Academic literature on the topic 'Smartphone-based'
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Journal articles on the topic "Smartphone-based"
Aralikatti, Rakesh I., and Kishan S. Anegundi. "Location-Based Services in a Smartphone." Bonfring International Journal of Software Engineering and Soft Computing 6, Special Issue (October 31, 2016): 130–33. http://dx.doi.org/10.9756/bijsesc.8259.
Full textPituła, Emil, Marcin Koba, and Mateusz Śmietana. "Which smartphone for a smartphone-based spectrometer?" Optics & Laser Technology 140 (August 2021): 107067. http://dx.doi.org/10.1016/j.optlastec.2021.107067.
Full textGao, Xuefei, and Nianqiang Wu. "Smartphone-Based Sensors." Electrochemical Society Interface 25, no. 4 (2016): 79–81. http://dx.doi.org/10.1149/2.f07164if.
Full textHandzel, Ophir, and Kevin Franck. "Smartphone based hearing evaluation." Operative Techniques in Otolaryngology-Head and Neck Surgery 32, no. 2 (June 2021): 87–91. http://dx.doi.org/10.1016/j.otot.2021.05.004.
Full textAhmed, Yunus. "Smartphone-based analytical biosensors." Dental Poster Journal 9, no. 2 (2020): 1–2. http://dx.doi.org/10.15713/ins.dpj.056.
Full textGarabelli, Paul, Stavros Stavrakis, and Sunny Po. "Smartphone-based arrhythmia monitoring." Current Opinion in Cardiology 32, no. 1 (January 2017): 53–57. http://dx.doi.org/10.1097/hco.0000000000000350.
Full textKumar, Nilesh, Bandello Francesco, and Ashish Sharma. "Smartphone-based Gonio-Imaging." Journal of Glaucoma 28, no. 9 (September 2019): e149-e150. http://dx.doi.org/10.1097/ijg.0000000000001306.
Full textTurk-Adawi, Karam, and Sherry L. Grace. "Smartphone-based cardiac rehabilitation." Heart 100, no. 22 (August 27, 2014): 1737–38. http://dx.doi.org/10.1136/heartjnl-2014-306335.
Full textNuñez, José Jesús Reyes. "Smartphone-Based School Atlases?" Cartographica: The International Journal for Geographic Information and Geovisualization 48, no. 2 (June 2013): 126–33. http://dx.doi.org/10.3138/carto.48.2.1842.
Full textHuang, Xiwei, Dandan Xu, Jin Chen, Jixuan Liu, Yangbo Li, Jing Song, Xing Ma, and Jinhong Guo. "Smartphone-based analytical biosensors." Analyst 143, no. 22 (2018): 5339–51. http://dx.doi.org/10.1039/c8an01269e.
Full textDissertations / Theses on the topic "Smartphone-based"
Yang, Zhenyu. "Smartphone-based Optical Sensing." University of Dayton / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1461863029.
Full textReyes, Ortiz Jorge Luis. "Smartphone-based human activity recognition." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/284725.
Full textEl Reconocimiento de Actividades Humanas (RAH) es un campo de investigación multidisciplinario que busca recopilar información sobre el comportamiento de las personas y su interacción con el entorno con el propósito de ofrecer información contextual de alta significancia sobre las acciones que ellas realizan. Recientemente, el RAH ha contribuido en el desarrollo de áreas de estudio enfocadas a la mejora de la calidad de vida del hombre tales como: la inteligència ambiental (Ambient Intelligence) y la vida cotidiana asistida por el entorno para personas dependientes (Ambient Assisted Living). El primer paso para conseguir el RAH consiste en realizar observaciones mediante el uso de sensores fijos localizados en el ambiente, o bien portátiles incorporados de forma vestible en el cuerpo humano. Sin embargo, para el segundo caso, aún se dificulta encontrar dispositivos poco invasivos, de bajo consumo energético, que permitan ser llevados a cualquier lugar, y de bajo costo. En esta tesis, nosotros exploramos el uso de teléfonos móviles inteligentes (Smartphones) como una alternativa para el RAH. Estos dispositivos, de uso cotidiano y fácilmente asequibles en el mercado, están dotados de sensores embebidos, potentes capacidades de cómputo y diversas tecnologías de comunicación inalámbrica que los hacen apropiados para esta aplicación. Nuestro trabajo presenta una serie de contribuciones en relación al desarrollo de sistemas para el RAH con Smartphones. En primera instancia proponemos un sistema que permite la detección de seis actividades físicas en tiempo real y que, además, tiene en cuenta las transiciones posturales que puedan ocurrir entre ellas. Con este fin, hemos contribuido en distintos ámbitos que van desde el procesamiento de señales y la selección de características, hasta algoritmos de Aprendizaje Automático (AA). Nosotros utilizamos dos sensores inerciales (el acelerómetro y el giroscopio) para la captura de las señales de movimiento de los usuarios. Estas han de ser procesadas a través de técnicas de filtrado para la reducción de ruido, segmentación y obtención de características relevantes en la detección de actividad. También hacemos énfasis en el estudio de Máquinas de soporte vectorial (MSV) que son uno de los