Tsai-Rong Chang, Pei-Shan Lin, and Tzu-Ying Wang. "The Sensor Calibration and Growth Parameters Monitoring for Phalaenopsis Cultivation." In Advances in Intelligent Systems and Computing, 793–802. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15035-8_77.

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Chu, Hung-Chi, Fang-Lin Chao, and Wei-Tsung Siao. "Parameters with Eco-performance of Solar Powered Wireless Sensor Network." In Design for Innovative Value Towards a Sustainable Society, 154–59. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3010-6_31.

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Dub, Martin, and Vojtěch Dynybyl. "Sensor for In-time Identification of Deep Core Drilling Parameters." In Current Methods of Construction Design, 243–49. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33146-7_28.

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Szczęsna, Agnieszka, Adrian Nowak, Piotr Grabiec, Piotr Rozentryt, and Marzena Wojciechowska. "Wearable Sensor Vest Design Study for Vital Parameters Measurement System." In Innovations in Biomedical Engineering, 330–37. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47154-9_38.

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Masoum, Alireza, Nirvana Meratnia, Arta Dilo, Zahra Taghikhaki, and Paul J. M. Havinga. "Cross-Layer Analyses of QoS Parameters in Wireless Sensor Networks." In Communications in Computer and Information Science, 595–605. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17878-8_60.

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Eradus, W. J. "Battery-Less Sensors for Continuous Measurement of Physiological Parameters of Animals." In Sensor Technology in the Netherlands: State of the Art, 317–19. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5010-1_51.

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Conference papers on the topic "Sensor parameters"

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Liao, Yuanfang, Xinguo Wei, Jian Li, and Gangyi Wang. "Parameters optimization of image sensor for star sensors." In 2017 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2017. http://dx.doi.org/10.1109/ist.2017.8261518.

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AJIBOYE, Aye Taiwo, Jaye Femi OPADIJI, and Adebimpe Ruth AJAYI. "GRAPHICAL METHOD FOR DETERMINATION OF MQ-SERIES GAS SENSOR CIRCUIT PARAMETERS FOR A STANDALONE GAS ALARM SYSTEM." In SOUTHERN BRAZILIAN JOURNAL OF CHEMISTRY 2021 INTERNATIONAL VIRTUAL CONFERENCE. DR. D. SCIENTIFIC CONSULTING, 2022. http://dx.doi.org/10.48141/sbjchem.21scon.20_abstract_ajiboye.pdf.

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MQ-series gas sensors belong to the metal oxide semiconductor (MOS) family of sensors that can sense the presence of many gases. These sensors find their application in gas alarm systems as key components. While necessary sensor circuit output voltage value for alarm point in a standalone gas alarm system is desirable, but what exact combination of the sensor circuit parameters is required? Hitherto, the determination of these circuit parameters has not been much attention in the research community. This study explores a structured graphical approach of determining MQ series gas sensor circuit parameters for a standalone gas alarm system that yields the desired sensor circuit output voltage value for the alarm point. Model equations were developed for the sensor dynamics, and based on these model equations, graphs for the determination of required sensor parameters were plotted for a case of MQ-4 gas sensor response to liquefied petroleum gas (LPG). A structured graphical approach for determining MQ-series gas sensor circuit parameters for alarm points in a standalone gas alarm system showed that using MQ-4 gas sensor and LPG as the target gas. For a sensor circuit output voltage of 2 V for alarm point at 1000 ppm of LPG, the corresponding value of RO, RS, and RL obtained were 20 kΩ, 30 kΩ, and 20 kΩ, respectively. Hence, the developed structured graphical approach is suitable for determining MQ series gas sensor circuit parameters for a standalone gas alarm system under the influence of its associated gases.
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Leonovitch, Georgy I., Valery N. Zakharov, and Aleksandr I. Gorshkov. "Engineering of the fiber optic Bragg grating sensor of electrical parameters and software application for automatic simulation of its parameters." In Information Technology and Nanotechnology-2017. IP Zaitsev V.D., 2017. http://dx.doi.org/10.18287/1613-0073-2017-1966-1-4.

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Nowadays one of the most effective transducer rised to the high demands based on metrological and exploitative characteristics are fiber optical. In the article there is modern state of measurement fiber optical sensors. Basic types and methods of measurement are examined. New model of fiber optic Bragg grating sensor for measurement of electric parameters is suggested. For the suggested model a program for computing the parameters of sensor is written, valid model is presented on experimental board. The results of the work and their valuating are received.
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Mahmood, Usman, Adel Al-Jumaily, and Moha'med Al-Jaafreh. "Type-2 Fuzzy Classification of Blood Pressure Parameters." In 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information. IEEE, 2007. http://dx.doi.org/10.1109/issnip.2007.4496910.

