Relevant bibliographies by topics / Intelligent sensors

Academic literature on the topic 'Intelligent sensors'

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Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Intelligent sensors"

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Fu, Jie, Qiya Gao, and Shuang Li. "Application of Intelligent Medical Sensing Technology." Biosensors 13, no. 8 (August 13, 2023): 812. http://dx.doi.org/10.3390/bios13080812.

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With the popularization of intelligent sensing and the improvement of modern medical technology, intelligent medical sensing technology has emerged as the times require. This technology combines basic disciplines such as physics, mathematics, and materials with modern technologies such as semiconductors, integrated circuits, and artificial intelligence, and has become one of the most promising in the medical field. The core of intelligent medical sensor technology is to make existing medical sensors intelligent, portable, and wearable with full consideration of ergonomics and sensor power consumption issues in order to conform to the current trends in cloud medicine, personalized medicine, and health monitoring. With the development of automation and intelligence in measurement and control systems, it is required that sensors have high accuracy, reliability, and stability, as well as certain data processing capabilities, self-checking, self-calibration, and self-compensation, while traditional medical sensors cannot meet such requirements. In addition, to manufacture high-performance sensors, it is also difficult to improve the material process alone, and it is necessary to combine computer technology with sensor technology to make up for its performance shortcomings. Intelligent medical sensing technology combines medical sensors with microprocessors to produce powerful intelligent medical sensors. Based on the original sensor functions, intelligent medical sensors also have functions such as self-compensation, self-calibration, self-diagnosis, numerical processing, two-way communication, information storage, and digital output. This review focuses on the application of intelligent medical sensing technology in biomedical sensing detection from three aspects: physical sensor, chemical sensor, and biosensor.
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Taymanov, Roald E., and Ksenia Sapozhnikova. "Problems of Terminology in the Field of Intelligent Sensors and Systems." Key Engineering Materials 437 (May 2010): 434–38. http://dx.doi.org/10.4028/www.scientific.net/kem.437.434.

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Terms and definitions in the field of sensors and measuring systems with the elements of artificial intelligence are not well-established. Nowadays, in Russia a draft of state standard “Intelligent Sensors and Intelligent Measuring Systems. Basic Terms and Definitions” is being under development. In accordance with the draft of the standard, the paper deals both with definitions and grounds of a number of terms such as “adaptive sensor”, “metrological self-check of sensors”, “metrological diagnostic check”, “intelligent sensor”, etc.
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Micko, Kristian, Peter Papcun, and Iveta Zolotova. "Review of IoT Sensor Systems Used for Monitoring the Road Infrastructure." Sensors 23, no. 9 (May 4, 2023): 4469. http://dx.doi.org/10.3390/s23094469.

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An intelligent transportation system is one of the fundamental goals of the smart city concept. The Internet of Things (IoT) concept is a basic instrument to digitalize and automatize the process in the intelligent transportation system. Digitalization via the IoT concept enables the automatic collection of data usable for management in the transportation system. The IoT concept includes a system of sensors, actuators, control units and computational distribution among the edge, fog and cloud layers. The study proposes a taxonomy of sensors used for monitoring tasks based on motion detection and object tracking in intelligent transportation system tasks. The sensor’s taxonomy helps to categorize the sensors based on working principles, installation or maintenance methods and other categories. The sensor’s categorization enables us to compare the effectiveness of each sensor’s system. Monitoring tasks are analyzed, categorized, and solved in intelligent transportation systems based on a literature review and focusing on motion detection and object tracking methods. A literature survey of sensor systems used for monitoring tasks in the intelligent transportation system was performed according to sensor and monitoring task categorization. In this review, we analyzed the achieved results to measure, sense, or classify events in intelligent transportation system monitoring tasks. The review conclusions were used to propose an architecture of the universal sensor system for common monitoring tasks based on motion detection and object tracking methods in intelligent transportation tasks. The proposed architecture was built and tested for the first experimental results in the case study scenario. Finally, we propose methods that could significantly improve the results in the following research.
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Vladareanu, Luige. "Advanced Intelligent Control through Versatile Intelligent Portable Platforms." Sensors 20, no. 13 (June 29, 2020): 3644. http://dx.doi.org/10.3390/s20133644.

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Deep research and communicating new trends in the design, control and applications of the real time control of intelligent sensors systems using advanced intelligent control methods and techniques is the main purpose of this research. The innovative multi-sensor fusion techniques, integrated through the Versatile Intelligent Portable (VIP) platforms are developed, combined with computer vision, virtual and augmented reality (VR&AR) and intelligent communication, including remote control, adaptive sensor networks, human-robot (H2R) interaction systems and machine-to-machine (M2M) interfaces. Intelligent decision support systems (IDSS), including remote sensing, and their integration with DSS, GA-based DSS, fuzzy sets DSS, rough sets-based DSS, intelligent agent-assisted DSS, process mining integration into decision support, adaptive DSS, computer vision based DSS, sensory and robotic DSS, are highlighted in the field of advanced intelligent control.
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Jiang, Shali, and Qiong Ren. "Application of Sensors in Intelligent Clothing Design." International Journal of Online Engineering (iJOE) 14, no. 06 (June 22, 2018): 4. http://dx.doi.org/10.3991/ijoe.v14i06.8694.