algoritmos de AA más usados en la actualidad. Para ello reformulamos varios de sus métodos estándar (lineales y no lineales) con el propósito de encontrar la mejor combinación de variables que garanticen un buen desempeño del sistema en cuanto a precisión, coste computacional y requerimientos de energía, los cuales son aspectos esenciales en dispositivos portátiles con suministro de energía mediante baterías. En concreto, proponemos dos MSV multiclase para la clasificación de actividad: un algoritmo lineal que permite el balance entre la reducción de la dimensionalidad y la precisión del sistema; y asimismo presentamos un algoritmo no lineal conveniente para dispositivos con limitaciones de hardware que solo utiliza aritmética de punto fijo en la fase de predicción y que permite reducir la complejidad del modelo de aprendizaje mientras mantiene el rendimiento del sistema. La eficacia del sistema propuesto es verificada a través de una experimentación extensiva sobre la base de datos RAH que hemos generado y hecho pública en la red. Esta contiene la información inercial obtenida de un grupo de 30 participantes que realizaron una serie de actividades de la vida cotidiana en un ambiente controlado mientras tenían sujeto a su cintura un smartphone que capturaba su movimiento. Los resultados obtenidos en esta investigación demuestran que es posible realizar el RAH en tiempo real con una precisión cercana al 97%. De esta manera, podemos emplear la metodología propuesta en aplicaciones de alto nivel que requieran el RAH tales como monitorizaciones ambulatorias para personas dependientes (ej. ancianos o discapacitados) durante periodos mayores a cinco días sin la necesidad de recarga de baterías.
Zhang, Sen. "Smartphone Based Activity Recognition System." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354661301.
Full textAghanavesi, Somayeh. "Smartphone-based Parkinson’s disease symptom assessment." Licentiate thesis, Högskolan Dalarna, Mikrodataanalys, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:du-24925.
Full textDinis, Joel Eduardo dos Santos. "Attendance control system based on smartphone." Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/14059.
Full textAttendance control systems are associated with labour legislation for the protection of employees and employers. School attendances' issues may be directly connected to academic achievements at the same time it is di cult to control by children's parents. To solve these problems, there are several systems available and the di erence between them is essentially the technology adopted to make them work. Nowadays, mobile equipment market has a great diversity with smartphone equipments having the highest demands and high growth rates. Due to the huge capacities of their operating systems and hardware, smartphones have now the possibility to be used as part of an attendance control system. In this dissertation, it is developed an attendance control system based on smarphone and virtual doors composed of two Access Points (APs). This system has the advantage of being inexpensive and, since the application runs in the background of the operating system, attendance detection becomes a fully automatic process. Moreover, since a smartphone is a personal equipment which is hardly shared with other person, attempts to defraud the control system are very unlikely to happen.
Os sistemas de registo de assiduidade estão associados a legislação laboral para defender os interesses dos empregados e dos empregadores. O controlo de presenças em escolas adquiriu também extrema importância estando cada vez mais associado ao sucesso académico. Atualmente existe uma panóplia de sistemas deste tipo cujas diferenças estão essencialmente ao nível da tecnologia utilizada como base de funcionamento do sistema. O mercado de equipamentos m oveis apresenta igualmente grande diversidade e um rápido e sustentado crescimento, sendo mesmo um dos mercados com maiores taxas de crescimento ano ap os ano na área das tecnologias de informação. A venda de smartphones representa j a mais de metade da venda deste tipo de equipamentos. Devido as enormes potencialidades dos seus sistemas operativos e do seu hardware, estes equipamentos abriram a possibilidade da sua utilização como parte integrante de um sistema de registo de assiduidade. Nesta dissertação e proposto um sistema de registo de assiduidade baseado em smartphone e em portarias virtuais compostas por dois Access Point. O sistema apresenta como principais vantagens o facto de ser barato, a aplicação correr em segundo plano no sistema operativo tornando o processo de picagem um processo automático, e também por ser um dispositivo que o utilizador tem dificuldade em ceder a terceiros, reduzindo por isso tentativas de fraude ao sistema de controlo de assiduidade.
