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Dissertations / Theses on the topic 'Fire detection'
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1
Al-Khateeb, Shadi A. "Fire Detection Using Wireless Sensor Networks." Youngstown State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1411471850.
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Luisi, Domenico. "Conceptual design and specification of a microsatellite forest fire detection system /." Online version of thesis, 2007. http://hdl.handle.net/1850/5771.
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Zafar, Muhammad Asif, and Zeshan Aslam Khan. "Fire Detection in Coal Mines Using WSN." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-5030.
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Fire Detection in Coal Mines Using WSN is an application for monitoring and detection of fire in coal mines using wireless sensor networks. The application uses BDI (Belief, Desire and Intention) based multi agent model and its implementation on sensor networks. The Language which is interpreted by Jason is an extension of AgentSpeak; this is based on the BDI Architecture. The BDI agents are reactive planning systems, systems that are not meant to compute the value of a function and terminate, but rather designed to be permanently running, reacting to some form of event. The distributed model of environment is adopted to overcome the communication overhead, power consumption, network delay and reliability on a centralized base station.
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Krasuski, Adam, and Piotr Wasilewski. "The Detection of Outlying Fire Service’s Reports." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113145.
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We present a methodology for improving the detection of outlying Fire Service’s reports based on domain knowledge and dialogue with Fire & Rescue domain experts. The outlying report is considered as element which is significantly different from the remaining data. Outliers are defined and searched on the basis of domain knowledge and dialogue with experts. We face the problem of reducing high data dimensionality without loosing specificity and real complexity of reported incidents. We solve this problem by introducing a knowledge based generalization level intermediating between analysed data and experts domain knowledge. In the methodology we use the Formal Concept Analysis methods for both generation appropriate categories from data and as tools supporting communication with domain experts. We conducted two experiments in finding two types of outliers in which outliers detection was supported by domain experts.
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True, Nicholas James. "Real-time fire detection in low quality video." Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/fullcit?p1477940.
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Thesis (M.S.)--University of California, San Diego, 2010.Title from first page of PDF file (viewed July 13, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (leaves 63-65).
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Rexfort, Claudia. "A contribution to fire detection modelling and simulation." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=971472572.
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Kutzner, Kendy. "Processing MODIS Data for Fire Detection in Australia." Thesis, Universitätsbibliothek Chemnitz, 2002. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200200831.
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The aim of this work was to use remote sensing data from the MODIS instrument of the Terra satellite to detect bush fires in Australia. This included preprocessing the demodulator output, bit synchronization and reassembly of data packets. IMAPP was used to do the geolocation and data calibration. The fire detection used a combination of fixed threshold techniques with difference tests and background comparisons. The results were projected in a rectangular latidue/longitude map to remedy the bow tie effect. Algorithms were implemented in C and Matlab. It proved to be possible to detect fires in the available data. The results were compared with fire detection done done by NASA and fire detections based on other sensors and found to be very similarDas Ziel dieser Arbeit war die Nutzung von Fernerkundungsdaten des MODIS Instruments an Bord des Satelliten Terra zur Erkennung von Buschfeuern in Australien. Das schloss die Vorverarbeitung der Daten vom Demodulator, die Bitsynchronisation und die Umpacketierung der Daten ein. IMAPP wurde genutzt um die Daten zu kalibrieren und zu geolokalisieren. Die Feuererkennung bedient sich einer Kombination von absoluten Schwellwerttests, Differenztests und Vergleichen mit dem Hintergrund. Die Ergebnisse wurden in eine rechteckige Laengen/Breitengradkarte projiziert um dem BowTie Effekt entgegenzuwirken. Die benutzten Algrorithmen wurden in C und Matlab implementiert. Es zeigte sich, dass es moeglich ist in den verfuegbaren Daten Feuer zu erkennen. Die Ergebnisse wurden mit Feuererkennungen der NASA und Feuererkennung die auf anderen Sensoren basieren verglichen und fuer sehr aehnlich befunden
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Rehman, Adeel ur. "Autonomous Fire Detection Robot Using Modified Voting Logic." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32008.
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Recent developments at Fukushima Nuclear Power Plant in Japan have created urgency in the scientist community to come up with solutions for hostile industrial environment in case of a breakdown or natural disaster. There are many hazardous scenarios in an indoor industrial environment such as risk of fire, failure of high speed rotary machines, chemical leaks, etc. Fire is one of the leading causes for workplace injuries and fatalities. The current fire protection systems available in the market mainly consist of a sprinkler systems and personnel on duty. In the case of a sprinkler system there could be several things that could go wrong, such as spraying water on a fire created by an oil leak may even spread it, the water from the sprinkler system may harm the machinery in use that is not under the fire threat and the water could potentially destroy expensive raw material, finished goods and valuable electronic and printed data. There is a dire need of an inexpensive autonomous system that can detect and approach the source of these hazardous scenarios. This thesis focuses mainly on industrial fires but, using same or similar techniques on different sensors, may allow it to detect and approach other hostile situations in industrial workplace. Autonomous robots can be equipped to detect potential threats of fire and find out the source while avoiding the obstacles during navigation. The proposed system uses Modified Voting Logic Fusion to approach and declare a potential fire source autonomously. The robot follows the increasing gradient of light and heat intensity to identify the threat and approach the source.
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Osgood, David Raymond. "The detection of the early stages of fire." Thesis, London South Bank University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336804.
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Lawday, R. M. "The automatic detection of audible fire alarm warnings." Thesis, Birmingham City University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.573693.
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Le, Xuqing. "Fire Detection Robot using Type-2 Fuzzy Logic Sensor Fusion." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32471.
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In this research work, an approach for fire detection and estimation robots is presented. The approach is based on type-2 fuzzy logic system that utilizes measured temperature and light intensity to detect fires of various intensities at different distances. Type-2 fuzzy logic system (T2 FLS) is known for not needing exact mathematic model and for its capability to handle more complicated uncertain situations compared with Type-1 fuzzy logic system (T1 FLS). Due to lack of expertise for new facilities, a new approach for training experts’ expertise and setting up T2 FLS parameters from pure data is discussed in this thesis. Performance of both T1 FLS and T2 FLS regarding to same fire detection scenario are investigated and compared in this thesis. Simulation works have been done for fire detection robot of both free space scenario and new facility scenario to illustrate the operation and performance of proposed type-2 fuzzy logic system. Experiments are also performed using LEGO MINDSTROMS NXT robot to test the reliability and feasibility of the algorithm in physical environment with simple and complex situation.
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Alamgir, Nyma. "Computer vision based smoke and fire detection for outdoor environments." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/201654/1/Nyma_Alamgir_Thesis.pdf.
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Surveillance Video-based detection of outdoor smoke and fire has been a challenging task due to the chaotic variations of shapes, movement, colour, texture, and density. This thesis contributes to the advancement of the contemporary efforts of smoke and fire detection by proposing novel technical methods and their possible integration into a complete fire safety model. The novel contributions of this thesis include an efficient feature calculation method combining local and global texture properties, the development of deep learning-based models and a conceptual framework to incorporate weather information in the fire safety model for improved accuracy in fire prediction and detection.
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Goessmann, Florian. "Improved spatial resolution of bushfire detection with MODIS." Thesis, Curtin University, 2007. http://hdl.handle.net/20.500.11937/909.
