Bibliografías temáticas / Real- Time Wildlife Monitoring

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Literatura académica sobre el tema "Real- Time Wildlife Monitoring"

Autor: Grafiati
Publicado: 7 de junio de 2025
Última modificación: 2 de agosto de 2025

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Artículos de revistas sobre el tema "Real- Time Wildlife Monitoring"

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Jagannathan, Preetha, Kalaivanan Saravanan, Subramaniyam Deepajothi, and Sharmila Vadivel. "Federated Learning and Blockchain-Based Collaborative Framework for Real-Time Wild Life Monitoring." Cybernetics and Information Technologies 25, no. 1 (2025): 19–35. https://doi.org/10.2478/cait-2025-0002.

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Abstract Effective wildlife monitoring in hilly and rural areas can protect communities and diminish human-wildlife conflicts. A collaborative framework may overcome challenges like inadequate data integrity and security, declining detection accuracy over time, and delays in critical decision-making. The proposed study aims to develop a real-time wildlife monitoring framework using Federated Learning and blockchain to improve conservation strategies. Min-max normalization enhances training data and Elastic Weight Consolidation (EWC) for real-time adaptation. The improvised YOLOv8+EWC enables r
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Ma, Zhibin, Yanqi Dong, Yi Xia, Delong Xu, Fu Xu, and Feixiang Chen. "Wildlife Real-Time Detection in Complex Forest Scenes Based on YOLOv5s Deep Learning Network." Remote Sensing 16, no. 8 (2024): 1350. http://dx.doi.org/10.3390/rs16081350.

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With the progressively deteriorating global ecological environment and the gradual escalation of human activities, the survival of wildlife has been severely impacted. Hence, a rapid, precise, and reliable method for detecting wildlife holds immense significance in safeguarding their existence and monitoring their status. However, due to the rare and concealed nature of wildlife activities, the existing wildlife detection methods face limitations in efficiently extracting features during real-time monitoring in complex forest environments. These models exhibit drawbacks such as slow speed and
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Gaikwad, Dr Jitendra. "ML Based WildLife Trap Camera System." International Journal for Research in Applied Science and Engineering Technology 12, no. 11 (2024): 2037–40. http://dx.doi.org/10.22214/ijraset.2024.65557.

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This paper presents a real-time wildlife species classification system leveraging Convolutional Neural Networks (CNNs). The system classifies wildlife images from the Oregon Wildlife dataset and extends its functionality to process live video feeds for species recognition. Using PyTorch and OpenCV, the model achieves robust accuracy on a balanced dataset and demonstrates real-time inference capabilities, making it a potential tool for wildlife monitoring and conservation efforts.
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Wall, Jake, George Wittemyer, Brian Klinkenberg, and Iain Douglas-Hamilton. "Novel opportunities for wildlife conservation and research with real-time monitoring." Ecological Applications 24, no. 4 (2014): 593–601. http://dx.doi.org/10.1890/13-1971.1.

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Anitha Bujunuru, Nanam Shiva Kumar, Pedimalla Nishwanth, and Mylaram Manoj Kumar. "Real-Time Zigbee Sensor Network for Forest Monitoring and Wildlife Conservation." International Journal of Latest Technology in Engineering Management & Applied Science 14, no. 5 (2025): 423–26. https://doi.org/10.51583/ijltemas.2025.140500043.

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Abstract Tree smuggling, especially of high-value species like sandalwood and teak, poses a significant threat to biodiversity and forest ecosystems. These trees are highly sought after for their commercial value, making them frequent targets of illegal logging operations. This illicit activity not only depletes valuable natural resources but also contributes to deforestation and environmental degradation. In response to this growing concern, an IoT-based monitoring system has been developed to detect and prevent such activities. At the core of the system is a Node MCU microcontroller, integra
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THOMAS, SHINEY, George Elsa, Francis Alphonsa, Job Anna, and Maria James Ann. "Wildlife Detection And Recognition Using YOLO V8." International Journal on Emerging Research Areas (IJERA) 04, no. 02 (2025): 81–87. https://doi.org/10.5281/zenodo.14714518.