Wahlström, Johan. "Sensor Fusion for Smartphone-based Vehicle Telematics." Doctoral thesis, KTH, Teknisk informationsvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-218071.
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Gomes, Vítor Emanuel Ornelas. "Smartphone based accident detection and eCall implementation." Master's thesis, Universidade de Aveiro, 2013. http://hdl.handle.net/10773/12835.
Full textIntelligent Transportation Systems are emerging, to increase safety, e - ciency and comfort on roads. This intelligence is due to the fact that new technologies are being introduced in the most recent automobiles. As a result of this technological evolution, vehicular communication systems are being developed, to provide drivers with more information about the interventionists present in the roads they circulate. Predictions point that this information can increase safety and e ciency on roads. Presently, the Instituto de Telecomunica c~oes de Aveiro, is developing its own vehicular communication system, named HEADWAY, as a solution. HEADWAY DSRC 5.9 GHz vehicular communication system currently under development. Smartphones nowadays are very popular devices. This is due to the fact that they pack incredible hardware resources in a small and portable device and the possibility to third party developers, develop applications for them. This enables these devices to be used in di erent areas, depending only from the creativity of the developers. To diminish the number of fatalities due to road accidents, the European Commission has mandated the implementation of eCall in every new vehicle by 2015. In vehicles, the eCall aim to detect accidents and request accidents automatically. This dissertation targets, on the one hand, the development of an accident detection mechanism with eCall implementation. On the other hand it targets the integration of smartphones with HEADWAY, by developing an application that takes advantage of the system characteristics and demonstrates it. To achieve the proposed goals, an Android application was developed which acts as an HMI for HEADWAY, enables message exchange between vehicles, automatically detects accidents and proceeds with a help request. Most of the proposed goals where achieved, except the eCall implementation, which an alternative method was developed.
Os Sistemas de Transporte Inteligentes estão a emergir, de forma a introduzir mais segurança, eficiência e conforto nas estradas. Esta inteligência deve-se ao facto de novas tecnologias estarem a ser introduzidas nos automóveis recentes. Como resultado da evolução tecnológica os sistemas de comunicação veiculares estão a ser desenvolvidos, com o objectivo de munir os condutores com informações relativas aos diferentes intervenientes da estrada onde circulam. Prevê-se que este tipo de informação leve a uma maior segurança e eficiência nas estradas. Actualmente no Instituto de Telecomunicações de Aveiro, está a decorrer um projecto que visa fornecer uma alternativa como sistema de comunicações veiculares. Este projecto tem o nome de HEADWAY. O HEADWAY é um sistema de comunicações veiculares DSRC 5.9 GHz, atualmente em desenvolvimento. Os smartphones hoje em dia já são dispositivos estabelecidos no mercado. Isto deve-se ao facto destes apresentarem um grande potencial, ao integrarem recursos de hardware incríveis num pequeno dispositivo e de permitirem o desenvolvimento de aplicações por terceiros. A criatividade dos programadores tem permitido a utilização destes dispositivos em diversas áreas. De forma a diminuir o número de mortes causadas por acidentes rodoviários, a Comissão Europeia, tornou obrigatório que em 2015 todos os novos carros estejam equipados com o sistema eCall, que visa a deteção de acidentes e pedido de ajuda ao 112 automáticos. Esta dissertação tem por um lado, o objectivo de desenvolver um detector de acidentes com implementação de eCall, e, por outro lado, integrar um smartphone com o HEADWAY, através do desenvolvimento de uma aplicação que tire partido das características deste sistema e assim o demonstre. Para cumprir os objectivos foi desenvolvida uma aplicação para Android que atua como HMI para o HEADWAY, facilita a troca de mensagens entre veículos, deteta automaticamente acidentes e procede com pedidos de ajuda. Na conclusão do projecto, verificou-se que os objectivos propostos foram na sua maioria concluídos, exceptuando a implementação da eCall ao 112, sendo desenvolvido um método alternativo.