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The capability to monitor bushfires on a large scale from space has long been identified as an important contribution to climate and atmospheric research as well as a tool an aid in natural hazard response. Since the work by Dozier (1981), fire monitoring from space has relied on the principles he described. His method of identifying fires within a pixel significantly larger than the fire by utilizing the different responses of the 3 μm and 11 μm channels has been applied to a number of sensors. Over the last decade a lot of work has been invested to refine and validate fire detections based on this approach. So far, the application of the method proposed by Dozier (1981) reached its peak with the launch of the MODIS instrument on board the Terra satellite. In contrast to earlier sensors, MODIS was equipped with spectral channels specifically designed for the detection of fires with algorithms based on the work by Dozier (1981). These channels were designed to overcome problems experienced with other platforms, the biggest of which is the saturation of the 3 μm channel caused by big, hot fires. Since its launch, MODIS has proven itself to be a capable platform to provide worldwide fire detection at a moderate resolution of 1 km on a daily basis.It is the intention of this work to open up new opportunities in remote sensing of fires from satellites by showing capabilities and limitations in the application of other spectral channels, in particular the 2.1 μm channel of MODIS, than the ones currently used. This channel is chosen for investigation as fires are expected to emit a significant amount of energy in this bandwidth and as it is available at a native resolution of 500 m on MODIS; double the resolution of the 3 μm and 11 μm channels. The modelling of blackbodies of typical bushfire temperatures shows that a fire detection method based on the 2.1 μm channel will not be able to replace the current methods. Blackbodies of temperatures around 600 to 700 K, that are common for smoldering fires, do not emit a great amount of energy at 2.1 μm. It would be hardly possible to detect those fires by utilizing the 2.1 μm channel. The established methods based on the 3 μm and 11 μm channels are expected to work better in these cases. Blackbodies of typically flaming fires (above 800 K) however show a very high emission around 2.1 μm that should make their detection using the 2.1 μm channel possible.In order to develop a fire detection method based on the 2.1 μm channel, it is necessary to differentiate between the radiance caused by a fire of sub pixel size and the radiance of a pixel caused by the reflection of sunlight. This is attempted by using time series of past observations to model a reflectance value for a given pixel expected in absence of a fire. A fire detection algorithm exploiting the difference between the expected and observed reflectance is implemented and its detection results are compared to high resolution ASTER fire maps, the standard MODIS fire detection algorithm (MOD14) and burnt area maps. The detections of the method based on the 2.1 μm channel are found to correspond very well with the other three datasets. However, the comparison showed detections that do not align with MOD14 active fire detections but are generally aligned with burn areas. This phenomena has to be investigated in the future.
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Giglio, Louis. "Detection, evaluation, and analysis of global fire activity using MODIS data." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3490.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.Thesis research directed by: Geography. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Saunders, Julie Ann. "The Prediction of Smoke Detector Activation Times in a Two-Storey House Fire through CFD Modelling." Thesis, University of Canterbury. Civil and Natural Resources Engineering, 2010. http://hdl.handle.net/10092/4077.
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This report describes an investigation into the prediction of the activation times of domestic ionisation and photoelectric smoke detectors within a two storey dwelling, the work undertaken being an extension to that previously presented by Brammer (2002). Three fire scenarios are considered, each having been a real test fire undertaken at the Building Research Establishment in Cardington. These three fire scenarios all involved the flaming combustion of an upholstered armchair within the lounge on the Ground floor. During the experiments various results were recorded, including temperatures, optical densities and smoke detector activation times.
The fire scenarios where modelled using FDS, Version 5. Base parameters regarding the fuel load where defined to be 0.05kgsoot/kgfuel and 20MJ/kg. Consideration was also given to the effect varying the effective heat of combustion and defined soot yield would have on derived smoke detector activation times. Additional simulations where thus run considering soot yields of 0.04kgsoot/kgfuel and 0.10ksoot/kgfuel, and an effective heat of combustion of 25MJ/kg.
Three prediction methods where applied to the results of the FDS simulations for derivation of the activation times of smoke detectors located throughout the house. These methods where the temperature correlation method, Heskestad’s method, and Cleary’s method. The temperature correlation method considered activation criterions of 4°C, 13°C and 20°C above ambient.
The Heskestad and Cleary methods were found to derive comparable activation times for each detector location. None of the prediction algorithms where however found to predict activation times consistently comparable to the test data. Rather, it was determined that for an appropriate prediction method to be adopted for accurate assessment of a given fire scenario, consideration must be given to the:
• type of detector being assessed;
• location of the detector relative to the fire;
• mode of combustion (i.e. flaming or smouldering); and the
• growth rate of the fire.
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Goessmann, Florian. "Improved spatial resolution of bushfire detection with MODIS." Curtin University of Technology, Department of Applied Physics, 2007. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=17134.
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The capability to monitor bushfires on a large scale from space has long been identified as an important contribution to climate and atmospheric research as well as a tool an aid in natural hazard response. Since the work by Dozier (1981), fire monitoring from space has relied on the principles he described. His method of identifying fires within a pixel significantly larger than the fire by utilizing the different responses of the 3 μm and 11 μm channels has been applied to a number of sensors. Over the last decade a lot of work has been invested to refine and validate fire detections based on this approach. So far, the application of the method proposed by Dozier (1981) reached its peak with the launch of the MODIS instrument on board the Terra satellite. In contrast to earlier sensors, MODIS was equipped with spectral channels specifically designed for the detection of fires with algorithms based on the work by Dozier (1981). These channels were designed to overcome problems experienced with other platforms, the biggest of which is the saturation of the 3 μm channel caused by big, hot fires. Since its launch, MODIS has proven itself to be a capable platform to provide worldwide fire detection at a moderate resolution of 1 km on a daily basis.It is the intention of this work to open up new opportunities in remote sensing of fires from satellites by showing capabilities and limitations in the application of other spectral channels, in particular the 2.1 μm channel of MODIS, than the ones currently used. This channel is chosen for investigation as fires are expected to emit a significant amount of energy in this bandwidth and as it is available at a native resolution of 500 m on MODIS; double the resolution of the 3 μm and 11 μm channels. The modelling of blackbodies of typical bushfire temperatures shows that a fire detection method based on the 2.1 μm channel will not be able to replace the current methods. Blackbodies of temperatures around 600 to 700 K, that are common for smoldering fires, do not emit a great amount of energy at 2.1 μm. It would be hardly possible to detect those fires by utilizing the 2.1 μm channel. The established methods based on the 3 μm and 11 μm channels are expected to work better in these cases. Blackbodies of typically flaming fires (above 800 K) however show a very high emission around 2.1 μm that should make their detection using the 2.1 μm channel possible.
In order to develop a fire detection method based on the 2.1 μm channel, it is necessary to differentiate between the radiance caused by a fire of sub pixel size and the radiance of a pixel caused by the reflection of sunlight. This is attempted by using time series of past observations to model a reflectance value for a given pixel expected in absence of a fire. A fire detection algorithm exploiting the difference between the expected and observed reflectance is implemented and its detection results are compared to high resolution ASTER fire maps, the standard MODIS fire detection algorithm (MOD14) and burnt area maps. The detections of the method based on the 2.1 μm channel are found to correspond very well with the other three datasets. However, the comparison showed detections that do not align with MOD14 active fire detections but are generally aligned with burn areas. This phenomena has to be investigated in the future.