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The use of YOLOv8 for wildlife detection and recognition has transformed real-time monitoring across diverse environments, particularly in rural, forested, and human-wildlife conflict zones. Its lightweight architecture, efficient feature extraction, and deep learning capabilities make it a preferred tool for wildlife conservation. YOLOv8’s ability to detect and classify animals in real-time has enhanced wildlife population monitoring, reduced risks of human-wildlife encounters, and contributed to biodiversity conservation. A major advancement in YOLOv8 is its ability to perform well und
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A, Ajay. "Intelligent Habitat Surveillance and Protection System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48814.

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Abstract— As mortal-wildlife commerce grows further frequent, and wildlife territories face adding environmental pressures, covering beast get has come pivotal for conservation sweats and ecological exploration. This paper presents an AI-driven Wildlife behavior Monitoring System using computer vision, deep literacy, and YOLOv8 to descry, classify, and dissect wildlife conditioning in real-time. The proposed system directly identifies species and tracks actions similar to feeding, movement, resting, and social relations across different territories. It provides detailed receptivity through spa
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Mangewa, Lazaro J., Patrick A. Ndakidemi, and Linus K. Munishi. "Integrating UAV Technology in an Ecological Monitoring System for Community Wildlife Management Areas in Tanzania." Sustainability 11, no. 21 (2019): 6116. http://dx.doi.org/10.3390/su11216116.

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Unmanned aerial vehicles (UAV) have recently emerged as a new remote sensing aerial platform, and they are seemingly advancing real-time data generation. Nonetheless, considerable uncertainties remain in the extent to which wildlife managers can integrate UAVs into ecological monitoring systems for wildlife and their habitats. In this review, we discuss the recent progress and gaps in UAV use in wildlife conservation and management. The review notes that there is scanty information on UAV use in ecological monitoring of medium-to-large mammals found in groups in heterogeneous habitats. We also
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P, Dr Srinivas Babu. "Implementation of Amphibious Robot for Wildlife Monitoring." International Journal for Research in Applied Science and Engineering Technology 12, no. 12 (2024): 2280–85. https://doi.org/10.22214/ijraset.2024.66202.

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This paper presents an amphibious robot designed for wildlife surveillance on land and environmental monitoring across both land and water. The system incorporates AI-driven technologies and integrated sensors for real-time data collection, including water quality parameters such as turbidity, TDS, and pH. Equipped with advanced surveillance capabilities and geofencing for boundary detection, the robot navigates autonomously in challenging terrains. Solar-powered operation ensures sustainability and cost efficiency. This innovative tool supports ecosystem health assessment and aids in environm
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Renuka Moharir, Srushti Khiratkar, Arati Jadhao, Shruti Khaire, and Dr. Amit Welekar. "Real-Time Tiger Detection Using Ml and Sensor Integration for Village Protection." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 03 (2025): 1042–46. https://doi.org/10.47392/irjaeh.2025.0148.

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In this research, we addressed the critical issue of human-wildlife conflict, focusing on tigers entering villages near forested regions. Such incidents endanger human lives and livelihoods while also threatening wildlife conservation efforts. To mitigate this, we developed an Automated Tiger Detection System integrating motion sensors, ultrasonic sensors, thermal cameras, and machine learning algorithms. This system detects tiger presence in real time and sends alerts to villagers and authorities, enabling swift preventive action. We first discussed the limitations of traditional monitoring m
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Tesis sobre el tema "Real- Time Wildlife Monitoring"

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Drummond, John J. "Real-time event execution monitoring." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1997. http://handle.dtic.mil/100.2/ADA341536.

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Thesis (M.S. in Software Engineering) Naval Postgraduate School, September. 1997.<br>"September 1997." Thesis advisor(s): Man-Tak Shing, Valdis Berzins. Includes bibliographical references (p. 131). Also available online.
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Kudlacek, Ondrej. "Real Time Plasma State Monitoring." Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3424518.

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The thesis describes several methods of plasma state monitoring for feedback control. For a tokamak device operation, one needs to gain in real time some information about the plasma state. The amount of needed information increases with the size of the device. In small machines, such as ISTTOK and Golem, the plasma current centroid position control is sufficient, as the heat fluxes are low and the plasma is in limiter regime. In larger devices, like RFX-mod, TCV or ASDEX-Upgrade with more complex plasma shapes and higher heat fluxes on the first wall, it is necessary to measure and control th
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Banovic, Vladimir. "Real-Time Monitoring of Neurovascular Cells." Thesis, KTH, Mikro- och nanosystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231847.