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<p class="0abstract"><span lang="EN-US">In order to study the application of sensors in intelligent clothing design, the artificially intelligent cutting-edge technology -machine learning method was proposed to combine a variety of signals of non-contact sensors in several different positions. Higher accuracy was achieved, while maintaining the comfort brought by a non-contact sensor. The experimental results showed that the proposed strategy focused on the combination of clothing design technology and artificial intelligence technology. As a result, without changing the sensor materials, it enhances the comfort and precision of clothing, eliminates the comfort reduced by sensor close to the skin, and transforms inaccurate measurement into accurate measurement. </span></p>
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White, Neil. "Intelligent sensors." Sensor Review 17, no. 2 (June 1997): 97–98. http://dx.doi.org/10.1108/02602289710170267.

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Hashikawa, Fumitaka, and Kazuyuki Morioka. "Convenient Position Estimation of Distributed Sensors in Intelligent Spaces Using SLAM for Mobile Robots." Journal of Robotics and Mechatronics 27, no. 2 (April 20, 2015): 191–99. http://dx.doi.org/10.20965/jrm.2015.p0191.

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<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/09.jpg"" width=""200"" />Overview of the proposed method</div> Intelligent space is one in which many networked sensors are distributed. The purpose of intelligent space is to support information for human beings and robots based on the integration of sensor information. Specifically, to support location-based applications in intelligent space, networked sensors must get locations of human beings or robots. To do so, sensor locations and orientations of sensors must be known in world coordinates. To measure numerous sensor locations accurately by hand, this study focuses on estimating the locations and orientations of distributed sensors in intelligent space – but doing so automatically. We propose map sharing using distributed laser range sensors and a mobile robot to estimate the locations of distributed sensors. Comparing maps of sensor and robots, sensor locations are estimated on a global map built by SLAM of a mobile robot. An ICP matching algorithm is used to improve map matching among sensors and robots. Experimental results with actual distributed sensors and a mobile robot show that the proposed system estimates sensor locations satisfactorily and improve the accuracy of a global map built by SLAM. </span>
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Gao, Qiya, Jie Fu, Shuang Li, and Dong Ming. "Applications of Transistor-Based Biochemical Sensors." Biosensors 13, no. 4 (April 11, 2023): 469. http://dx.doi.org/10.3390/bios13040469.

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Transistor-based biochemical sensors feature easy integration with electronic circuits and non-invasive real-time detection. They have been widely used in intelligent wearable devices, electronic skins, and biological analyses and have shown broad application prospects in intelligent medical detection. Field-effect transistor (FET) sensors have high sensitivity, reasonable specificity, rapid response, and portability and provide unique signal amplification during biochemical detection. Organic field-effect transistor (OFET) sensors are lightweight, flexible, foldable, and biocompatible with wearable devices. Organic electrochemical transistor (OECT) sensors convert biological signals in body fluids into electrical signals for artificial intelligence analysis. In addition to biochemical markers in body fluids, electrophysiology indicators such as electrocardiogram (ECG) signals and body temperature can also cause changes in the current or voltage of transistor-based biochemical sensors. When modified with sensitive substances, sensors can detect specific analytes, improve sensitivity, broaden the detection range, and reduce the limit of detection (LoD). In this review, we introduce three kinds of transistor-based biochemical sensors: FET, OFET, and OECT. We also discuss the fabrication processes for transistor sources, drains, and gates. Furthermore, we demonstrated three sensor types for body fluid biomarkers, electrophysiology signals, and development trends. Transistor-based biochemical sensors exhibit excellent potential in multi-mode intelligent analysis and are good candidates for the next generation of intelligent point-of-care testing (iPOCT).
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Nowaková, Jana, and Miroslav Pokorný. "Intelligent Controller Design by the Artificial Intelligence Methods." Sensors 20, no. 16 (August 10, 2020): 4454. http://dx.doi.org/10.3390/s20164454.

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With the rapid growth of sensor networks and the enormous, fast-growing volumes of data collected from these sensors, there is a question relating to the way it will be used, and not only collected and analyzed. The data from these sensors are traditionally used for controlling and influencing the states and processes. Standard controllers are available and successfully implemented. However, with the data-driven era we are facing nowadays, there is an opportunity to use controllers, which can include much information, elusive for common controllers. Our goal is to propose a design of an intelligent controller–a conventional controller, but with a non-conventional method of designing its parameters using approaches of artificial intelligence combining fuzzy and genetics methods. Intelligent adaptation of parameters of the control system is performed using data from the sensors measured in the controlled process. All parts designed are based on non-conventional methods and are verified by simulations. The identification of the system’s parameters is based on parameter optimization by means of its difference equation using genetic algorithms. The continuous monitoring of the quality control process and the design of the controller parameters are conducted using a fuzzy expert system of the Mamdani type, or the Takagi–Sugeno type. The concept of the intelligent control system is open and easily expandable.
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Wu, Guang, and Xuezheng Zhang. "Realization of Wireless Sensors and Intelligent Computer Aided Teaching in Physical Education and Training." Wireless Communications and Mobile Computing 2022 (February 12, 2022): 1–12. http://dx.doi.org/10.1155/2022/6415352.