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England, Ben. "An investigation into arc detection and fire safety aspects of photovoltaic installations." Thesis, England, Ben (2012) An investigation into arc detection and fire safety aspects of photovoltaic installations. Other thesis, Murdoch University, 2012. https://researchrepository.murdoch.edu.au/id/eprint/15561/.
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The number of PV systems around the world is increasing and the systems are aging with little to no inspections and maintenance. Exposed to UV, the weather and rodents cables, connection points and other components can degrade to the point where there is a break in the circuit and over this gap the current from the PV array can continue to flow causing an arc. The heat and electrical energy from the arc can ignite nearby materials and start a fire which could cause further damage. When an arc starts there is no off switch to easily cut the power from the PV array so the arcing situation can continue. A number of systems have been developed to detect these arcs in order to identify and eliminate them early before they start a fire. One of these devices was tested to determine if it was effective in detecting arcs. The Texas Instruments SolarMagic RD-195 DC Arc Detection Evaluation Board detected all the arcs created and did not give any false positives. The devices available on the market today are effective at detecting arcs and some have been integrated into the inverters of PV systems along with devices to extinguish any arcs. The integration of these and other features into PV systems makes PV systems safer and reduces the potential for damage to people the system and surrounds.
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Thomas, Evan Alexander Beirne. "Investigating the feasibility of a modulated diode laser for crewed spacecraft fire detection." Diss., Connect to online resource, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1433476.
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Alsaadi, Abdulrahman. "Smart smoke and fire detection with wireless and global system for mobile technology." Thesis, California State University, Long Beach, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=1606705.
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Fire safety is one of the major concerns for a safe home environment. Current implementations of home or workplace environment monitoring systems consist of rudimentary smoke detectors devoid of any communication capabilities. Recent trends in the industry have shown a growth in the use of smart devices at homes and with the recent advances in areas of machine learning and data sciences, this trend is expected to evolve at a rate faster than ever before. These smart devices constantly monitor the data of their environment and make decisions by performing data analytics on those observations. Amazon Echo is one such example where an ‘always-listening’ device responds intelligently to a speaker’s command giving its users a Smart Home experience.
In this implementation, we harness the developments in aforementioned areas to make Smart Fire Alarm System. The Smart Fire Alarm constantly monitors the environment and not only alerts the facility where it is located, but it also communicates with the fire department and the guardian of the property through Global System for Mobile (GSM) Communication making the damage control procedures efficient and faster. An ARM7 processor (LPDC 2148), ZigBee IEEE 802.15.4 protocol, and GSM subsystems are used in this implementation to communicate between the base station and smoke detectors.
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Davenport, Timothy M. "Early Forest Fire Detection using Texture Analysis of Principal Components from Multispectral Video." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/795.
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The aim of this study is to incorporate the spectral, temporal and spatial attributes of a smoke plume for Early Forest Fire Detection. Image processing techniques are used on multispectral (red, green, blue, mid-wave infrared, and long-wave infrared) video to segment and indentify the presence of a smoke plume within a scene.
The temporal and spectral variance of a smoke plume is captured through Principal Component Analysis (PCA) where the Multispectral-Multitemporal PCA is performed on a sequence of video frames simultaneously. The presence of a plume existing in one of the higher order principal components is determined by the texture of its spatial content. The texture is characterized by statistical descriptors derived from the principal component‟s joint probability density distribution of intensities occurring within a spatial relationship, known as a Gray Level Co-Occurrence Matrix (GLCM). Initial analysis is performed on selected frames where only a subset of time is considered. Once the parameters are chosen from the static analysis, the algorithms are executed on video through time to validate the method.
The results show that a smoke plume is readily segmented via PCA. Based on the five spectral bands over 3 seconds sampled at 1 second, the plume exists in the 7th principal component. Within these principal components, the smoke‟s presence is best identified by the correlation texture descriptor. The smoke is very spatially correlated compared to the scene at large. Therefore a spike in the spatial correlation of the principal components is all that is needed to identify the start of the smoke plume.
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Lynch, James Andrew. "A study of smoke aging examining changes in smoke particulate size." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0510104-194400/.
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Söderström, Rikard. "An early fire detection system through registration and analysis of waste station IR-images." Thesis, Linköpings universitet, Datorseende, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-71275.
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In this thesis, an investigation was performed to find ways of differencing between firesand vehicles at waste stations in hope of removing vehicles as a source of error duringearly fire detection. The existing system makes use of a heat camera, which rotates in 48different angles (also known as zones) in a fixed position. If the heat is above a certainvalue within a zone the system sounds the fire alarm.The rotation of the camera results in an unwanted displacement between two successiveframes within the same zone. By use of image registration, this displacement wasremoved. After the registration of an image, segmentation was performed where coldobjects are eliminated as an error source. Lastly, an analysis was performed upon thewarm objects.At the end, it was proven that the image registration had been a successful improvementof the existing system. It was also shown that vehicles can, to some extent, beeliminated as an error source.I denna uppsats görs en undersökning av sätt att urskilja mellan bränder och fordon vid avfallsbunkrar, i hopp om att ta bortfordon som felkälla under tidig branddetektion. Dagens system använder sig av en värmekamera som roterar i 48 vinklar(även kallade zoner) från en fix position och larmar då det blir för varmt i någon zon.Roteringen av kameran medför en icke önskvärd förskjutning mellan två efterföljande bilder inom samma zon. Processenbildregistrering används för att eliminera denna förskjutning. Efter registreringen utförs en segmentering där kalla objekt tasbort som felkälla. När detta är utfört görs en analys av de varma objekten med en mängd mätningar.I slutet bevisas att registreringen har fungerat mycket väl, likaså att det går till viss del att eliminera fordon som felkällaunder tidig brandetektion.
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Moussa, Georges Fouad Mr. "EARLY FOREST FIRE DETECTION USING TEXTURE, BLOB THRESHOLD, AND MOTION ANALYSIS OF PRINCIPAL COMPONENTS." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/881.
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Forest fires constantly threaten ecological systems, infrastructure and human lives. The purpose behind this study is minimizing the devastating damage caused by forest fires. Since it is impossible to completely avoid their occurrences, it is essential to accomplish a fast and appropriate intervention to minimize their destructive consequences. The most traditional method for detecting forest fires is human based surveillance through lookout towers. However, this study presents a more modern technique. It utilizes land-based real-time multispectral video processing to identify and determine the possibility of fire occurring within the camera’s field of view. The temporal, spectral, and spatial signatures of the fire are exploited. The methods discussed include: (1) Range filtering followed by entropy filtering of the infrared (IR) video data, and (2) Principal Component Analysis of visible spectrum video data followed by motion analysis and adaptive intensity threshold. The two schemes presented are tailored to detect the fire core, and the smoke plume, respectively.
Cooled Midwave Infrared (IR) camera is used to capture the heat distribution within the field of view. The fire core is then isolated using texture analysis techniques: first, range filtering applied on two consecutive IR frames, and then followed by entropy filtering of their absolute difference.
