Prototype of Indoor Activity Estimation System with Low Load
| Autor: | Yusuke Kishikawa, Toshimitsu Inomata, Yoshikazu Arai, Shintaro Imai |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Estimation
0209 industrial biotechnology 020901 industrial engineering & automation Artificial neural network Computer science Water flow Real-time computing 0202 electrical engineering electronic engineering information engineering Low load Illuminance 020201 artificial intelligence & image processing 02 engineering and technology |
| Zdroj: | GCCE |
| DOI: | 10.1109/gcce.2018.8574774 |
| Popis: | In this research, we aim to estimate observed person’s indoor activities with low load. The proposed system satisfies the following three functional requirements i.e., (F1) an observed person is not required wearing tags/sensors, (F2) not using camera, and (F3) using inexpensive sensors. The system estimates the observed person’s activities based on acquired data from human sensors, power consumption sensors, illuminance sensors and water flow sensors. From the result of preliminary experiment, the system uses neural network for estimation. We implemented a prototype system and confirmed that moderate estimation accuracy and low load are compatible. |
| Databáze: | OpenAIRE |
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