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Bol'shakov, Alexander A., Brett A. Cruden, and Surendra P. Sharma. "Sensor for monitoring plasma parameters." In Lasers and Applications in Science and Engineering, edited by Peter R. Herman, Jim Fieret, Alberto Pique, Tatsuo Okada, Friedrich G. Bachmann, Willem Hoving, Kunihiko Washio, et al. SPIE, 2004. http://dx.doi.org/10.1117/12.528991.

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Staszek, Kamil, Jakub Sorocki, Krzysztof Wincza, and Slawomir Gruszczynski. "Six-port reflectometer with tunable parameters ensuring measurement accuracy enhancement." In 2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet). IEEE, 2017. http://dx.doi.org/10.1109/wisnet.2017.7878747.

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Lluna, Eduardo, A. Edith Navarro, Diego Ramírez, and Silvia Casans. "Sensor Network to Measure Electric Parameters." In 2010 Fourth International Conference on Sensor Technologies and Applications (SENSORCOMM). IEEE, 2010. http://dx.doi.org/10.1109/sensorcomm.2010.81.

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Kozlovski, N. Y., M. W. Gallagher, and D. C. Malocha. "SAW sensor correlator system performance parameters." In 2011 Joint Conference of the IEEE International Frequency Control and the European Frequency and Time Forum (FCS). IEEE, 2011. http://dx.doi.org/10.1109/fcs.2011.5977753.

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Zanaj, Elma, Indrit Enesi, and Elda Zenelaj. "Improving Parameters for Wireless Sensor Networks." In 2011 14th International Conference on Network-Based Information Systems (NBiS). IEEE, 2011. http://dx.doi.org/10.1109/nbis.2011.68.

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Karpmski, Mikolaj, Pawel Raif, Stanislaw Rajba, Teresa Rajba, and Vasyl Martsenyuk. "Wireless sensor networks with randomized parameters." In 2016 16th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2016. http://dx.doi.org/10.1109/iccas.2016.7832497.

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Reports on the topic "Sensor parameters"

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Richman, E. E., A. L. Dittmer, and J. M. Keller. Field analysis of occupancy sensor operation: Parameters affecting lighting energy savings. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/10185252.

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Domgmo-Momo, Gilles. Infrared Spectroscope for Electron Bunch-length Measurement: Heat Sensor Parameters Analysis. Office of Scientific and Technical Information (OSTI), September 2012. http://dx.doi.org/10.2172/1050220.

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Gungor, Osman, Imad Al-Qadi, and Navneet Garg. Pavement Data Analytics for Collected Sensor Data. Illinois Center for Transportation, October 2021. http://dx.doi.org/10.36501/0197-9191/21-034.

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The Federal Aviation Administration instrumented four concrete slabs of a taxiway at the John F. Kennedy International Airport to collect pavement responses under aircraft and environmental loading. The study started with developing preprocessing scripts to organize, structure, and clean the collected data. As a result of the preprocessing step, the data became easier and more intuitive for pavement engineers and researchers to transform and process. After the data were cleaned and organized, they were used to develop two prediction models. The first prediction model employs a Bayesian calibration framework to estimate the unknown material parameters of the concrete pavement. Additionally, the posterior distributions resulting from the calibration process served as a sensitivity analysis by reporting the significance of each parameter for temperature distribution. The second prediction model utilized a machine-learning (ML) algorithm to predict pavement responses under aircraft and environmental loadings. The results demonstrated that ML can predict the responses with high accuracy at a low computational cost. This project highlighted the potential of using ML for future pavement design guidelines as more instrumentation data from future projects are collected to incorporate various material properties and pavement structures.
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McMurtrey, Michael, Kunal Mondal, Joseph Bass, Kiyo Fujimoto, and Austin Biaggne. Report on plasma jet printer for sensor fabrication with process parameters optimized by simulation input. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1668670.

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Goldstein, N., J. Lee, S. M. Adler-Golden, and F. Bien. Diode laser-based sensor system for long-path absorption measurements of atmospheric concentration and near-IR molecular spectral parameters. Office of Scientific and Technical Information (OSTI), December 1993. http://dx.doi.org/10.2172/10118156.