Since smoke represents the earliest sign of fire, this study also explores multiple techniques for detecting smoke plumes in a given scene. The spatial and temporal variance of smoke plume is captured using temporal Principal Component Analysis, PCA. The results show that a smoke plume is readily segmented via PCA applied on the visible Blue band over 2 seconds sampled every 0.2 seconds. The smoke plume exists in the 2nd principal component, and is finally identified, segmented, and isolated, using either motion analysis or adaptive intensity threshold.
Experimental results, obtained in this study, show that the proposed system can detect smoke effectively at a distance of approximately 832 meters with a low false-alarm rate and short reaction time. Applied, such system would achieve early forest fire detection minimizing fire damage.
Keywords: Image Processing, Principal Component Analysis, PCA, Principal Component, PC, Texture Analysis, Motion Analysis, Multispectral, Visible, Cooled Midwave Infrared, Smoke Signature, Gaussian Mixture Model.
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Garges, David Casimir. "Early Forest Fire Detection via Principal Component Analysis of Spectral and Temporal Smoke Signature." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1456.
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The goal of this study is to develop a smoke detecting algorithm using digital image processing techniques on multi-spectral (visible & infrared) video. By utilizing principal component analysis (PCA) followed by spatial filtering of principal component images the location of smoke can be accurately identified over a period of exposure time with a given frame capture rate. This result can be further analyzed with consideration of wind factor and fire detection range to determine if a fire is present within a scene. Infrared spectral data is shown to contribute little information concerning the smoke signature. Moreover, finalized processing techniques are focused on the blue spectral band as it is furthest away from the infrared spectral bands and because it experimentally yields the largest footprint in the processed principal component images in comparison to other spectral bands. A frame rate of .5 images/sec (1 image every 2 seconds) is determined to be the maximum such that temporal variance of smoke can be captured. The study also shows eigenvectors corresponding to the principal components that best represent smoke and are valuable indications of smoke temporal signature. Raw video data is taken through rigorous pre-processing schemes to align frames from respective spectral band both spatially and temporally. A multi-paradigm numerical computing program, MATLAB, is used to match the field of view across five spectral bands: Red, Green, Blue, Long-Wave Infrared, and Mid-Wave Infrared. Extracted frames are aligned temporally from key frames throughout the data capture. This alignment allows for more accurate digital processing for smoke signature. v Clustering analysis on RGB and HSV value systems reveal that color alone is not helpful to segment smoke. The feature values of trees and other false positives are shown to be too closely related to features of smoke for in solely one instance in time. A temporal principal component transform on the blue spectral band eliminates static false positives and emphasizes the temporal variance of moving smoke in images with higher order. A threshold adjustment is applied to a blurred blue principal component of non-unity principal component order and smoke results can be finalized using median filtering. These same processing techniques are applied to difference images as a more simple and traditional technique for identifying temporal variance and results are compared.
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Kohler, Daniel G. "STUDY OF STATISTICAL AND COMPUTATIONAL INTELLIGENCE METHODS OF DETECTING TEMPORAL SIGNATURE OF FOREST FIRE HEAT PLUME FROM SINGLE-BAND GROUND-BASED INFRARED VIDEO." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/796.
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This thesis will analyze video from land-based, cooled mid-wave infrared cameras to identify temporal features indicative of a heat plume from a forest fire. Desirable features and methods will show an ability to distinguish between heat plume movement and other movements, such as foliage, vehicles, humans, and birds in flight. Features will be constructed primarily using combinations of statistics and principal component analysis (PCA) with intent to detect key characteristics of fire and heat plume: persistence and growth. Several classification systems will combine and filter the features in an attempt to classify pixels as either heat or non-heat. The classification systems will be tuned and compared with common metrics of error rate and computation time. It was found that the movement pattern of a heat plume could be distinguished from the similar movement pattern of foliage by detecting outlier movement patterns, a phenomenon associated with the growth property of fire. Outlier movement patterns were best detected by thresholding the quotient of mean and median of a set of variance measurements over time. The best tested classifier in terms of minimizing false positives without losing the heat signal came from PCA of a dual-range moving average difference.
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Kutzner, Kendy. "Processing MODIS Data for Fire Detection in Australia Verarbeitung von MODIS Daten zur Feuererkennung in Australien /." [S.l. : s.n.], 2001. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10358966.
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Hammond, Sean LaRoy. "Mapping Fire Fuels Through Detection of Canopy Biomass Loading In Juniper, Sagebrush, and Gambel Oak Communities." DigitalCommons@USU, 2012. https://digitalcommons.usu.edu/etd/1194.
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Every year, millions of acres of forest and rangeland are burned in prescribed burns as well as wildfires. The costs associated with wildfires may be some of the largest we face as a society both in material goods and in life. The importance of managing fire fuels has increased with the development of the wildland-urban interface. With this increased emphasis has come the development of tools to assess, map, and simulate fuel maps at a landscape level. These fuel maps are then input into computer-aided wildfire simulation models that are used by land managers in the planning process. A current challenge for land managers is to find efficient ways to measure the amount and structure of fire fuels on a landscape level. Fuel models are one of the required inputs for software that mathematically computes wildfire rate of spread. Various methods have been used to develop fuel maps. It is the objective of this thesis to develop a method by which fuel models can be predicted and mapped on a landscape level through utilization of remotely sensed data. The proposed process for this method is: 1) develop landcover classification, 2) assess data analysis approaches for use in creation of predictive regression models, 3) correlation of data results to Natural Fuels Photo Series, and 4) translate Natural Fuels Photo Series classifications into fuel models described by Scott and Burgan.
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Guo, Shangyuan, and Dailu Wang. "Analysis and Recognition of Flames from Different Fuels." Thesis, University of Gävle, Department of Industrial Development, IT and Land Management, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-7301.
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This paper presents a method for recognition of flame types coming from different kinds of fuel through analysis of flame images. Accurate detection of fire alarm and achievement of early warning is positive development for cities fire safety. Image-based fire flame detection technology is a new effective way to achieve early warning through the early fire flame detection. Different fuel combustion in air it the basic of basis to recognize the type of flame. The application built up by using generic color model and the techniques of image analysis.
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Koch, Sandra. "The detection of sharp force, blunt force and gunshot trauma on whole pigs recovered from a fire environment." Thesis, Boston University, 2012. https://hdl.handle.net/2144/12455.
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Thesis (M.S.)--Boston UniversityThe ability to recognize and identify skeletal material is a fundamental skill in forensic and physical anthropology. Understanding the process that remains have undergone when they have been exposed to a fire environment necessitates further study and specialization as the basic structure of a bone may be altered from the microscopic level to the overall morphology. Analysis of burnt bone goes beyond understanding how the normal taphonomic processes may affect skeletal remains to the specifics of heat and fire related changes. Additionally, the study of how heat or fire alteration affects trauma determinations can be important for determining the forensic significance of a case. The procedures of a fire investigation play a very important role in the recognition, preservation and analysis of skeletal remains especially considering site recovery techniques and perimortem trauma interpretation determination. This study utilized whole pigs to document changes to trauma from exposure to a compartment fire. The results were compared to previous studies done on individual skeletal elements to show that trauma was still recognizable and often protected in the postcranial body.