Ben, Tahayekt Ben Tahaikt Chaimaa. "A secure user authentication scheme for critical mobile applications." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-34845.
Full textMILD, MARKUS, and VINKLER ALEXIS MÄÄTTÄ. "An Explorative Usability Studyof Smartphone-Based Indoor Navigation." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-138025.
Full textI takt med den konstant växande globala mobilanvändningen blir vi allt mer beroende av mobila tjänster. Smartphones har numera ett brett spektrum av användningsområden, där platsspecifika tjänster blivit en del av vår vardag. Tjänsterna har dock hitintills främst kommit att omfatta utomhusmiljöer. Genom att utnyttja mobiltelefonens inbyggda Assisted Global Positioning System (A-GPS) i kombination med tekniker för platsigenkänning, som baseras på exempelvis mobilmaster eller WiFi-noder, kan dock mobiltelefoner numera användas för att bestämma en position även i inomhusmiljöer. Då utvecklingen av inomhuspositionering fortskridit har förstadium-system, avsedda för inomhusnavigering med hjälp av smartphones, tagits fram. Bortsett från noggrannheten i den resulterade positionen så har andra områden inom inomhusnavigering och -positionering blivit åsidosatta, såsom användarbeteende och implementering av de framtagna systemen. Denna studie innefattar två faser, varav första fasen var att upprätta två inomhusnavigeringssystem samt parallellt utvärdera dessa system ur ett utvecklarperspektiv. I den andra fasen, kallad slutanvändarperspektivet, genomfördes användartester, vilket gjordes i form av fälttest i kombination med intervjuer. Gemensamt för bägge faser var användbarhet, där två olika perspektiv och därmed två olika betydelser gestaltades. Resultatet från vår studie visar tydligt att system utformade för inomhusnavigering med hjälp av smartphones, ännu inte nått sin fulla potential - varken för slutanvändare eller administratörer. Den inbäddade funktionaliteten visade sig vara väldigt felkänslig, där små användbarhetsproblem fick stora konsekvenser för slutanvändares förmåga att orientera och navigera sig inomhus. Administratörer/utvecklare måste göra en grundlig utvärdering av den ämnade inomhusmiljön, för att säkerställa att systemet kommer fungera samt för att minimera den totala tiden för implementeringen. Administratörer bör även överväga kontrollerbarheten av tillgängliga system, då beroenden till aktörer som tillhandahåller systemet innebär en oönskad brist av kontroll. Om existerande infrastruktur ämnas användas, såsom WiFi-noder, bör nödvändiga förutsättningar för inomhuspositionering säkerställas på förhand. Avslutningsvis i denna rapport listas våra (författarnas) gemensamma rekommendationer, där de mest omfattande slutsatserna lyfts fram i form av sex riktlinjer. Riktlinjerna som tagits fram är: 1 Funktionalitet för orientering och navigering är felkänslig, 2. Positioneringsmetod bör väljas baserat på den tilltänkta miljön, 3. Stabil positionering är viktigare än exakt positionering, 4. Live-spårning ger omedelbar återkoppling på förflyttning, 5. Dynamiska planlösningar är grundläggande för ett dynamiskt navigeringssytem, samt 6. Kontrollerbarhet är värdefullt, beroenden bör vara minimala.
Konnaiyan, Karthik Raj. "Smartphone Based 3D Printed Colorimeter for Biomedical Applications." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5975.
Full textBooks on the topic "Smartphone-based"
Reyes Ortiz, Jorge Luis. Smartphone-Based Human Activity Recognition. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14274-6.
Full textGao, Ruipeng, Fan Ye, Guojie Luo, and Jason Cong. Smartphone-Based Indoor Map Construction. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8378-5.
Full textKehtarnavaz, Nasser, Abhishek Sehgal, and Shane Parris. Smartphone-Based Real-Time Digital Signal Processing. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-031-02540-2.
Full textKehtarnavaz, Nasser, Shane Parris, and Abhishek Sehgal. Smartphone-Based Real-Time Digital Signal Processing. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-031-02537-2.