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Wireless sensors integrate a variety of high-tech, powered by engines to form network nodes, and randomly distributed sensors and data processing units form a network through a certain rule. The wireless sensor can directly transmit the collected digital signal to the computer for analysis and processing. Intelligent computer refers to a computer that can simulate and expand artificial intelligence. It is a dynamically developing concept and always represents the most advanced level of computer development. This article aims to study the role of wireless sensors and intelligent computer-assisted teaching in physical education and training. It is hoped that wireless sensors and intelligent computer technology will assist in physical training. This article briefly summarizes the status quo of the use of wireless sensors, briefly introduces the design and use of various wireless sensors, and briefly explains their differences. This article explains the theoretical basis and principles of use of intelligent computers. Aiming at the shortcomings of traditional multimedia courseware in the teaching process, an application idea is proposed, and a modular design method is adopted to design a computer-assisted teaching system based on integrated ware. The test results of this paper show that 40% of the students were very satisfied with the intelligent PC-assisted educational delivery system in PE lessons, 67% were satisfied with the usage of the intelligent CC-AS in PE lessons and 22% disagreed with the usage of the intelligent CC-AS in PE lessons; 14.2% of the teachers often used the intelligent CC-AS in PE lessons and 30% of teachers occasionally used ICDS in PE lessons and another 12% never used ICDS in PE lessons.
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Dissertations / Theses on the topic "Intelligent sensors"

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Yalcinkaya, Fikret. "Towards biomedical intelligent sensors." Thesis, University of Sussex, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285141.

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Potassium, sodium, and calcium are crucial electrolytes of human blood. Among the functions of the electrolytes are maintenance of osmotic pressure and water distribution in the various body fluid compartments, maintenance of the proper pH, regulation of the proper function of the heart and other muscles, involvement in oxidation-reduction or electron transfer reactions, and participation in catalysis as cofactors for enzymes. Therefore, abnormal levels of electrolytes may be either the cause or the consequence of a variety of disorders, and thus the determination of electrolytes in different body fluids in general and in whole human blood particularly is one of the most important functions of the clinical laboratory . Serum or plasma is the usual specimen employed for assay of potassium, sodium, and calcium but not whole human blood. This research intended to create a sensor-array capable of analysing potassium, sodium, and calcium ion-activity in whole human blood based on miniaturised ion-sensors and zero-current direct potentiometry. This research dealt with sensing-side of the sensor-array hoping for integration of these sensors with microelectronics or discrete parts based electronics in due time. Clinics use single electrodes for K+, Na+, and Ca2+ sensing in body fluids. However, single sensing is costly and in emergency cases time consuming as well. Therefore a portable, battery-operated cost- and time-effective sensor array is needed for multi-sensing of r, Na +, and Ca2 + either in emergency cases in field or for patient near bed-side measurement/monitoring. The approach of this thesis to the problem is as follows: This thesis has five phases, all equally important. The first phase, a theoretical phase, mainly deals with the determination of the technique which fits best with chemical sensors and integration with microelectronics, and the decision among many alternative chemicals, whether natural or man-made, available for multi-sensing realisation, by taking into account all the best efforts devoted to development of chemical-sensors. The second phase is the miniaturisation process of the electrochemical sensor-array, either ion-sensors or reference electrode, as much as possible. The third phase is multi-sensing application of the sensorarray for sensing K+, Na+, and ci+ with binary and mixed electrolytes and with artificial and whole human blood respectively, the fourth phase is the sensor-array response with only millilitre or microlitre volumes of whole human blood and the fifth phase is the integration of a sensor array with discrete, parts based, electronic circuitry. So, as a new application a disposable reference electrode has been realised which reasonably fits with the sensor array for the analysis of potassium, sodium, and calcium in whole human blood. Since all the single sensing of these cations have been realised by using a conventional reference electrode, either silver/silver chloride or calomel electrode, which is a bulky and expensive alternative, this research prepared, tested, and implemented a new disposable reference electrode for the sensor-array based on a poly (vinyl alcohol) matrix incorporating a proper amount of Kel. Having a successfully working miniaturised reference electrode, valinomycin, ETH 157, and ETH 1001 ionophores have been used as the selective materials for potassium, sodium, and calcium in whole human blood, respectively. Multisensing applications have only used solutions as testing medium whereas the work described in this thesis goes one step further and uses artificial and whole human blood with fairly reasonable responses.
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Lundman, Pontus. "Sensors for intelligent and reliable components." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-274922.

