Samsung Automation Studio is to provide development tools and execution environment that can easily configure application logic by connecting both Samsung service and 3rd party service. This project is to share the node for open source NodeRED developed by Samsung Automation Studio team to the community. If you are using nodered, you can easily install the node we provide. And you can use Samsung's IoT and AI-related services more easily, and you can have an extended experience in conjunction with your own services.
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Request to add object detection node and data extraction nodes #59
안녕하세요. Samsung SW Academy For Youth 7th의 SASM 오픈소스 프로젝트 팀 '5생활관'입니다.
Samsung Automation Studio for Mashup(이하 SASM)에 기존 motion-pose와 함께 object detection 요소를 추가하여 사용자가 위치한 장소에 따라 motion pose가 의도하는 플로우를 달리 할 수 있는 다형성을 확보하였습니다. 동시에 motion pose과 object의 상호작용을 분석하여 log를 남기고 이를 시각화하는 dashboard chart를 제작하였습니다.
또한 이 플로우에서 API를 활용해 이후 동작을 연계하는 과정에서 활용되는 데이터 추출(data extraction) 노드까지 제작하였습니다.
본 노드와 플로우를 제작하기까지 기획 및 개발 과정에서 여러 인사이트와 기술적으로 지원해주신 삼성전자 김선학 멘토님과 이진규 멘토님, 그리고 SSAFY 관계자분들께 깊은 감사를 드립니다.
English
Hello. This is the SASM open source project team 'D5MI' of Samsung SW Academy For Youth 7th.
By adding the object detection element along with the existing motion-pose to Samsung Automation Studio for Mashup (hereafter referred to as SASM), polymorphism that allows the intended flow of motion pose to vary depending on the location of the user has been secured. At the same time, we created a dashboard chart that analyzes the interaction between motion pose and object, leaves a log and visualizes it.
In addition, using the API in this flow, data extraction nodes that is used in the process of linking subsequent actions was also created.
We will briefly summarize the descriptions of the nodes we have developed.
name
description
object detection
recognition/judgment of over 80 objects and recording of logs
object person determine
determine which object is interacting with the recognized person
log
saves log records of object and person recognition in a file in a fixed format
data extractor
selects and extracts only a specific part of API data
data filter
select and extract a specific part of API data when some elements satisfy specific conditions
For details on the developed nodes, please refer to the link below.
We would like to express our deepest gratitude to mentors Seonhak Kim and Jinkyu Lee of Samsung Electronics, mentors of Samsung Electronics, and SSAFY officials for providing various insights and technical support during the planning and development process until the production of this node and flow.
SangWoo-Han97
commented
1 year ago
Korean
안녕하세요. Samsung SW Academy For Youth 7th의 SASM 오픈소스 프로젝트 팀 '5생활관'입니다.
Samsung Automation Studio for Mashup(이하 SASM)에 기존 motion-pose와 함께 object detection 요소를 추가하여 사용자가 위치한 장소에 따라 motion pose가 의도하는 플로우를 달리 할 수 있는 다형성을 확보하였습니다. 동시에 motion pose과 object의 상호작용을 분석하여 log를 남기고 이를 시각화하는 dashboard chart를 제작하였습니다.
또한 이 플로우에서 API를 활용해 이후 동작을 연계하는 과정에서 활용되는 데이터 추출(data extraction) 노드까지 제작하였습니다.
저희가 개발한 노드들에 대한 설명을 간략하게 요약하겠습니다.
object detectionobject person determinelogdata extractordata filter개발한 노드들에 대한 세부 내용은 아래의 링크를 참고해주시기 바랍니다.
본 노드와 플로우를 제작하기까지 기획 및 개발 과정에서 여러 인사이트와 기술적으로 지원해주신 삼성전자 김선학 멘토님과 이진규 멘토님, 그리고 SSAFY 관계자분들께 깊은 감사를 드립니다.
English
Hello. This is the SASM open source project team 'D5MI' of Samsung SW Academy For Youth 7th.
By adding the object detection element along with the existing motion-pose to Samsung Automation Studio for Mashup (hereafter referred to as SASM), polymorphism that allows the intended flow of motion pose to vary depending on the location of the user has been secured. At the same time, we created a dashboard chart that analyzes the interaction between motion pose and object, leaves a log and visualizes it.
In addition, using the API in this flow, data extraction nodes that is used in the process of linking subsequent actions was also created.
We will briefly summarize the descriptions of the nodes we have developed.
object detectionobject person determinelogdata extractordata filterFor details on the developed nodes, please refer to the link below.
We would like to express our deepest gratitude to mentors Seonhak Kim and Jinkyu Lee of Samsung Electronics, mentors of Samsung Electronics, and SSAFY officials for providing various insights and technical support during the planning and development process until the production of this node and flow.