Literatura científica selecionada sobre o tema "Mobile IR sensor"
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Artigos de revistas sobre o assunto "Mobile IR sensor"
Lim, Jungwook, Jihun Kim, Long Yan, Hyunpil Noh, Seungki Jung, Doosik Seol, Junghyung Pyo et al. "A single chip PPG sensor with enhanced IR sensitivity for low power and small size". Electronic Imaging 2021, n.º 7 (18 de janeiro de 2021): 66–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.7.iss-066.
Texto completo da fonteArtemčiukas, Edgaras, e Leonidas Sakalauskas. "INTEGRATION OF SENSOR ORIENTATION DATA INTO AN AUGMENTED REALITY TECHNOLOGY / JUTIKLIŲ ORIENTACIJOS DUOMENŲ INTEGRACIJA PAPILDYTOSIOS REALYBĖS TECHNOLOGIJOJE". Mokslas – Lietuvos ateitis 6, n.º 2 (24 de abril de 2014): 172–77. http://dx.doi.org/10.3846/mla.2014.24.
Texto completo da fonteLee, Kyunghyun, Sangkyeum Kim e Kwanho You. "Iterative Regression Based Hybrid Localization for Wireless Sensor Networks". Sensors 21, n.º 1 (2 de janeiro de 2021): 257. http://dx.doi.org/10.3390/s21010257.
Texto completo da fonteBaasandorj, Bayanjargal, Aamir Reyaz, Park Joung Ho, Cha Wang Cheol, Deok Jin Lee e Kil To Chong. "A Mobile Robot Obstacle Avoidance Using Fuzzy Logic and Model Predictive Control". Applied Mechanics and Materials 548-549 (abril de 2014): 922–27. http://dx.doi.org/10.4028/www.scientific.net/amm.548-549.922.
Texto completo da fontePatel, Karan. "Operating Electric Equipment with IR Sensor and IOT". International Journal for Research in Applied Science and Engineering Technology 9, n.º VI (20 de junho de 2021): 1935–41. http://dx.doi.org/10.22214/ijraset.2021.35408.
Texto completo da fonteUhm, Taeyoung, Jeongwoo Park, Jungwoo Lee, Gideok Bae, Geonhui Ki e Youngho Choi. "Design of Multimodal Sensor Module for Outdoor Robot Surveillance System". Electronics 11, n.º 14 (15 de julho de 2022): 2214. http://dx.doi.org/10.3390/electronics11142214.
Texto completo da fonteAndreev, V. P. "Obstacle shape determination by mobile robot sensor system using GP2Y0A (Sharp) type IR distance sensors". Power engineering: research, equipment, technology 26, n.º 1 (24 de abril de 2024): 195–207. http://dx.doi.org/10.30724/1998-9903-2024-26-1-195-207.
Texto completo da fonteKurniawan, Aditya, e Kholilatul Wardani. "Kinect Structural Noise Elimination Technique For ITIS Mobile Robot Data Collector". International Journal of Engineering & Technology 7, n.º 4.27 (30 de novembro de 2018): 1. http://dx.doi.org/10.14419/ijet.v7i4.27.22425.
Texto completo da fonteYanmida, Dele Zacheaus, Abubakar Surajo Imam e Sabur Ajibola Alim. "Obstacle Detection and Anti-Collision Robot Using Ultrasonic Sensor". ELEKTRIKA- Journal of Electrical Engineering 22, n.º 1 (28 de abril de 2023): 11–14. http://dx.doi.org/10.11113/elektrika.v22n1.404.
Texto completo da fonteSut, Dhruba Jyoti. "Development of an Autonomous Real Time Collision Avoidance Mobile Robot". International Journal for Research in Applied Science and Engineering Technology 10, n.º 1 (31 de janeiro de 2022): 1700–1705. http://dx.doi.org/10.22214/ijraset.2022.40125.
Texto completo da fonteTeses / dissertações sobre o assunto "Mobile IR sensor"
Gal, Carol. "Multi-sensor (IR) data fusion for mobile robot navigation using occupancy grid method". Thesis, University of Ottawa (Canada), 1994. http://hdl.handle.net/10393/6843.
Texto completo da fonteChakchouk, Mohamed. "Conceptiοn d'un détecteur de système mécatronique mobile intelligent pour observer des molécules en phase gazeuse en ΙR". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMIR06.