Full textBasu, Souvik, Siuli Roy, and Sipra Das Bit. Reliable Post Disaster Services over Smartphone Based DTN. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6573-7.
Full textOzer, Ekin. Multisensory Smartphone Applications in Vibration-Based Structural Health Monitoring. [New York, N.Y.?]: [publisher not identified], 2016.
Find full text1961-, Baciu George, ed. Introduction to wireless localization: With iPhone SDK examples. Hoboken, N.J: Wiley, 2012.
Find full textRajesh, Lal, ed. Beginning smartphone web development: Building JavaScript, CSS, HTML and Ajax-based applications for iPhone, Android, Palm Pre, Blackberry, Windows Mobile and Nokia S60. New York: Apress, 2009.
Find full textAtif, Iqbal, and Guzinski Jaroslaw, eds. High performance control of AC drives with MATLAB/Simulink models. Chichester, West Sussex: Wiley, 2012.
Find full textSmartphone-Based Detection Devices. Elsevier, 2021. http://dx.doi.org/10.1016/c2020-0-00290-2.
Full textBook chapters on the topic "Smartphone-based"
Yus, Francisco. "Location-based smartphone interaction 1." In Smartphone Communication, 211–30. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003200574-15.
Full textHuang, Huawei, and Song Guo. "Smartphone Based Emergency Communication." In Big Data in Emergency Management: Exploitation Techniques for Social and Mobile Data, 131–47. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48099-8_7.
Full textStütz, Thomas, Thomas Kowar, Michael Kager, Martin Tiefengrabner, Markus Stuppner, Jens Blechert, Frank H. Wilhelm, and Simon Ginzinger. "Smartphone Based Stress Prediction." In Lecture Notes in Computer Science, 240–51. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20267-9_20.
Full textCalabretta, Maria Maddalena, Laura Montali, Antonia Lopreside, Aldo Roda, and Elisa Michelini. "Smartphone-Based Cell Detection." In Handbook of Cell Biosensors, 1–16. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-47405-2_98-1.
Full textKurylyak, Yuriy, Francesco Lamonaca, and Domenico Grimaldi. "Smartphone-Based Photoplethysmogram Measurement." In Digital Image and Signal Processing for Measurement Systems, 135–64. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003337911-5.
Full textDawson, Catherine. "Smartphone app-based research." In A–Z of Digital Research Methods, 335–41. Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9781351044677-51.
Full textCalabretta, Maria Maddalena, Laura Montali, Antonia Lopreside, Aldo Roda, and Elisa Michelini. "Smartphone-Based Cell Detection." In Handbook of Cell Biosensors, 963–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-23217-7_98.
Full textReyes Ortiz, Jorge Luis. "Introduction." In Smartphone-Based Human Activity Recognition, 1–5. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14274-6_1.
Full textReyes Ortiz, Jorge Luis. "Background." In Smartphone-Based Human Activity Recognition, 9–35. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14274-6_2.
Full textReyes Ortiz, Jorge Luis. "State of the Art." In Smartphone-Based Human Activity Recognition, 37–56. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14274-6_3.
Full textConference papers on the topic "Smartphone-based"
Lau, Vincent M. K. "Smartphone based robot." In SIGGRAPH Asia 2013 Symposium on Mobile Graphics and Interactive Applications. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2543651.2543693.
Full textStafford, Matthew, Adriana Rogers, Shela Wu, Charles Carver, N. Sertac Artan, and Ziqian Dong. "TETRIS: Smartphone-to-Smartphone Screen-Based Visible Light Communication." In 2017 IEEE 14th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS). IEEE, 2017. http://dx.doi.org/10.1109/mass.2017.101.
Full text"SMARTPHONE BASED E-LEARNING." In 3rd International Conference on Computer Supported Education. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003334901610170.
Full textGiardini, Mario E., Iain A. T. Livingstone, Stewart Jordan, Nigel M. Bolster, Tunde Peto, Matthew Burton, and Andrew Bastawrous. "A smartphone based ophthalmoscope." In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2014. http://dx.doi.org/10.1109/embc.2014.6944049.
Full textErickson, David, and Matt Mancuso. "Smartphone based Molecular Diagnostics." In Optical Sensors. Washington, D.C.: OSA, 2013. http://dx.doi.org/10.1364/sensors.2013.sw3b.2.