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Britt, Sanford, James Martin-Hayden, and Mitchell A. Plummer. An Assessment of Aquifer/Well Flow Dynamics: Identification of Parameters Key to Passive Sampling and Application of Downhole Sensor Technologies. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada621876.

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Miles, Gaines E., Yael Edan, F. Tom Turpin, Avshalom Grinstein, Thomas N. Jordan, Amots Hetzroni, Stephen C. Weller, Marvin M. Schreiber, and Okan K. Ersoy. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570567.bard.

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In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were studied and a relationship was derived. It was found that using a ratio of two wavelenght reflectance images (750nm and 670nm) it was possible to segment the plants from the background. Once ths was accomplished it was then possible to classify the segmented images into weed or crop by use of the neural network. The neural network developed for this work is a modification of the standard learning vector quantization algorithm. This neural network was modified by replacing the time-varying adaptation gain with a constant adaptation gain and a binary reinforcement function. This improved accuracy and training time as well as introducing several new properties such as hill climbing and momentum addition. The network was trained and tested with different wavelength combinations in order to find the best results. Finally, the results of the classifier were evaluated using a pixel based method and a block based method. In the pixel based method every single pixel is evaluated to test whether it was classified correctly or not and the best weed classification results were 81% and its associated crop classification accuracy is 57%. In the block based classification method, the image was divided into blocks and each block was evaluated to determine whether they contained weeds or not. Different block sizes and thesholds were tested. The best results for this method were 97% for a block size of 8 inches and a pixel threshold of 60. A simulation model was developed to 1) quantify the effectiveness of a site-specific sprayer, 2) evaluate influence of diffeent design parameters on efficiency of the site-specific sprayer. In each iteration of this model, infected areas (weed patches) in the field were randomly generated and the amount of required herbicides for spraying these areas were calculated. The effectiveness of the sprayer was estimated for different stain sizes, nozzle types (conic and flat), nozzle sizes and stain detection levels of the identification system. Simulation results indicated that the flat nozzle is much more effective as compared to the conic nozzle and its relative efficiency is greater for small nozzle sizes. By using a site-specific sprayer, the average ratio between the spraying areas and the stain areas is about 1.1 to 1.8 which can save up to 92% of herbicides, especially when the proportion of the stain areas is small.
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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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Searcy, Stephen W., and Kalman Peleg. Adaptive Sorting of Fresh Produce. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568747.bard.

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This project includes two main parts: Development of a “Selective Wavelength Imaging Sensor” and an “Adaptive Classifiery System” for adaptive imaging and sorting of agricultural products respectively. Three different technologies were investigated for building a selectable wavelength imaging sensor: diffraction gratings, tunable filters and linear variable filters. Each technology was analyzed and evaluated as the basis for implementing the adaptive sensor. Acousto optic tunable filters were found to be most suitable for the selective wavelength imaging sensor. Consequently, a selectable wavelength imaging sensor was constructed and tested using the selected technology. The sensor was tested and algorithms for multispectral image acquisition were developed. A high speed inspection system for fresh-market carrots was built and tested. It was shown that a combination of efficient parallel processing of a DSP and a PC based host CPU in conjunction with a hierarchical classification system, yielded an inspection system capable of handling 2 carrots per second with a classification accuracy of more than 90%. The adaptive sorting technique was extensively investigated and conclusively demonstrated to reduce misclassification rates in comparison to conventional non-adaptive sorting. The adaptive classifier algorithm was modeled and reduced to a series of modules that can be added to any existing produce sorting machine. A simulation of the entire process was created in Matlab using a graphical user interface technique to promote the accessibility of the difficult theoretical subjects. Typical Grade classifiers based on k-Nearest Neighbor techniques and linear discriminants were implemented. The sample histogram, estimating the cumulative distribution function (CDF), was chosen as a characterizing feature of prototype populations, whereby the Kolmogorov-Smirnov statistic was employed as a population classifier. Simulations were run on artificial data with two-dimensions, four populations and three classes. A quantitative analysis of the adaptive classifier's dependence on population separation, training set size, and stack length determined optimal values for the different parameters involved. The technique was also applied to a real produce sorting problem, e.g. an automatic machine for sorting dates by machine vision in an Israeli date packinghouse. Extensive simulations were run on actual sorting data of dates collected over a 4 month period. In all cases, the results showed a clear reduction in classification error by using the adaptive technique versus non-adaptive sorting.
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