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One way to tackle the climate change society is facing today is through the change to renewable energy sources, such as wind power. Today, a trend when it comes to technology is that products are evolving into becoming more cyber-physical systems (CPS) by integrating functions realized with mechanics, control and communication. One challenge for CPS is to find cost-effective and reliable sensor solutions.  The purpose of this project is to lay the foundations for an intelligent CPS with the help of sensors and condition monitoring methods that, with further development, can reduce the downtime of a wind turbine. Thus, the reliability of the wind turbine and the profitability of its investors increase. The aim of the work is to develop an overall concept for a sensor package with analysis methods that enable real-time diagnosis in the gearbox of a wind turbine. This sensor package should be able to monitor the most common problems that arise in the gearbox and it should also be able to be used as a basis for a possible development of a CPS in the future.  The work is based on an information search that enables the creation of a list of requirements. This then forms the basis for concept generation through the use of a function/means tree and concept evaluation through the use of elimination matrix, weight determination matrix and weighted criteria matrix.  The work concludes that there are four main types of failures that occur in the gearbox and that should be monitored. These are scuffing, micropitting, propagation of cracks and bearing failure. The final concept uses vibration analysis for monitoring of micropitting, crack propagation and bearing failure, oil analysis for monitoring of scuffing and micropitting and temperature measurement for monitoring of scuffing and bearing failure. For vibration analysis, piezoelectric sensors are used, for oil analysis electromagnetic sensors and for temperature measurement resistance thermometers are used.  The work finds that it is appropriate in this day and age to use well-established methods for condition monitoring in the gearbox of wind turbines.
Ett sätt att tackla de klimatförändringar samhället står inför idag är genom omställningen till förnybara energikällor, såsom vindkraft. Idag är en trend när det kommer till teknik att produkter utvecklas till att allt mer bli cyberfysiska system (CPS) genom att de integrerar funktioner som realiseras med mekanik, reglering och kommunikation. En utmaning för CPS är att hitta kostnadseffektiva och tillförlitliga sensorlösningar.  Syftet med detta projekt är att lägga grunden till ett intelligent CPS med hjälp av sensorer och tillståndsövervakningsmetoder som med vidare utveckling ska kunna minska stilleståndstiden hos ett vindkraftverk. Således ökar tillförlitligheten hos vindkraftverket samt räntabiliteten för investerarna av dessa. Arbetets mål är att utveckla ett övergripande koncept för ett sensorpaket med analysmetoder som möjliggör realtidsdiagnos i växellådan hos ett vindkraftverk. Detta sensorpaket ska kunna övervaka de vanligaste problemen som uppstår i växellådan och ska kunna användas som grund för eventuell utveckling av ett CPS i framtiden.  Arbetet grundas i en informationssökning som möjliggör skapandet av en kravspecifikation. Denna ligger sedan till grund för konceptgenerering genom användandet av funktions/medelträd samt konceptutvärdering genom användandet av elimineringsmatris, viktbestämningsmatris samt kriterieviktsmetoden.  I arbetet framkommer att det finns fyra huvudsakliga skador som uppkommer i växellådan och som bör övervakas. Dessa är scuffing, mikropitting, sprickpropagering och lagerhaveri. Det slutgiltiga konceptet använder vibrationsanalys för övervakning av mikropitting, sprickpropagering och lagerhaveri, oljeanalys för övervakning av scuffing och mikropitting samt temperaturmätning för övervakning av scuffing och lagerhaveri. Vid vibrationsanalys används piezoelektriska sensorer, vid oljeanalys elektromagnetiska sensorer och för temperaturmätning resistanstermometrar.  Arbetet konstaterar att det i dagsläget är lämpligt att använda väletablerade metoder för tillståndsövervakning i växellådan hos vindkraftverk.
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Padmanaban, Haricharan. "Real time implementation of physical intelligent sensors /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1240704211&sid=8&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Jonsson, Patrik. "Intelligent networked sensors for increased traffic safety." Licentiate thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-14982.