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Bernardi, Davide. "Detecting Single-Cell Stimulation in Recurrent Networks of Integrate-and-Fire Neurons." Doctoral thesis, Humboldt-Universität zu Berlin, 2019. http://dx.doi.org/10.18452/20560.
Full textAbstract:
Diese Arbeit ist ein erster Versuch, mit Modellbildung und mathematischer Analyse die Experimente zu verstehen, die zeigten, dass die Stimulation eines einzelnen Neurons im Cortex eine Verhaltensreaktion auslösen kann. Dieser Befund stellt die verbreitete Ansicht infrage, dass viele Neurone nötig sind, um Information zuverlässig kodieren zu können. Der Ausgangspunkt der vorliegenden Untersuchung ist die Stimulation einer zufällig ausgewählten Zelle in einem Zufallsnetzwerk exzitatorischer und inhibitorischer Neuronmodelle. Es wird dann nach einem plausiblen Ausleseverfahren gesucht, das die Einzelzellstimulation mit einer mit den Experimenten vergleichbaren Zuverlässigkeit detektieren kann. Das erste Ausleseschema reagiert auf Abweichungen vom spontanen Zustand in der Aktivität einer Auslesepopulation. Die Stimulation wird detektiert, wenn bei der Auswahl der Auslesepopulation denjenigen Neuronen ein Vorzug gegeben wird, die eine direkte Verbindung von der stimulierten Zelle bekommen. Im zweiten Teil der Arbeit wird das Ausleseschema erweitert, indem ein zweites Netzwerk als Ausleseschaltkreis dient. Interessanterweise erweist sich dieses Ausleseschema nicht nur als plausibler, sondern auch als effektiver. Diese Resultate basieren sowohl auf Simulationen als auch auf analytischen Rechnungen. Weitere Experimente zeigten, dass eine konstante Strominjektion einen Effekt auslöst, der kaum von Dauer und Intensität der Stimulation abhängt, der aber bei unregelmäßiger Stimulation zunimmt. Der letzte Teil der Arbeit befasst sich mit einer theoretischen Erklärung für diese Ergebnisse. Hierzu werden die biologischen Eigenschaften des Systems im Modell detaillierter beschrieben. Weiterhin wird die Funktionsweise des Ausleseschemas so modifiziert, dass es auf Veränderungen reagiert, anstatt den Input zu integrieren. Dieser Differenzierdetektor liefert Ergebnisse, die mit den Experimenten übereinstimmen, und könnte bei nichtstationärem Input vorteilhaft sein.This thesis is a first attempt at developing a theoretical model of the experiments which show that the stimulation of a single cell in the cortex can trigger a behavioral reaction and that challenge the common belief that many neurons are needed to reliably encode information. As a starting point of the present work, one neuron selected at random within a random network of excitatory and inhibitory integrate-and-fire neurons is stimulated. One important goal of this thesis is to seek a readout scheme that can detect the single-cell stimulation in a plausible way with a reliability compatible with the experiments. The first readout scheme reacts to deviations from the spontaneous state in the activity of a readout population. When the choice of readout neurons is sufficiently biased towards those receiving direct links from the stimulated cell, the stimulation can be detected. In the second part of the thesis, the readout scheme is extended by employing a second network as a readout circuit. Interestingly, this new readout scheme is not only more plausible, but also more effective. These results are based both on numerical simulations of the network and on analytical approximations. Further experiments showed that the probability of the behavioral reaction is substantially independent of the length and intensity of the stimulation, but it increases when an irregular current is used. The last part of this thesis seeks a theoretical explanation for these findings. To this end, a recurrent network including more biological details of the system is considered. Furthermore, the functioning principle of the readout is modified to react to changes in the activity of the local network (a differentiator readout), instead of integrating the input. This differentiator readout yields results in accordance with the experiments and could be advantageous in the presence of nonstationarities.
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Radjabi, Ryan F. "WILDFIRE DETECTION SYSTEM BASED ON PRINCIPAL COMPONENT ANALYSIS AND IMAGE PROCESSING OF REMOTE-SENSED VIDEO." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1621.
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Early detection and mitigation of wildfires can reduce devastating property damage, firefighting costs, pollution, and loss of life. This thesis proposes the method of Principal Component Analysis (PCA) of images in the temporal domain to identify a smoke plume in wildfires. Temporal PCA is an effective motion detector, and spatial filtering of the output Principal Component images can segment the smoke plume region. The effective use of other image processing techniques to identify smoke plumes and heat plumes are compared. The best attributes of smoke plume detectors and heat plume detectors are evaluated for combination in an improved wildfire detection system. PCA of visible blue images at an image sampling rate of 2 seconds per image effectively exploits a smoke plume signal. PCA of infrared images is the fundamental technique for exploiting a heat plume signal. A system architecture is proposed for the implementation of image processing techniques. The real-world deployment and usability are described for this system.
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Chen, Hung-Ming, and 陳弘明. "Automative Fire Detection Robot." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/72616538310876955707.
Full textAbstract:
碩士國立雲林科技大學
電機工程系
102
Due to the high frequency of fires in modern environment, how to prevent effectively is an important issue; the loss can be minimized by taking a prevention in advance. Early the prevention of fire was done by people; and later evolved into the sensor to detect the fire that detection system can detect smoke and temperature; however the smoke and the temperature diffusion is slow, it happened time delay of detection and distance shorter issues. Visual flame detection system can improve these shortcomings. To achieve immediate early discovery of fire to avoid the expansion purposes through an effective methods of visual flame detection to identify flame pixels. This thesis is to develop an automatic fire monitoring with modular robot; the main contoroller is AT89S52 produced by Atmel; and to design a wireless remote computers can be remote and immediate effectively detect temperature changes of environment; as an automatic fire detection robot control system. In the experiments; robot is free to walk around; and detects the fire ambient temperature in an unknown environment. Human-machine interface controls the robot action and uses the Sensirion's "SHT71" temperature sensor; Logitech camera captures image around environmental using recognition algorithms to identify suspicious fired zone.
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CHAN, YA-LI, and 詹雅莉. "The System of Fire Detection." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/48622000131579802333.
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碩士吳鳳科技大學
光機電暨材料研究所
104
Due to the high frequency of fire occurrence in modern environments, how to prevent fire effectively is an important issue. The fire loss can be minimized by taking a suitable fire prevention. Early the fire prevention was performed by people; and later the flame sensors were developed to detect the smoke and temperature. However the diffusion rates of the smoke and the temperature are slower, it leads to the shortcomings of the time delay and lower coverage on detection. Visual flame detection system can improve these shortcomings. The visual flame detection system can immediately identify the flame pixels, so that it can early find the fire point to avoid the fire expansion. This thesis is to develop a modular robot with automatic fire monitoring; the main controller is AT89S52 produced by Atmel; and a wireless remote computer is designed as an automatic fire detection robot control system to remotely control and immediately detect the temperature changes of environments. In the experiments, the robot is free to walk around, and detects the flame and the ambient temperature in an unknown environment. The human-machine interface is designed to control the robot action. The Sensirion's "SHT71" temperature sensor and the Logitech camera are used to detect temperature and to capture image around the environment. Finally, the flame recognition algorithm is employed to identify the suspicious fire zone. Keywords: robot, temperature sensors, fire detection, human-machine interface
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Peng, Jian-Wen, and 彭建文. "An Investigation of Fire Detection." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/89544312207866452133.