Full textBa, Zhongjie, Tianhang Zheng, Zhan Qin, Hanlin Yu, Liu Liu, Baochun Li, Xue Liu, and Kui Ren. "Accelerometer-based smartphone eavesdropping." In MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3372224.3417323.
Full textLiu, Qiang, Yun Liu, Huizhen Yuan, Jiabin Wang, Jianye Guang, and Wei Peng. "Smartphone based LSPR biosensor." In 2018 Asia Communications and Photonics Conference (ACP). IEEE, 2018. http://dx.doi.org/10.1109/acp.2018.8596229.
Full textManolopoulos, Vasileios, Panos Papadimitratos, Sha Tao, and Ana Rusu. "Securing smartphone based ITS." In 2011 11th International Conference on ITS Telecommunications (ITST). IEEE, 2011. http://dx.doi.org/10.1109/itst.2011.6060053.
Full textTao, Tao, Yu-E. Sun, Dongmei Chen, Yu Xin, Yonglong Luo, and He Huang. "PosAla: A Smartphone-Based Posture Alarm System Design for Smartphone Users." In 2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN). IEEE, 2018. http://dx.doi.org/10.1109/msn.2018.00026.
Full textAnthimopoulos, Marios, Sidharta Gupta, Spyridon Arampatzis, and Stavroula Mougiakakou. "Smartphone-based urine strip analysis." In 2016 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2016. http://dx.doi.org/10.1109/ist.2016.7738253.
Full textReports on the topic "Smartphone-based"
Lashkov, Igor, Alexey Kashevnik, and Andrey Ronzhin. Ontology-based Personalisation for Online Driver Monitoring by Smartphone. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, May 2019. http://dx.doi.org/10.7546/crabs.2019.05.13.
Full textKourtellis, Achilleas. Smartphone-based Connected Bicycle Prototype Development for Sustainable Multimodal Transportation System. Tampa, FL: University of South Florida, February 2018. http://dx.doi.org/10.5038/cutr-nctr-rr-2018-03.
Full textWard, Andrew, Anthony Falls, and Craig Rutland. Development of smartphone-based semi-prepared runway operations (SPRO) models and methods. Engineer Research and Development Center (U.S.), December 2021. http://dx.doi.org/10.21079/11681/42500.
Full textRakestraw, D. Resonant Acoustic Characterization of Coins: An Inquiry-Based Learning Activity for Everyone with a Smartphone. Office of Scientific and Technical Information (OSTI), November 2021. http://dx.doi.org/10.2172/1830948.
Full textCeballos, Francisco, Berber Kramer, Azad Mishra, Miguel Robles, and Mann S. Toor. Picture-based crop insurance: using farmers’ smartphone pictures to reduce basis risk and costs of loss verification. International Initiative for Impact Evaluation (3ie), June 2020. http://dx.doi.org/10.23846/tw13fe11.
Full textSeidametova, Zarema S., Zinnur S. Abduramanov, and Girey S. Seydametov. Using augmented reality for architecture artifacts visualizations. [б. в.], July 2021. http://dx.doi.org/10.31812/123456789/4626.
Full textLi, Lingxi, Yaobin Chen, Renren Tian, Feng Li, Howell Li, and James R. Sturdevant. An Integrated Critical Information Delivery Platform for Smart Segment Dissemination to Road Users. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317440.
Full textBedoya-Maya, Felipe, Lynn Scholl, Orlando Sabogal-Cardona, and Daniel Oviedo. Who uses Transport Network Companies?: Characterization of Demand and its Relationship with Public Transit in Medellín. Inter-American Development Bank, September 2021. http://dx.doi.org/10.18235/0003621.
Full textTreadwell, Jonathan R., James T. Reston, Benjamin Rouse, Joann Fontanarosa, Neha Patel, and Nikhil K. Mull. Automated-Entry Patient-Generated Health Data for Chronic Conditions: The Evidence on Health Outcomes. Agency for Healthcare Research and Quality (AHRQ), March 2021. http://dx.doi.org/10.23970/ahrqepctb38.
Full textEvaluating the Accuracy of Smartphone-Based Travel Behavior Data. Tampa, FL: University of South Florida, June 2022. http://dx.doi.org/10.5038/cutr-nicr-y1-3-1.
Full text