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Our society needs to continuously perform transports of people and goods toensure that business is kept going. Every disturbance in the transportation ofpeople or goods affects the commerce and may result in economical losses forcompanies and society. Severe traffic accidents cause personal tragedies forpeople involved as well as huge costs for the society. Therefore the roadauthorities continuously try to improve the traffic safety. Traffic safety may beimproved by reduced speeds, crash safe cars, tires with better road grip andimproved road maintenance. The environmental effects from roadmaintenance when spreading de-icing chemicals need to be considered, i.e.how much chemicals should be used to maximize traffic safety and minimizethe environmental effects. Knowledge about the current and upcoming roadcondition can improve the road maintenance and hence improve traffic safety.This thesis deals with sensors and models that give information about the roadcondition.The performance and reliability of existing surface mounted sensors wereexamined by laboratory experiments. Further research involved field studies tocollect data used to develop surface status models based on road weather dataand camera images. Field studies have also been performed to find best usageof non intrusive IR technology.The research presented here showed that no single sensor give enoughinformation by itself to safely describe the road condition. However, the resultsindicated that among the traditional road surface mounted sensors only theactive freezing point sensor gave reliable freezing point results. Furtherresearch aimed to find a model that could classify the road condition indifferent road classes from existing road weather sensor data and road images.The result was a model that accurately could distinguish between the roadconditions dry, wet, snowy and icy. These road conditions are clearly dissimilarand are therefore used as the definition of the road classes used in this thesis.Finally, results from research regarding remote sensing IR technology showedthat it significantly improves knowledge of the road temperature and statuscompared to data from surface mounted sensors.
Vårt samhälle bygger på att det finns effektiva transporter av människor ochvaror för att säkerställa att samhällets funktioner fungerar och att företagenkan genomföra sina affärer. Störningar i transporterna av människor och varorpåverkar handeln och kan leda till ekonomiska förluster för både företag ochvårt samhälle. Allvarliga trafikolyckor orsakar personliga tragedier för deinblandade samt stora kostnader för samhället. Det är med denna bakgrundsom vägmyndigheterna kontinuerligt arbetar med att förbättratrafiksäkerheten. Trafiksäkerheten kan förbättras genom att minskahastigheterna, se till att bilarna blir krocksäkra, krav på däck med bättreväggrepp och ett bättre vägunderhåll. Miljöeffekterna från vinterväghållningdär avisningsmedel sprids på vägarna måste beaktas, d.v.s. hur mycketkemikalier bör användas för att maximera trafiksäkerheten och minimeramiljöpåverkan. Denna avhandling handlar om sensorer och modeller som gerinformation om väglaget. En kunskap om aktuellt och kommande väglag kanförbättra väghållningen och därmed öka trafiksäkerheten.I avhandlingen har prestanda och tillförlitlighet hos befintliga vägmonteradesensorer granskats i laboratorieexperiment. Data från fältstudier har använtsför att utveckla modeller som kan ge information om vägytans status baseratpå meteorologiska mätdata och kamerabilder. Det har också genomförtsfältstudier för att utforska den fördelaktigaste användningen av beröringsfriinfraröd sensorteknik.Den forskning som presenteras här visar att ingen enskild givare ger tillräckliginformation för att säkert beskriva väglaget. Från de traditionella ytmonteradesensorerna drogs slutsatsen att den aktiva fryspunktsgivaren gav de mesttillförlitliga fryspunktsresultaten. Det vidare arbetet handlade om att hitta enmodell som skulle kunna klassificera vägförhållanden i olika vägklassergenom att utnyttja information från befintliga sensorer och kamerabilder.Detta arbete resulterade i en modell som tillförlitligt kan särskilja väglagentorr, våt, snöig och isig. Dessa väglag är väsentligt olika och har därför valtssom väglagsklasser i denna avhandling. Under en säsong genomfördes ävenfältförsök med beröringsfri infraröd mätteknik där det visade sig att denberöringsfria teknologin förbättrar kunskapen om vägbanans temperatur och vägbanans status.
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Angelikaki, C. "An intelligent sample changer." Thesis, University of Reading, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234786.

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Bandhil, Pavan. "Physical intelligent sensors for integrated system health management /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1136091891&sid=12&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Oesch, Christopher. "Intelligent sensors with embedded algorithms for ISHM applications /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1240704841&sid=5&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Abbasi, Mohammed Abdul Rahim. "An integrated platform for Physical and Virtual Intelligent Sensors /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1559856921&sid=16&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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De, Mel Geeth R. "Intelligent resource selection for sensor-task assignment : a knowledge-based approach." Thesis, University of Aberdeen, 2014. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=215104.

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Today, sensing resources play a crucial role in the success of critical tasks such as border monitoring and surveillance. Although there are various types of resources available, each with different capabilities, only a subset of these resources are useful for a specific task. This is due to the dynamism in tasks' environment and the heterogeneity of the resources. Thus, an effective mechanism to select resources for tasks is needed so that the selected resources cater for the needs of the tasks. Though a considerable amount of research has already been done in different communities to efficiently allocate resources to tasks, we argue that there is little work done to guarantee the effectiveness of the section with respect to the context of operation. In this thesis, we propose a knowledge-based approach in which the context of operation is introduced to the resource selection process. First, we present a formalism to represent a sensor domain. We then introduce sound and complete mechanisms through which effective resource solutions for tasks are discovered. An extension to the representation is then proposed so that the agility in resource selection is increased. Finally, we present an architecture whereby a multitude of such knowledge bases are exposed as services so that a coalition can fully benefit from its networked resources; a query language – and its semantics – to discover appropriate service collections for user requirements are also presented. We have evaluated our work through controlled experiments and critical arguments. Through these evaluations, we have shown that our approach can indeed improve the resource selection process and can augment resource allocation mechanisms. Our approach is general in that, it can be applied in many other domains.
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Sankar, Sandhya. "INTELLIGENT PLACEMENT OF METERS/SENSORS FOR SHIPBOARD POWER SYSTEM ANALYSIS." MSSTATE, 2008. http://sun.library.msstate.edu/ETD-db/theses/available/etd-09102007-140439/.

