DocumentCode :
3746285
Title :
Kansei Engineering-based Sensor for Agro-industry (KESAN) for measurement and monitoring of worker performance
Author :
Mirwan Ushada;Atris Suyantohadi;Nafis Khuriyati;Tsuyoshi Okayama;Dzikri Rahadian Fudholi
Author_Institution :
Universitas Gadjah Mada, Department of Agro-Industrial Technology, Faculty of Agricultural Technology, Yogyakarta, Indonesia Postal Code 55281
fYear :
2015
Firstpage :
19
Lastpage :
23
Abstract :
This paper highlighted Kansei Engineering-based Sensor for Agro-industry, which is abbreviated as KESAN. KESAN was developed to measure and monitor worker performance in Agro-industrial Small-Medium sized Enterprises (SMEs). It was developed using Artificial Neural Network (ANN) model based on Kansei Engineering approach. The training and validation data was collected from four types of Food´s SMEs in Special Region of Yogyakarta. ANN´s weight is transformed in to Arduino. There were 12 inputs of KESAN as total mood disturbance, heart rate, workstations temperature, relative humidity, lighting and noise, which were measured before and after working. The worker performance was indicated by LED signal of green (normal workers), yellow (CCW) and red (OCW). This research concluded KESAN as a low cost, portable, practicable and intermediate information technology for SMEs.
Keywords :
"Temperature measurement","Workstations","Information technology","Artificial neural networks","Mood","Heart rate","Monitoring"
Publisher :
ieee
Conference_Titel :
Science in Information Technology (ICSITech), 2015 International Conference on
Print_ISBN :
978-1-4799-8384-1
Type :
conf
DOI :
10.1109/ICSITech.2015.7407770
Filename :
7407770
Link To Document :
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