Texto completo da fonteThis work anticipates that, in an ever-expanding digital technology world, technological breakthroughs in the analysis of data collected by spectroscopic devices will allow the almost instantaneous identification of known species observed in-situ in a specific environment, leaving the necessary in-depth analysis of unobserved species. The method derived from RBDO (Reliability Based Design Optimization) technology will be used to implement an artificial intelligence procedure to identify observed species from a mobile IR sensor. To successfully analyze the obtained data, it is necessary to appropriately assign molecular species from the observed IR data using appropriate theoretical models. This work focuses on the observation from mobile devices equipped with appropriate sensors, antennas, and electronics to capture and send raw or analyzed data from an interesting IR spectroscopic environment. It is therefore interesting if not essential to focus on symmetry-based theoretical tools for the spectroscopic analysis of molecules, which allows to identify the IR windows to be chosen for observation in the design of the device. Then, by fitting the theoretical spectroscopic parameters to the observed frequencies, the spectrum of a molecular species can be reconstructed. A deconvolution of the observed spectra is necessary before the analysis in terms of intensity, width and line center characterizing a line shape. Therefore, an adequate strategy is needed in the design to include data analysis during the observation phase, which can benefit from an artificial intelligence algorithm to account for differences in the IR spectral signature. In this regard, the analytical power of the instrument data can be improved by using the reliability-based design optimization (RBDO) methodology. Based on the multi-physics behavior of uncertainty propagation in the hierarchical system tree, RBDO uses probabilistic modeling to analyze the deviation from the desired output as feedback parameters to optimize the design in the first place. The goal of this thesis is to address IR observation window parameters to address reliability issues beyond mechatronic design to include species identification through analysis of collected data
Capítulos de livros sobre o assunto "Mobile IR sensor"
Rao, Sudarshana S., e Santosh R. Desai. "Automatic Dent Detection in Automobile Using IR Sensor". In Evolutionary Computing and Mobile Sustainable Networks, 501–11. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9605-3_34.
Texto completo da fonteDarif, Anouar, Chaibi Hasna e Rachid Saadane. "An Energy-Efficient MAC Protocol for Mobile Wireless Sensor Network Based on IR-UWB". In Advances in Intelligent Systems and Computing, 1–12. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76357-6_1.
Texto completo da fonteSekkas, O., S. Hadjiefthymiades e E. Zervas. "Sensor Data Fusion for Location Awareness". In Encyclopedia of Mobile Computing and Commerce, 863–69. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59904-002-8.ch145.
Texto completo da fonteC. G, Mallamma, Varalakshmi B. D, Nagapushpa K. P e Anuradha U. "SMART NAVIGATION ASSISTANCE SYSTEM FOR THE VISUALLY IMPAIRED". In Futuristic Trends in IOT Volume 3 Book 5, 209–26. Iterative International Publisher, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bgio5p2ch4.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Mobile IR sensor"
Park, Hyunwoong, e Sooyong Lee. "Rotating Range Sensor System for Obstacle Detection and Map Building". In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/detc2006-99658.
Texto completo da fonteBishnu, Soham Kanti, Sayantika Chowdhury, Pritam Sarkar, Sanaita Khan, Madhurima Paul, Anamitral Gupta, Puijita Roy, Shayani Samanta e Nibedita Maity. "Heart Rate Monitoring system using IR-photodetector sensor". In 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE, 2018. http://dx.doi.org/10.1109/iemcon.2018.8614884.
Texto completo da fonteWu, Shaohua, Qiaoling Zhang, Qinyu Zhang e Haiping Yao. "Integrative Ranging and Positioning for IR-UWB Wireless Sensor Networks". In 2011 Third International Conference on Communications and Mobile Computing (CMC). IEEE, 2011. http://dx.doi.org/10.1109/cmc.2011.96.
Texto completo da fonteHsu, Hsi-Chou, e Jyh-Horng Wen. "A Low Complexity IR-UWB Receiver for Wireless Sensor Networks". In 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS). IEEE, 2012. http://dx.doi.org/10.1109/imis.2012.95.
Texto completo da fonteXiao, Zhu, Guang-hua Tan, Ren-fa Li e Ke-chu Yi. "A Joint Localization Scheme Based on IR-UWB for Sensor Network". In 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2011. http://dx.doi.org/10.1109/wicom.2011.6040590.
Texto completo da fonteSegura, Marcelo J., Vicente A. Mut e Hector D. Patino. "Mobile robot self-localization system using IR-UWB sensor in indoor environments". In 2009 IEEE International Workshop on Robotic and Sensors Environments (ROSE 2009). IEEE, 2009. http://dx.doi.org/10.1109/rose.2009.5355978.
Texto completo da fonteKarvonen, Heikki, e Leonardo Goratti. "Optimal code rate for wireless sensor networks using IR-UWB and non-coherent detection". In 2010 IEEE 7th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS). IEEE, 2010. http://dx.doi.org/10.1109/mass.2010.5663918.
Texto completo da fontePflug, Hans W., Jos Oudenhoven, Nauman F. Kiyani, Johan H. C. van den Heuvel, Kathleen Philips e Harmke de Groot. "Zinc-air battery modeling for small form factor IR-UWB Wireless Sensor Network radios". In 2013 IEEE 24th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2013. http://dx.doi.org/10.1109/pimrc.2013.6666136.
Texto completo da fonteJinpoy Hong, Youjun Choi e Kyihwan Park. "Mobile robot navigation using modified flexible vector field approach with laser range finder and IR sensor". In 2007 International Conference on Control, Automation and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iccas.2007.4406993.
Texto completo da fonteChao, Paul C. P., Li-Chi Hsu e Trong-Hieu Tran. "A New Small-Sized Non-Dispersive Infrared (NDIR) Sensor and its Drive/Readout Circuits". In ASME 2016 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/isps2016-9562.
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