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Real time monitoring of the shipboard power system is a complex task to address. Unlike the terrestrial power system, the shipboard power system is a comparatively smaller system but with more complexity in terms of its system operation. This requires the power system to be continuously monitored to detect any type of fluctuations or disturbances. Planning metering systems in the power system of a ship is a challenging task not only due to the dimensionality of the problem, but also due to the need for reducing redundancy while improving network observability and efficient data collection for a reliable state estimation process. This research is geared towards the use of a Genetic Algorithm for intelligent placement of meters in a shipboard system for real time power system monitoring taking into account different system topologies and critical parameters to be measured from the system. The algorithm predicts the type and location of meters for identification and collection of measurements from the system. The algorithm has been tested with several system topologies.
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Books on the topic "Intelligent sensors"

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1932-, Yamasaki Hiroo, ed. Intelligent sensors. Amsterdam: Elsevier, 1996.

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1967-, Gassmann Oliver, and Meixner H, eds. Sensors in intelligent buildings. Weinheim ; New York: Wiley-VCH, 2001.

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Kannadhasan, S., R. Nagarajan, and Alagar Karthick. Intelligent Technologies for Sensors. New York: Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003314851.

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H, Baltes, Göpel W, and Hesse J, eds. Sensors update. Weinheim: VCH, 1996.

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H, Baltes, Göpel W, and Hesse J, eds. Sensors update. Weinheim: VCH, 1996.

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Brasche, Ulrich. Intelligent sensors: Technology, applications, and European markets. Berlin: VDE-Verlag, 1989.

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Islam, Rafiqul. New developments in intelligent sensors and models. Hauppauge, N.Y: Nova Science Publishers, 2011.

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1938-, Zuech Nello, ed. Handbook of intelligent sensors for industrial automation. Reading, Mass: Addison-Wesley, 1992.

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Instruments, Texas. Optoelectronics and image sensors: Data book : CCD image sensors, optocouplers, intelligent displays, IR emitters, and phototransistors. Dallas, Texas: Texas Instruments, 1990.

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Incorporated, Texas Instruments, ed. Optoelectronics and image sensors data book, 1990: CCD image sensors, optocouplers, intelligent displays, IR emitters, and phototransistors. Dallas, Tex: Texas Instruments, 1990.

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Book chapters on the topic "Intelligent sensors"

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Mekid, Samir, Andrew Starr, and Robert Pietruszkiewicz. "Intelligent Wireless Sensors." In E-maintenance, 83–123. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-205-6_5.

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Mukhopadhyay, Subhas Chandra. "Wireless Sensors and Sensors Network." In Intelligent Sensing, Instrumentation and Measurements, 55–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37027-4_3.

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Hörmann, Leander B., Julian Karoliny, and Philipp Peterseil. "Solar-Based Energy Harvesting and Low-Power Wireless Networks." In Intelligent Secure Trustable Things, 235–51. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54049-3_14.

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AbstractIn modern industrial applications, machines and facilities, more and more sensors are used to control and optimise the processes. To be flexible and reduce cost, wireless sensors can be used in a broad range of applications. To prevent regular battery replacement, there is the possibility to supply wireless sensors by energy harvesting. In this chapter, we investigate the possibility to use solar-based energy harvesting to supply wireless sensors. For this, we consider four wireless network protocols and evaluate the power consumption using a simple sensor use case with different communication parameters. We further measure how much power can actually be harvested in a typical office environment with natural light. To provide realistic results, different sensor locations as well as seasonal changes are considered. The evaluations are combined to understand what size of solar cell is needed to supply the considered wireless protocols with different configurations.
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Nwagboso, Christopher O. "Intelligent sensors for vehicles." In Automotive Sensory Systems, 323–51. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1508-7_15.

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Mukhopadhyay, Subhas Chandra. "Sensors Fundamental." In Intelligent Sensing, Instrumentation and Measurements, 1–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37027-4_1.

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Banupriya, R., J. Manjushree Kumari, and L. Suganya. "Modeling of an Active Voltage Doubler: Resonant DC–DC Converter for Wide Range DC Drive Applications." In Intelligent Technologies for Sensors, 145–62. New York: Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003314851-13.

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Joshi, Apoorva, Ambrish Kumar Sharma, Karuna Nidhi Pandagre, and Sanjeev Gour. "Medical Devices and Sensor Application." In Intelligent Technologies for Sensors, 75–88. New York: Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003314851-8.

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Chindhi, Pradeep, H. P. Rajani, Geeta Kalkhambkar, and Rajashri Khanai. "Design and Optimization of Low-Cost RF Energy-Harvesting Circuit." In Intelligent Technologies for Sensors, 305–14. New York: Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003314851-23.

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Ananthi, J. Vijitha, and P. Subha Hency Jose. "Performance Analysis of Clustered Routing Protocol for Wearable Sensor Devices in an IoT-Based WBAN Environment." In Intelligent Technologies for Sensors, 253–70. New York: Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003314851-20.

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Jaganathan, Subash Chandra Bose, Murugesh Veerasamy, Azath Mubarakali, Chandramohan Dhasarathan, Velmani Ramasamy, R. Kalpana, and Ninoslav Marina. "The Future of Web Crowdfunding: An Ethereum Blockchain Approach." In Intelligent Technologies for Sensors, 337–72. New York: Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003314851-25.