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Organs-on-a-chip devices are perfused cell culture systems aimed at creating the minimal functional unit of an organ - suchas the neurovascular unit (NVU) of the brain. NVU-on-a-chip platforms can provide an effective framework for studyingcentral nervous system physiology, disease etiology and provide a mean for drug development.In this work, we investigated the possibility of developing NVU-on-a-chip devices, with real-time sensing capabilitiesof glucose - intended for monitoring the metabolic activity of neurovascular cells. This was done by evaluating theperformance and applicability of in
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Blixt, Fanny. "Real-time auto-test monitoring system." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85824.

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At Marginalen Bank, there are several microservices containing endpoints that are covered bytest automation. The documentation of which microservices and endpoints that are covered byautomated tests is currently done manually and is proven to contain mistakes. In the documentation, the test coverage for all microservices together and for every individual microserviceis presented. Marginalen Bank needs a way to automate this process with a system that cantake care of test coverage documentation and present the calculated data. Therefore, the purpose of this research is to find a way to create a
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O'Brien, Robert Philip. "Embedded System Design for Real-time Monitoring of Solitary Embedded System Design for Real-time Monitoring of Solitary." Scholar Commons, 2015. https://scholarcommons.usf.edu/etd/5546.

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Alzheimer's disease and other forms of dementia cause cognitive disabilities in the afflicted person. As a result, the person with dementia often requires assistance from a primary caregiver. However, while the caregiver is away from the home they are unaware of the person's status and may not be able to find out without returning to the home due to dementia's effects on cognition. In this thesis work, a system of embedded devices is presented which tracks a solitary dementia patient in the home in real-time. The system is composed of three main hardware components. Multiple passive and active
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Nilsson, Holmgren Sebastian. "Real-Time Test Oracles using Event Monitoring." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-952.

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<p>To gain confidence in that a dynamic real-time system behaves correctly, we test it. Automated verification & validation can be used to conduct testing of such systems in an effective and economic way.</p><p>An event monitor can be used as a part of a test oracle to monitor the system that is being tested. The test oracle could use the data (i.e., the streams of events) derived from the tested system, to determine if an executed test case gave a positive or negative result. To do this, the test oracle compares the streams of events received from the event monitor with the event expressions
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Singh-Levett, Ishan. "Real-time integral based structural health monitoring." Thesis, University of Canterbury. Mechanical Engineering, 2006. http://hdl.handle.net/10092/1171.

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Structural Health Monitoring (SHM) is a means of identifying damage from the structural response to environmental loads. Real-time SHM offers rapid assessment of structural safety by owners and civil defense authorities enabling more optimal response to major events. This research presents an real-time, convex, integral-based SHM methods for seismic events that use only acceleration measurements and infrequently measured displacements, and a non-linear baseline model including hysteretic dynamics and permanent deformation. The method thus identifies time-varying pre-yield and post-yield
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Tang, Xiaoxi. "Novel remote ECG real-time monitoring system /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?CSED%202009%20TANG.

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Verulkar, Shubhangi M., and Maruti Limkar. "Real Time Health Monitoring Using GPRS Technology." IJCSN Journal, 2012. http://hdl.handle.net/10150/229011.

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The concept of the project taken from Telemedicine. It is a rapidly developing application of clinical medicine where medical information is transferred through interactive audiovisual media for the purpose of consulting, and sometimes remote medical procedures or examinations. Telemedicine may be as simple as two health professionals discussing a case over the telephone, or as complex as using satellite technology and videoconferencing equipment to conduct a real-time consultation between medical specialists in two different countries. Telemedicine generally refers to the use of c
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Törnqvist, Sebastian, and Henrik Westerberg. "Tablespoon - real-time system metric monitoring for Karamel." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-206118.

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System resource utilisation metrics is an important source of the decisionmaking process for a general-purpose auto-scaling solution in cloud computing. It is critical for a monitoring system to be light-weight in its usage of system resources. In this work, Tablespoon, a real-time monitoring system, is presented. It operates on a publish-subscribe architecture and is agent push-based. Tablespoon itself has a low bandwidth usage profile by using agent-side filtering and an inter-group aggregation mechanism. Our solution ensures that requested events are received at most once by the subscriber,
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Libros sobre el tema "Real- Time Wildlife Monitoring"

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Real-time water-quality monitoring for protection of wildlife at Quivira National Wildlife Refuge, south-central Kansas. U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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Christensen, Victoria G. Characterization of surface-water quality based on real-time monitoring and regression analysis, Quivira National Wildlife Refuge, south-central Kansas, December 1998 through June 2001. U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Drummond, John J. Real-time event execution monitoring. Naval Postgraduate School, 1997.