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碩士淡江大學
資訊工程學系
89
In general, the object tracking technology can be applied extensively to traffic control, public security, and object recognition. About object tracking technology, there are three main steps of tracking the object from a series image: separating object from the background, identifying and tracing it.In terms of traditional object tracking technology, the tracked object usually should have fixed shape, so it can be separated from the background by characteristics. For instance, the tracked object can be any line-moving object, such as running cars, flying airplanes or sailing boats. The tracked object can be separated by the general technology due to the monotone of background. However, this kind of traditional technology fails to track the object that rapid moving or continuously changing in shape.The purpose of this study is to discuss a new technology called “Color Separated” that tracked object from the viewpoint of chromatology. It also can track the object that moves rapidly or keeps continuously changing in shape, especially natural phenomenon, such as fire or water. This study put more emphasis on the tracked object’s color of the collaboration between hue, saturation and brightness in images. This technology can track rapid-moving and unfixed object with the specific color bandwidth precisely. Moreover, the technology is not necessary to consider about the various problems, which are interfered with resolution, noise signals or different shot angles and focus.“Color Separate” technology can be applied to fire detection. In this study, a “fire-detect system” model is built based on “color separated” technology. Compared traditional methodology of fire-detect with new technology, the area of target image can be found by subtracting the object images and getting the range of image differences. In terms of “color mask” of “Color Separated”, the area of “fire” image will be separated from background image, then the system is able to distinguish the real color of “fire” image from similar color of non-fire object, then non-fire object will be discarded in order to identify the real “fire” image by way of “color mask”.In the model, it should be mentioned that “disorder” is used to be instead of traditional complex operation. Disorder can find fire rapidly and detect the range that the fire spread. In addition, it can also measure the burning area and burning level.In summary, this system is able to operate properly real-time. Combined with monitoring and alarm system, this model can provide proper warning to avoid the disaster as fire just starts. It is great helpful to industrial security and public security.
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Chen, Kuang-Yue, and 陳寬裕. "Study of Fire Detection System." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/67465975375746935114.
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碩士國立交通大學
電機與控制工程系
87
This thesis focus on the study of current fire detection systems. Recent research results on the fire detection systems are also studied. In this thesis, we divide the current system into four parts: Sensor, Interface, Controller and Actuator. We not only investigate the three major problems about current systems (reconstruction of fire situations, effective slaking the fire and promoting system’s stability) but also present a structure of an ideal intelligent fire detection system. After discussing the problems of the current system with respect to the three major problems, we utilize power line transmit networks to integrate the fire detection system and Home Automation to realize the aforementioned improving ideas with respective to the three major problems in real systems.
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Madeira, Ana Abrantes de Abreu. "Intelligent System for Fire Detection." Master's thesis, 2020. http://hdl.handle.net/10316/92216.
Full textAbstract:
Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e TecnologiaA detecção de um incêndio na sua fase inicial pode mitigar amplamente as suas consequências. Com os desenvolvimentos na área da tecnologia de captura de imagens e a consequente melhoria da qualidade das imagens obtidas, torna-se hoje em dia possível o desenvolvimento de sistemas de identificação visual de incêndios. O presente trabalho apresenta um sistema inteligente de reconhecimento de fumo e fogo que pode ser aplicado a imagens capturadas por câmaras de smartphones. Este sistema destina-se a ser integrado numa aplicação que permitirá reportar incêndios por meio de dados crowdsourced. No âmbito do desenvolvimento do sistema, diferentes técnicas de deep learning para classificação de imagens e detecção de objetos foram implementadas e testadas, considerando duas abordagens distintas de reconhecimento de objetos de imagem: classificação de imagens e detecção de objetos. As fases de treino e avaliação dos modelos são também documentadas no presente trabalho, assim como todas as etapas de pré e pós-processamento consideradas. Para o desenvolvimento das diferentes abordagens de detecção de objetos e classificação de imagens, são propostos diferentes datasets para o treino e avaliação dos modelos ResNet e YOLO, específicos para o problema de reconhecimento de fumo e fogo em imagens. Destacam-se os datasets anotados propostos para treino e teste de modelos YOLO, que podem ser usados em futuros projetos de deteção de fumo e fogo. O sistema proposto apresenta resultados promissores para a detecção de objetos das classes Fire e Smoke em imagens estáticas. Com a abordagem de detecção proposta, é também possível obter bons resultados na classificação das imagens, atribuindo uma classe a cada imagem com base nos objetos detectados, através do método de pós-processamento proposto.
The early detection of a fire can largely mitigate its harmful consequences. With the developments in the area of image capture technology and the consequent improvement in image quality, it is now possible to develop systems for visual identification of fire indicators. The present work presents an intelligent fire and smoke recognition system that can be applied to images captured by smartphone cameras. This system is to be integrated into an application that will allow the reporting of fires using crowdsourced data.Different deep learning techniques for image classification and object detection were implemented and tested, considering two distinct image object recognition approaches: image classification and object detection. The models' training and evaluation phases are documented in the present thesis as well as all the pre-processing and post-processing steps that were taken into account. As part of the development of fire detection and classification approaches, different datasets are proposed to train and evaluate ResNet and YOLO models, specific to the fire and smoke recognition problem. The proposed annotated datasets for YOLO models stand out, which can be used in future smoke and fire detection projects. The proposed system presents promising results for detecting objects of the Fire and Smoke classes in still images. With the proposed detection approach, it is also possible to obtain good results for image classification, assigning a class to each image based on the detected objects with the proposed post-processing method.
Outro - FCT - FireLoc
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Chiou, You-huei, and 邱宥惠. "Fire Detection Based on Acoustic Signals." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/64176362587494957900.
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碩士國立雲林科技大學
機械工程系碩士班
101
A real-time machine acoustic based day and night time fire detection method that can be incorporated with a automatic suppression system for early fire detection is proposed by this work. Sound waves generated by the pulsation of flame influence the density of air to form the longitudinal wave, and continue until the fire flame disappeared. The fire could be detected by means of measuring acoustic signal and recognized with the sonogram under various indoor burning conditions. In this work, an acoustic signal process is proposed which used a circuit to filter the high frequency signal to reduce the interference of measurement, and amplify the amplitude of the signals of fire burning. By using a standard sound source to make sure the measured range of the frequency of electric circuit. Detect the fire through audio and video signals in the same time, to prove the reliability of the detection system, experimental results show that the proposed fire detection based on acoustic signals system is successfully detecting the fire frequency . Keywords : Condenser microphone, audio signals, signal process, fire frequency.
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WU, JIA-CHIENG, and 吳嘉乾. "Dynamic Fire Detection and Escaping Motion Planning." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/58611367028623623685.
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碩士國立雲林科技大學
電機工程系
104
The thesis designed a modular based mobile robot with the microchip STC12C5A60S2 as the core and embedded flame sensing module, a gas sensing module, an encoder module, an RF wireless module, three infrared obstacle avoidance modules, and a Bluetooth module are cooperated to establish the overall robot system. The robot system can detect dangerous area and program the escaping motion routes. Waypoint navigation algorithm is used to the escaping motion planning, The proposed algorithm is based on the value of Bluetooth RSSI to achieve indoor positioning. Keywords: modular based mobile robot, dynamic fire detection, escaping motion programing
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"Computer vision based embedded fire detection system." 2011. http://library.cuhk.edu.hk/record=b5894610.