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Conference papers on the topic "Intelligent sensors"

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Schoen, Marco P. "Dynamic Compensation of Intelligent Sensors." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-42275.

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Commercial sensors have generally, due to their own characteristics, some undesirable influences on the measured quantity and its precision. In particular, the dynamic characteristics can be reflected on to the measured quantity and lead to false or delayed interpretation of the underlying physical process. The quality and therefore the cost of the sensor is often tied with the dynamic performance of these instruments. Intelligent sensors are able to adapt to changing environments, calibrate themselves, and predict the pattern of the future signal. This paper presents algorithms to improve the dynamic performance of sensors, identify the dynamic characteristics of the sensor, and to predict the future pattern of the measured quantity. In particular, two inverse filters are proposed for the improvement of the sensors dynamic performance. One filter incorporates an optimal constant feedback gain that reduces the computational cost and increases the accuracy. A system identification method is used to identify the sensor’s dynamic properties and allows for adaptation of the inverse filter’s parameters. This identification algorithm computes the optimum input to the system i.e. the sensor. The optimization is based on the inverse correlation matrix of the information matrix. A genetic algorithm is used to perform both optimizations, for the computation of the optimal input, and for the optimal constant feedback gain. In addition, a predictive filter formulation is given that is based on the identified system. Simulation results indicate that both inverse filters are capable of recovering the original or true signal. The second filter shows superiority in terms of convergence, lower computational cost, and lower error due to its optimized parameters. The predictive filter indicates good working accuracy for the signal prediction.
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Oesch, Christopher, Ajay Mahajan, Lucas Utterback, Haricharan Padmanaban, Sanjeevi Chitikeshi, and Fernando Figueroa. "Intelligent Sensors for Integrated Health Management Systems." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-13576.

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This paper describes work being conducted on the development of intelligent sensors with learning capabilities as part of an integrated systems approach. The integrated systems approach treats the sensor as a complete system with its own sensing hardware (the traditional sensor), A/D converter, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow the system to learn its own behavior. The immediate application is the monitoring of rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS). The PIS as discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the digital data. If any event, i.e. spike, drift, noise, is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with a confidence factor in the reliability of the data. The VIS discussed here is a virtual implantation of the PIS in the G2 software environment. The VIS is designed to mirror the operations of the PIS; however, the VIS works on a computer at which digital data is provided as the input. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities.
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Yuan, Jane Xiaojing, and Fernando Figueroa. "Intuitive Intelligent Sensor Fusion With Highly Autonomous Sensors." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/dsc-24502.

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Abstract The objective of sensor fusion is to synergistically combine different sources of sensory information into one representational format to provide more complete and precise interpretation of the system. A generic sensor fusion framework based on a highly autonomous sensor (HAS) model is presented. The framework provides freedom to choose different data fusion methods and combine them together to achieve better performance. In the context of HAS’s, this paper describes a hierarchical decentralized sensor-fusion approach based on a qualitative theory to interpret measurements, and on qualitative procedures to reason and make decisions based on the measurement interpretations. In this manner, heuristic fusion methods are applied at a high-qualitative level as well as at a numerical level when necessary. This approach implements intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors.
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Chitikeshi, Sanjeevi, Ajay Mahajan, Pavan Bandhil, Lucas Utterbach, and Fernanado Figueroa. "Intelligent Sensors: Strategies for an Integrated Systems Approach." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-79403.

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This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).
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Parmar, Sumit, and Nilam Awte. "Intelligent sensors." In ICWET '10: International Conference and Workshop on Emerging Trends in Technology. New York, NY, USA: ACM, 2010. http://dx.doi.org/10.1145/1741906.1742232.

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Mukherjee, Somnath. "Intelligent Proximity Sensors." In 2012 International Conference on Computers and Devices for Communication (CODEC). IEEE, 2012. http://dx.doi.org/10.1109/codec.2012.6509343.

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Unsal, S., A. Shirkhodaie, and A. H. Soni. "Nonparametric Object Recognition With a New Tactile Sensor." In ASME 1992 Design Technical Conferences. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/detc1992-0448.

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Abstract Adding sensing capability to a robot provides the robot with intelligent perception capability and flexibility of decision making. To perform intelligent tasks, robots are highly required to perceive their operating environment, and react accordingly. With this regard, tactile sensors offer to extend the scope of intelligence of a robot for performing tasks which require object touching, recognition, and manipulation. This paper presents the design of an inexpensive pneumatic binary-array tactile sensor for such robotic applications. The paper describes some of the techniques implemented for object recognition from binary sensory information. Furthermore, it details the development of software and hardware which facilitate the sensor to provide useful information to a robot so that the robot perceives its operating environment during manipulation of objects.
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"Intelligent Sensors, Sensor Networks, and Information Processing." In 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, 2018. http://dx.doi.org/10.1109/etfa.2018.8502521.

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Kumar, Manish, Devendra P. Garg, and Randy A. Zachery. "Intelligent Sensor Modeling and Data Fusion via Neural Network and Maximum Likelihood Estimation." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-80972.