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Capítulos de libros sobre el tema "Real- Time Wildlife Monitoring"

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Acevedo, Miguel F. "Wildlife Monitoring." In Real-Time Environmental Monitoring, 2nd ed. CRC Press, 2023. http://dx.doi.org/10.1201/9781003184362-14.

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Acevedo, Miguel F. "Wildlife Monitoring." In Real-Time Environmental Monitoring, 2nd ed. CRC Press, 2023. http://dx.doi.org/10.1201/9781003425496-14.

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Choiński, Mateusz, Mateusz Rogowski, Piotr Tynecki, Dries P. J. Kuijper, Marcin Churski, and Jakub W. Bubnicki. "A First Step Towards Automated Species Recognition from Camera Trap Images of Mammals Using AI in a European Temperate Forest." In Computer Information Systems and Industrial Management. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84340-3_24.

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AbstractCamera traps are used worldwide to monitor wildlife. Despite the increasing availability of Deep Learning (DL) models, the effective usage of this technology to support wildlife monitoring is limited. This is mainly due to the complexity of DL technology and high computing requirements. This paper presents the implementation of the light-weight and state-of-the-art YOLOv5 architecture for automated labeling of camera trap images of mammals in the Białowieża Forest (BF), Poland. The camera trapping data were organized and harmonized using TRAPPER software, an open-source application for
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Acevedo, Miguel F. "Water Monitoring." In Real-Time Environmental Monitoring, 2nd ed. CRC Press, 2023. http://dx.doi.org/10.1201/9781003184362-12.

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Acevedo, Miguel F. "Atmospheric Monitoring." In Real-Time Environmental Monitoring, 2nd ed. CRC Press, 2023. http://dx.doi.org/10.1201/9781003184362-11.

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Acevedo, Miguel F. "Water Monitoring." In Real-Time Environmental Monitoring, 2nd ed. CRC Press, 2023. http://dx.doi.org/10.1201/9781003425496-12.

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Acevedo, Miguel F. "Atmospheric Monitoring." In Real-Time Environmental Monitoring, 2nd ed. CRC Press, 2023. http://dx.doi.org/10.1201/9781003425496-11.

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Kezunovic, Mladen, Sakis Meliopoulos, Vaithianathan Venkatasubramanian, and Vijay Vittal. "Real Time Stability Monitoring." In Power Electronics and Power Systems. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06218-1_3.

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Grave, Riccardo Dalle, and Simona Calugi. "Real-time self-monitoring." In A Young Person’s Guide to Cognitive Behavioural Therapy for Eating Disorders. Routledge, 2023. http://dx.doi.org/10.4324/9781003342489-11.

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Colombo, Christian, and Gordon J. Pace. "Monitoring Real-Time Properties." In Runtime Verification. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09268-8_10.

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Actas de conferencias sobre el tema "Real- Time Wildlife Monitoring"

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Anand, K., Srimathi G, and Srimathy R. "Integrated Wildlife Monitoring System for Real-Time Anti-Poaching and Conservation." In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910594.

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Saravanan, S., J. Relin Francis Raj, G. Vinoth Rajkumar, C. Antony Vasantha Kumar, N. Soundiraraj, and K. Bharathi. "Deploying Faster R-CNN for Real-Time Tiger Monitoring in Wildlife Conservation." In 2024 3rd International Conference on Automation, Computing and Renewable Systems (ICACRS). IEEE, 2024. https://doi.org/10.1109/icacrs62842.2024.10841726.

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Dasari, Kalyankumar, Mohmad Ahmed Ali, Shankara N.B, K. Deepthi Reddy, M. Bhavsingh, and K. Samunnisa. "A Novel IoT-Driven Model for Real-Time Urban Wildlife Health and Safety Monitoring in Smart Cities." In 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE, 2024. http://dx.doi.org/10.1109/i-smac61858.2024.10714601.

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Mughal, Abdul Basit, Javiriya Hameed Arian, Syed Mohsin Shah, Syed Mujtaba Haider, and Rafi Ullah Khan. "Real-Time Wildlife Tracking with Fine-Tuned YOLOv11." In 2025 2nd International Conference on Trends in Engineering Systems and Technologies (ICTEST). IEEE, 2025. https://doi.org/10.1109/ictest64710.2025.11042292.

