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An IoT Camera System for the Collection of Data Using QR Code as Object Recognition Algorithm
- Source :
- Scopus2-s2.0-85061033536, 4th Innovation and Trends in Engineering Congress, CONIITI 2018
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- 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. Faculty of Engineering of the Catholic University of Colombia
- Subjects :
- Application programming interfaces (API)
Internet of things
Object detection
Computer science
Application programming interface
Camera systems
computer.software_genre
Recognition of objects
Software and hardwares
Software
Web application
Object recognition algorithm
computer.programming_language
Camera system
Database
business.industry
HTTP
Cognitive neuroscience of visual object recognition
Data acquisition
Object recognition
Python (programming language)
Cameras
Recognition algorithm
Internet of things (IOT)
Data collection
The Internet
Computer systems programming
Timestamp
business
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI)
- Accession number :
- edsair.doi.dedup.....e2781287e57544938b96157bc146423e
- Full Text :
- https://doi.org/10.1109/coniiti.2018.8587087