Full textAbstract:
Gong, Yibo.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.
Includes bibliographical references (p. 99-108).
Abstracts in English and Chinese.
Abstract --- p.ii
Acknowledgement --- p.v
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Motivation and Objective --- p.1
Chapter 1.2 --- Contributions --- p.4
Chapter 1.2.1 --- Embedded fire detection platform --- p.4
Chapter 1.2.2 --- Extended CAMSHIFT object detection frame work --- p.5
Chapter 1.2.3 --- Cooperative multiple camera module --- p.8
Chapter 1.2.4 --- Aerial maritime survivor detection system --- p.9
Chapter 1.3 --- Organization of this thesis --- p.9
Chapter 2 --- Background Study --- p.11
Chapter 2.1 --- Embedded computer vision --- p.11
Chapter 2.2 --- Visual Fire detection --- p.12
Chapter 2.3 --- Color-based object detection and tracking --- p.15
Chapter 2.4 --- Multiple-camera system cooperation --- p.16
Chapter 2.5 --- Multiple-camera system calibration --- p.18
Chapter 3 --- Overview of the embedded fire detection system --- p.22
Chapter 3.1 --- Functional modules of the detection unit --- p.25
Chapter 3.2 --- Dataflow within the detection unit --- p.28
Chapter 4 --- Simulated annealing based MEAN SHIFT framework --- p.31
Chapter 4.1 --- Simulated annealing framework --- p.33
Chapter 4.2 --- Combination of simulated annealing with MEAN SHIFT --- p.37
Chapter 5 --- Extended CAMSHIFT framework for fire detection --- p.42
Chapter 5.1 --- Bidirectional color histogram training and backprojection --- p.43
Chapter 5.2 --- Choice of properly sized fire window --- p.48
Chapter 5.3 --- Alternative optimization based search window resizing --- p.49
Chapter 5.4 --- Multiple modal particle filter based window size optimization --- p.53
Chapter 5.4.1 --- Multiple modal particle filter --- p.53
Chapter 5.4.2 --- Integration of the MMPF with CAMSHIFT framework --- p.57
Chapter 5.5 --- fire monitoring --- p.63
Chapter 6 --- The multiple camera module --- p.65
Chapter 6.1 --- Calibration of the multi-camera system --- p.66
Chapter 6.2 --- Region mapping and cooperation among the cameras --- p.69
Chapter 7 --- Implementation and Experiments --- p.71
Chapter 7.1 --- Implementation --- p.71
Chapter 7.2 --- Experiments and performance evaluations --- p.74
Chapter 7.2.1 --- Bidirectional histogram training and backprojection --- p.76
Chapter 7.2.2 --- Performance of the hybrid Simulated annealing-Mean shift framework --- p.78
Chapter 7.2.3 --- Alternative optimization based search window resizing for CAMSHIFT --- p.84
Chapter 7.2.4 --- Multiple modal particle filter based search window resizing for CAMSHIFT --- p.87
Chapter 7.2.5 --- Real-scenario test on the arm system --- p.94
Chapter 7.2.6 --- Comparison of the two search window resizing mechanisms --- p.96
Chapter 7.2.7 --- Accuracy of the multiple camera calibration method --- p.97
Chapter 8 --- Extension to aerial maritime survivor search --- p.99
Chapter 8.1 --- Introduction --- p.99
Chapter 8.2 --- Implementation and experiment results --- p.102
Chapter 9 --- Conclusion --- p.105
Chapter 9.1 --- Contribution and summary of the work --- p.105
Chapter 9.2 --- Future work --- p.107
Bibliography --- p.109
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Chung, Chi-Hung, and 張吉弘. "Video-based Fire and Smoke Detection System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/06965426742936856902.
Full textAbstract:
碩士國立暨南國際大學
資訊工程學系
102
Along with the progress of computer technology, sophisticated image processing/understanding methods have developed and the application of intelligent video surveillance system are becoming more and more popular. In this thesis, we use image processing techniques to analyze image features of flame and smoke. The image features are then used to develop a video-based fire and smoke detection system. The proposed system consists of the fire detection module and the smoke detection module. In the fire detection module, we first detect foreground objects with a proper background model. Then, three pre-trained fire color look up tables, an LDA model, the standard deviation of the G-channel, an evaluated flame risk value are used to detect flame in video. In the smoke detection module, we use dark channel analysis to extract suspicious blurry regions from video. Also, we use wavelet analysis to determine whether the high frequency image energy is reducing. Then, smoke candidate regions are computed and are tracked to examine if the area of any of them keeps growing. When the area of a smoke candidate is increasing, it is determined to be a smoke region. Experimental results show that, when the input video resolution is 640×480, the fire and smoke detection speed is 100 frames/sec., and the recognition accuracy is about 92%.
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Hsieh, Tung-Che, and 謝東哲. "Vision-based Fire Detection Using Video Sequences." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/58978643743496088213.
Full textAbstract:
碩士中原大學
通訊工程碩士學位學程
102
Fire, if improperly used, could pose great threats to peoples’ security, life, and property. Motivated by the requirement to detect fire at its early stage, we aimed to develop an automatic system for vision-based fire detection using video sequences. Our system included four major steps, namely image preprocessing, foreground region analysis, fire dynamic behavior analysis, and fire flow energy analysis. Overall, our system could achieve the detection rates of over 91% in either indoor or outdoor environments. In addition, our system could achieve the system response time within 1 second (average delay of ~25 frames) once the fire occurred. In summary, our system could be used in surveillance systems, leading to prevent damage to peoples’ security, life, and property.
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CHEN, HUNG-JUNG, and 陳宏榮. "Fire Detection Based on Feature of Corner." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/2d47s4.
Full textAbstract:
碩士開南大學
資訊學院碩士在職專班
106
The purpose of this study is to study the detection of forest fire detection in the field of fire, hoping to use digital image video recognition method, which can be used in fire detection and prevention system in the future. At present, according to statistics from the Fire Department of the Ministry of the Interior over the years, the number of fires occurring in buildings exceeds 75% of the total number of occurrences. Therefore, due to factors such as market size and population density, System is more mature, manufacturers have developed related equipment and systems also have more options. Types are broadly divided into the flame temperature of the use of temperature-sensitive, flame-sensitive light type, flame smoke and flame gas chemical composition of the gas-type flame detector of different characteristics, to detect the fire. This paper focuses on fire detection in the forest field, considering the use of digital image processing methods to detect flames. Many researchers have put forward the relevant algorithms, such as support vector machine, wavelet analysis, Gaussian mixture model, KFM, particle swarm optimization and so on, using the digital image processing method of flame detection. This study attempts to use digital images Corner detection method of edge detection, and K-mean clustering algorithm, regional growing method, background subtraction method to improve the accuracy of corner detection, and remove the number of false corners.
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Lin, Pa-Hsun, and 林伯勳. "Fire and Smoke Detection Using Random Forest Algorithm." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/56813956821976269774.
