An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm
This paper proposes an Internet Of Things (IoT) implementation for recognition of objects using videos to store data about specific objects on internet. This IoT implementation is based on a recognition algorithm for objects using the OpenCV library for Python and a Raspberry PI 3 to store the data...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9203
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9203
- Palabra clave:
- Application programming interface
Camera system
Data collection
Internet of things
Recognition algorithm
Application programming interfaces (API)
Cameras
Computer systems programming
Data acquisition
HTTP
Object detection
Object recognition
Camera systems
Data collection
Internet of things (IOT)
Object recognition algorithm
Recognition algorithm
Recognition of objects
Software and hardwares
Web application
Internet of things
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm |
| title |
An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm |
| spellingShingle |
An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm Application programming interface Camera system Data collection Internet of things Recognition algorithm Application programming interfaces (API) Cameras Computer systems programming Data acquisition HTTP Object detection Object recognition Camera systems Data collection Internet of things (IOT) Object recognition algorithm Recognition algorithm Recognition of objects Software and hardwares Web application Internet of things |
| title_short |
An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm |
| title_full |
An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm |
| title_fullStr |
An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm |
| title_full_unstemmed |
An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm |
| title_sort |
An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm |
| dc.contributor.editor.none.fl_str_mv |
Lozano-Garzon C.A. |
| dc.subject.keywords.none.fl_str_mv |
Application programming interface Camera system Data collection Internet of things Recognition algorithm Application programming interfaces (API) Cameras Computer systems programming Data acquisition HTTP Object detection Object recognition Camera systems Data collection Internet of things (IOT) Object recognition algorithm Recognition algorithm Recognition of objects Software and hardwares Web application Internet of things |
| topic |
Application programming interface Camera system Data collection Internet of things Recognition algorithm Application programming interfaces (API) Cameras Computer systems programming Data acquisition HTTP Object detection Object recognition Camera systems Data collection Internet of things (IOT) Object recognition algorithm Recognition algorithm Recognition of objects Software and hardwares Web application Internet of things |
| description |
This paper proposes an Internet Of Things (IoT) implementation for recognition of objects using videos to store data about specific objects on internet. This IoT implementation is based on a recognition algorithm for objects using the OpenCV library for Python and a Raspberry PI 3 to store the data on a web application. This set of software and hardware act as a module. The module sends requests every time an object is detected to the web application. This module requires an active connection to the Internet to allow the HTTP communication. This web application is in charge of controlling and storing the data of the objects. For the purpose of this paper, the stored data on the web application is the ID of the module, a message and a timestamps. The data is collected by the modules of the objects that belong to a pool. Also, the information of the modules and the object is listed on the web application using different views of the stored data. © 2018 IEEE. |
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2018 |
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2018 |
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2020-03-26T16:33:13Z |
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2020-03-26T16:33:13Z |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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Conferencia |
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2018 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2018 - Proceedings |
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9781538681312 |
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https://hdl.handle.net/20.500.12585/9203 |
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10.1109/CONIITI.2018.8587087 |
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Universidad Tecnológica de Bolívar |
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Repositorio UTB |
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57205675016 57191621984 26325154200 |
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2018 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2018 - Proceedings 9781538681312 10.1109/CONIITI.2018.8587087 Universidad Tecnológica de Bolívar Repositorio UTB 57205675016 57191621984 26325154200 |
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https://hdl.handle.net/20.500.12585/9203 |
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eng |
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eng |