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The major thrust of this paper is to develop a sensor model based on a probabilistic approach that could accurately provide information about individual sensor’s uncertainties and limitations. The sensor model aims to provide a most informative likelihood function that can be used to obtain a statistical and probabilistic estimate of uncertainties and errors due to some environmental parameters or parameters of any feature extraction algorithm used in estimation based on sensor’s outputs. This paper makes use of a neural network that has been trained with the help of a novel technique that obtains training signal from a maximum likelihood estimator. The proposed technique was applied to model stereo-vision sensors and Infra-Red (IR) proximity sensor, and information from these sensors were fused in a Bayesian framework to obtain a three-dimensional occupancy profile of objects in robotic workspace. The capability of the proposed technique in accurately obtaining three-dimensional occupancy profile and efficiently removing individual sensor uncertainties was demonstrated and validated via experiments carried out in the Robotics and Manufacturing Automation (RAMA) Laboratory at Duke University.
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Chang, Yen-Chih, Chia-Chun Wang, Wen-De Jian, Chia-Chan Chang, Guo-Hua Feng, and Huang-Chen Lee. "Wireless sensors for intelligent ball screws monitoring." In 2016 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet). IEEE, 2016. http://dx.doi.org/10.1109/wisnet.2016.7444318.

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Reports on the topic "Intelligent sensors"

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Jacobs, Eddie L., David J. Russomanno, Carl Halford, and Aaron Robinson. Intelligent Network-Centric Sensors Development Program. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada569059.

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Ng, B., and W. Hanley. Towards Intelligent Dynamic Deployment of Mobile Sensors in Complex Resource-Bounded Environments. Office of Scientific and Technical Information (OSTI), May 2007. http://dx.doi.org/10.2172/919953.

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Mahlberg, Justin, Yaguang Zhang, Sneha Jha, Jijo K. Mathew, Howell Li, Jairaj Desai, Woosung Kim, et al. Development of an Intelligent Snowplow Truck that Integrates Telematics Technology, Roadway Sensors, and Connected Vehicle. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317355.

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The Indiana Department of Transportation (INDOT) manages and maintains over 28,000 miles of roadways. Maintenance of the roadways includes pavement repair in the summer as well as snow removal and de-icing in the winter. The prioritization of assets during winter storm events is crucial and impacts travel and safety. The objective of this project was to identify and develop tools INDOT could provide its operators to effectively perform winter operation de-icing activities. This project examined application methods and data to provide analytics and make data-driven decisions for state-wide deployment and operations. Discovery of calibration metrics partnered with fleetwide telematics enabled the development of analytic dashboards that allowed real-time evaluations and adjustments to be made during winter operation activities. These tools will allow the agency to better treat and enhance safety for road users.
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Peters, Kara J., and Mohammed A. Zikry. Intelligent Multi-scale Sensors for Damage Identification and Mitigation in Woven Composites for Aerospace Structural Applications. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada579751.

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Raghavan, Ajay. TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report. Office of Scientific and Technical Information (OSTI), April 2020. http://dx.doi.org/10.2172/1615666.

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Ratmanski, Kiril, and Sergey Vecherin. Resilience in distributed sensor networks. Engineer Research and Development Center (U.S.), October 2022. http://dx.doi.org/10.21079/11681/45680.

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With the advent of cheap and available sensors, there is a need for intelligent sensor selection and placement for various purposes. While previous research was focused on the most efficient sensor networks, we present a new mathematical framework for efficient and resilient sensor network installation. Specifically, in this work we formulate and solve a sensor selection and placement problem when network resilience is also a factor in the optimization problem. Our approach is based on the binary linear programming problem. The generic formulation is probabilistic and applicable to any sensor types, line-of-site and non-line-of-site, and any sensor modality. It also incorporates several realistic constraints including finite sensor supply, cost, energy consumption, as well as specified redundancy in coverage areas that require resilience. While the exact solution is computationally prohibitive, we present a fast algorithm that produces a near-optimal solution that can be used in practice. We show how such formulation works on 2D examples, applied to infrared (IR) sensor networks designed to detect and track human presence and movements in a specified coverage area. Analysis of coverage and comparison of sensor placement with and without resilience considerations is also performed.
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Alizadeh, Omid, Niroj Gurung, Farid Katiraei, Muhidin Lelic, Ahmad Momeni, Aleksi Paaso, Paul Pabst, Douglas Proudfoot, and Farnoosh Rahmatian. Sensors with Intelligent Measurement Platform and Low-cost Equipment (SIMPLE) for Monitoring and Control of Medium Voltage Distribution Systems with High Penetration of Intermittent Distributed Energy Resources. Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1774040.

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Stein, Peter J., and Armen Bahlavouni. Underwater Intelligent Sensor Protection System. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada630460.

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Stein, Peter J., and Armen Bahlavouni. Underwater Intelligent Sensor Protection System. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada618367.

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Stein, Peter J. Underwater Intelligent Sensor Protection System. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada624969.

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