Full textAbstract:
碩士國立暨南國際大學
資訊工程學系
101
Along with the progress of computer computation capabilities, sophisticated image processing/understanding methods have been developed and the functions of intelligent video surveillance systems have been greatly extended. In this thesis, we develop a video-based fire and smoke detection system based on the random forest algorithm. We use the distinct color and image variation properties of fire/smoke to select candidate regions. Then, image features of texture and motion patterns of the candidate regions are analyzed to determine any fire/smoke region. We propose to extract the features of both the texture and motion patterns of the fire/smoke with the local binary pattern (LBP) method. The random forest method is augmented to use the LBP features for fire/smoke detection to reduce false positive and enhance the fire and smoke detection rate.
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Wang, Jhen-yuan, and 王貞元. "Fire detection and region location in surveillance image." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/77373790782982673723.
Full textAbstract:
碩士國立臺灣科技大學
電機工程系
96
The fire accident causes economical damage as well as endangering the life of people, so a set of good system of fire detection is necessary. In this thesis, we will combine traditional image process in fire detection and relation of the variation of saturation for flame to deal with fire recognition and fire location. It deals with procedure as follows. First, extraction of the fire pixels in image, and to analyze the region from fire pixels, to label the saturation for fire region by the property of saturation for flame, recognition of fire and orientation of fire location.
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Siao, Chi-Wei, and 蕭積蔚. "Using Data Fusion in a Fire Detection System." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/54280163790518138400.
Full textAbstract:
碩士國立雲林科技大學
電機工程系
103
In modern society, while the usage of natural resources such as fire and electricity has become more and more widespread, fire accidents occur more often than ever, leading to a larger scale of damage and loss of lives. Therefore, it is essential to detect fire accidents and notify people immediately of yet correctly. When it comes to the traditional fire sensor, a physical limitation is its susceptibility to be influenced and affected by surrounding environment, which results in false alarms or even malfunctions. As a remedy, this thesis presents the implementation of a fire detection system that operates based on the Dempster-Shafer theory allowing for multi-sensor data fusion. Our development designates the Arduino microcontroller to measure and interpret the readings from three types of sensors: temperature, light and gas. All the readings are normalized to a moderate range of values for reasoning purposes and then transmitted to the backend Raspberry Pi over the wireless medium for subsequent inference processing. In our architecture, the Raspberry Pi is tasked to deduce the probability of fire accident occurrences in light of Demspter-Schaffer’s theory. Deduction also evaluates a conflict coefficient (Kconflict) as a pivotal parameter to validate the misbelief of our deduction results. Conflict coefficient is of utility to reduce false alarms or possible malfunctions of our system. Further, we have deployed a web server with a MySQL database as well, so as to interact with the Raspberry Pi for keeping necessary data in storage for future reference. In addition, our system offers three notification services. First, a web page is maintained to clearly display the system’s operation details. Second, an application enables the smartphone user to check the operational status of our system online anytime as long as there is accessibility to the Internet. Third, a messaging service informs the user of emergent events in real-time over SMS whenever necessary. We validate our development by field tests to collect realistic statistics. Experiments are conducted in a controllable, safe environment by emulating fire happening in daytime and nighttime, respectively. Each experiment undergoes three phases: no-fire, on fire, and post-fire situations. We are concerned with the detection sensitivity versus accuracy of real fire accidents. Experimental results show that, when Kconflict is set to 0.8, the accuracy of our implementation in no-fire and on-fire circumstances during daytime reaches 98% and the accuracy during nighttime amounts to 97%. When taking all the three phases into account, the accuracy during daytime and nighttime turns out to be 97% and 89%, respectively. Field tests ensure the effectiveness of our implementation, implying its practical use in real life.
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CiWeiLin and 林奇緯. "Gas-type fire detection and immediate notification system." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/36970417874955704282.
Full textAbstract:
碩士國立勤益科技大學
電子工程系
103
Fires are difficult to avoid, so if fast or immediately fled the scene of the fire the fire scene for emergency fire fighting process, to increase the chances of survival of the people and reduce the loss of finance. Occurred during each field of fire, will go through growing, exuberant and recession of the flame, therefore certain combustible substance has a close relationship. And the vast majority of the combustible substances, both containing carbon (C), hydrogen (H) element, because in the combustion process, the carbon, hydrogen and oxygen (O2) do engage, will produce products of incomplete combustion, such as carbon dioxide ( CO2), and incomplete combustion products such as carbon monoxide (CO) and other toxic gases. It can be seen, carbon dioxide and carbon monoxide during combustion flame is the material inevitably produce, so if in front of flame into the strong (the fire), the use of modern gas sensor technology (Nondispersive Infrared Detector, NDIR) for carbon dioxide and go carbon monoxide do synchronous analysis possibilities warning fires, and then with, under the concept of modern society to have one, and make the most rapid notified via App of the system, so that people make an immediate response to avoid greater losses .
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Teixeira, João Gilberto Fernandes Gonçalves. "Wireless Sensor Network for Forest Fire Detection 2." Master's thesis, 2017. https://repositorio-aberto.up.pt/handle/10216/105593.
Full textAbstract:
The main purpose for this project is the development of a semi-autonomous wireless sensor network for fire detection in remote territory. Making use of the IEEE 802.15.4 standard, a wireless standard for low-power, low-rate wireless sensor networks, a real sensor network and web application will be developed and deployed with the ability to monitor sensor data, detect a fire occurrence and generate early fire alerts.
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Oliveira, Guilherme de Castro. "Mock Testing Framework for a Fire Detection System." Master's thesis, 2021. https://hdl.handle.net/10216/139021.
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Wu, Jin-Rong, and 吳晉榮. "Wavelet Based Fire and Smoke Detection In Video." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/13941578222494412004.
Full textAbstract:
碩士義守大學
資訊工程學系碩士班
98
In order to detect fire and smoke in the open space, this paper integration the same properties of the flame and smoke to detect whether an open space in the presence of fire and smoke. First, detection image if there are moving objects, then use the color of flame and the chrominance value change in background image caused by smoke to analysis the move region. The third and fourth step are used the frequency to analysis the boundaries and flicker or oscillations in a pixel due to fire and smoke. The last step is using the boundaries properties of fire and smoke to reduce the false positives. Final combined the results of all steps to determine whether the video presence fire and smoke. Because of using the above methods to detect fire and smoke will cause the false alarm rate is too high, at the end of this paper suggested several ways to improve the false alarm rate. Including improve the threshold of moving objects detection method and improve the time frequency identification methods and using the different methods to determine the contours of smoke.
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Li, Mu-Chien, and 李牧謙. "Apply wireless sensor network on fire detection system." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/43353451777279969326.
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碩士國立屏東商業技術學院
資訊工程系(所)
99
This paper proposed the idea that to installing the sensor network for fire detection in the metropolitan building. The sensor nodes control the lighting lamplight by the little computing ability in the scene of a fire. The lamplight help the people to flee from the fire. Even the sensor nodes send the fire situation to fire bureau for relieving the victims of fire by Internet. In this paper, we propose a method to apply the wireless sensor network in the urban environment. First, we use the sensor network nodes to be a combination of sockets, and then nodes not only can use the power in building to maintain operation, but also can use sockets are distributed in building to form uniform and dense sensor coverage. In this environment, we use wireless sensor network sensing and transport functions as the core to construct the fire detection system.