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3 October 2018 through 5 October 2018 |
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Institute of Electrical and Electronics Engineers Inc. |
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Institute of Electrical and Electronics Engineers Inc. |
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Lozano-Garzon C.A.Ibanez J.F.Serrano Castaneda J.E.Martínez-Santos, Juan Carlos2020-03-26T16:33:13Z2020-03-26T16:33:13Z20182018 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2018 - Proceedings9781538681312https://hdl.handle.net/20.500.12585/920310.1109/CONIITI.2018.8587087Universidad Tecnológica de BolívarRepositorio UTB572056750165719162198426325154200This paper proposes an Internet Of Things (IoT) implementation for recognition of objects using videos to store data about specific objects on internet. This IoT implementation is based on a recognition algorithm for objects using the OpenCV library for Python and a Raspberry PI 3 to store the data on a web application. This set of software and hardware act as a module. The module sends requests every time an object is detected to the web application. This module requires an active connection to the Internet to allow the HTTP communication. This web application is in charge of controlling and storing the data of the objects. For the purpose of this paper, the stored data on the web application is the ID of the module, a message and a timestamps. The data is collected by the modules of the objects that belong to a pool. Also, the information of the modules and the object is listed on the web application using different views of the stored data. © 2018 IEEE.Faculty of Engineering of the Catholic University of ColombiaRecurso electrónicoapplication/pdfengInstitute of Electrical and Electronics Engineers Inc.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85061033536&doi=10.1109%2fCONIITI.2018.8587087&partnerID=40&md5=85cc8617cc28d3145eaef9d8459159a2Scopus2-s2.0-850610335364th Innovation and Trends in Engineering Congress, CONIITI 2018An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithminfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fApplication programming interfaceCamera systemData collectionInternet of thingsRecognition algorithmApplication programming interfaces (API)CamerasComputer systems programmingData acquisitionHTTPObject detectionObject recognitionCamera systemsData collectionInternet of things (IOT)Object recognition algorithmRecognition algorithmRecognition of objectsSoftware and hardwaresWeb applicationInternet of things3 October 2018 through 5 October 2018Cropley, J., (2018) Top Video Surveillance Trends for 2018, p. 3Shinobi, Shinobi Open Source Project, , https://shinobi.video/Ispy Open Source Project, , https://www.ispyconnect.com/, IspyRapid, V.M.S., RapidVMS Open Source Project, , http://www.veyesys.com/Zoneminder Open Source Project, , https://zoneminder.com/, ZoneminderArvidson, W., Predictions for 2017 in Video SurveillanceBelussi, L.F., Hirata, N.S., Fast component-based qr code detection in arbitrarily acquired images (2013) Journal of Mathematical Imaging and Vision, 45 (3), pp. 277-292Hogpracha, W., Vongpradhip, S., Recognition system for qr code on moving car (2015) Computer Science & Education (ICCSE), 2015 10th International Conference on, pp. 14-18. , IEEEKasinski, A., Schmidt, A., The architecture and performance of the face and eyes detection system based on the haar cascade classifiers (2010) Pattern Analysis and Applications, 13 (2), pp. 197-211Rezaei, M., Creating a cascade of haar-like classifiers: Step by step (2013) Aplikasi Pendeteksian Ras Kucing Dengan Mendeteksi Wajah Kucing Dengan Metode Viola JonesSajjad, M., Nasir, M., Muhammad, K., Khan, S., Jan, Z., Kumar Sangaiah, A., Elhoseny, M., Baik, S., (2017) Raspberry Pi Assisted Face Recognition Framework for Enhanced Law-enforcement Services in Smart Cities, , 11Yu, M., Zhang, D., Cheng, Y., Wang, M., An RFID electronic tag based automatic vehicle identification system for traffic iot applications (2011) Control and Decision Conference (CCDC), 2011 Chinese, pp. 4192-4197. , IEEEPatiño-Vanegas, A., Contreras-Ortiz, S.H., Martinez-Santos, J.C., A low noise stenography method for medical images with qr encoding of patient information (2017) Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 10138, p. 101380H. , International Society for Optics and PhotonicsDelgado, I.B., Colorado, L.A.M., Prada, E.J.A., Martínez-Santos, J.C., Irrigation system for oil palm in Colombia - An internet of things approach (2017) Workshop on Engineering Applications, pp. 300-311. , SpringerCastañeda, J.E.S., Patino, O.A., Martinez-Santos, J.C., Aquapp, an information system for a collaborative sensor network (2016) Computing Conference (CCC), 2016 IEEE 11th Colombian, pp. 1-6. , IEEEHendry, M.R.M., Rahman, M.N.A., Seyal, A.H., Smart attendance system applying qr code (2017) 12th International Conference on Latest Trends in Engineering and Technology (ICLTET'2017), pp. 22-24. , MayHicks, C.R., Turner, K.V., (1999) Fundamental Concepts in the Design of Experiments, 40. , Oxford University Press New Yorkhttp://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/9203/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/9203oai:repositorio.utb.edu.co:20.500.12585/92032023-05-26 16:28:48.821Repositorio Institucional UTBrepositorioutb@utb.edu.co |