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Govardhan, Mangalapuri, Maddiboina Naga Lavanya, Kanchana Gari Chandu Reddy, ATA Kishore Kumar, and Kanala Koushik Reddy. "Real-Time Wildlife Tracking and Anomaly Detection Using YOLOv8." In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910740.

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Kumari, Y. Sowjanya, Gottumukkala Vijaya Spandana, and M. Senthil. "Real-Time Wildlife Behavior Alerts with Hybrid DL Approaches." In 2025 6th International Conference on Recent Advances in Information Technology (RAIT). IEEE, 2025. https://doi.org/10.1109/rait65068.2025.11089465.

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M, Inbamalar T., Abirami S, Akshhaya S, Aparnaa C. A, and Archana T. "Real Time AI-Based Wildlife Detection and Deterrent System for Farmland Protection." In 2025 6th International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE, 2025. https://doi.org/10.1109/icirca65293.2025.11089914.

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Brown, Gerald K., J. R. Davies, and B. J. Hemblade. "Real Time Metal Loss Internal Monitoring." In CORROSION 2000. NACE International, 2000. https://doi.org/10.5006/c2000-00278.

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Abstract Internal Corrosion Monitoring over the last few decades has relied upon the 5 basic techniques. Little improvement in performance has been achieved. In addition many of the newer internal corrosion monitoring techniques have proved of little value in the field although some of them have instances of success in the laboratory. Industry has many high value hydrocarbon applications requiring corrosion rate monitoring for realtime problem solving and control. The high value of assets and the cost of asset replacement makes it necessary to practice cost effective process and corrosion cont
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Chang, G., M. Chevitarese, S. Kramer, et al. "SEABIRD: System for Environmental Assessment of Bird/Bat Interactions with Real-Time Detection." In Offshore Technology Conference. OTC, 2024. http://dx.doi.org/10.4043/35220-ms.

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A cadre of environmental regulations and the associated permits and authorizations require offshore wind (OSW) energy to be planned, constructed, and operated in ways that avoid, minimize, and mitigate environmental impacts, including potential harm to wildlife. Wind energy areas (WEAs) are often rich with birds under protection by the Migratory Bird Treaty Act (MBTA) and some species are also protected by the Endangered Species Act (ESA). Some birds (e.g., albatross, shearwaters, and petrels) may be more vulnerable to collision with OSW turbines because of their reliance on wind-rich areas to
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Bondi, Elizabeth. "AI for Conservation: Aerial Monitoring to Learn and Plan against Illegal Actors." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/825.

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Conservation of our planet’s natural resources is of the utmost importance and requires constant innovation. This project focuses on innovation for one aspect of conservation: the reduction of wildlife poaching. Park rangers patrol parks to decrease poaching by searching for poachers and animal snares left by poachers. Multiple strategies exist to aid in these patrols, including adversary behavior prediction and planning optimal ranger patrol strategies. These research efforts suffer from a key shortcoming: they fail to integrate real-time data, and rely on historical data collected during ran
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Informes sobre el tema "Real- Time Wildlife Monitoring"

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Quinn, Nigel W. T., Jeremy S. Hanlon, Josephine R. Burns, et al. Real-Time Water Quality Monitoring and Habitat Assessment in theSan Luis National Wildlife Refuge. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/862340.

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Bakhtiari, Sasan. Task 1. Monitoring real time materials degradation. NRC extended In-situ and real-time Monitoring. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1252705.

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Aruoba, S. Boragan, and Francis Diebold. Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w15657.

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Harker, Y. D. Real-time monitoring for human clinical trials. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/421337.

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French, Patrick D. Real-time monitoring system for phytoremediation optimization. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/882987.

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Anderson, Lawrence Frederick, and Benjamin W. Clough. Instrumentation development for real time brainwave monitoring. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/883483.

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D'Ambrosio, Bruce. Real-Time Value-Driven Monitoring and Repair. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada260959.

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Rajan Gurjar, Ph D. Development of Real-Time Coal Monitoring Instrument. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/981919.

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Zelepouga, Serguei, and Alexei Saveliev. Real Time Flame Monitoring of Gasifier and Injectors. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1081316.

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Littlefield, Richard J. Real-Time 3D Ultrasound for Physiological Monitoring 22258. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada373262.

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