Food Recognition via Monitoring Power Leakage from a Microwave Oven
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説明
In this paper, we demonstrate a food recognition method by monitoring power leakage from a domestic microwave oven. Universal Software Radio Peripheral (USRP) is applied as a low-cost spectrum analyzer to measure the microwave oven leakage as received signal strength indication (RSSI). We aim to recognize 18 categories of food that are commonly cooked in a microwave oven. By analyzing 180 features that contain the information of heating-time difference, we attain an average recognition accuracy of 82.3%. Using 138 features excluding the heating-time difference information, the average recognition accuracy is 56.2%. The recognition accuracy under different conditions is also investigated, for instance, utilizing different microwave ovens, different distances between the microwave oven and the USRP as well as different data down-sampling rates. Finally, a food recognition application is implemented to demonstrate our method.\n------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.23(2015) No.6(online)------------------------------
In this paper, we demonstrate a food recognition method by monitoring power leakage from a domestic microwave oven. Universal Software Radio Peripheral (USRP) is applied as a low-cost spectrum analyzer to measure the microwave oven leakage as received signal strength indication (RSSI). We aim to recognize 18 categories of food that are commonly cooked in a microwave oven. By analyzing 180 features that contain the information of heating-time difference, we attain an average recognition accuracy of 82.3%. Using 138 features excluding the heating-time difference information, the average recognition accuracy is 56.2%. The recognition accuracy under different conditions is also investigated, for instance, utilizing different microwave ovens, different distances between the microwave oven and the USRP as well as different data down-sampling rates. Finally, a food recognition application is implemented to demonstrate our method.\n------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.23(2015) No.6(online)------------------------------
収録刊行物
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- 情報処理学会論文誌コンシューマ・デバイス&システム(CDS)
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情報処理学会論文誌コンシューマ・デバイス&システム(CDS) 5 (4), 2015-10-03
一般社団法人情報処理学会
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詳細情報 詳細情報について
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- CRID
- 1050845762836025600
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- NII論文ID
- 110009868036
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- NII書誌ID
- AA12628043
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- ISSN
- 21865728
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- Web Site
- http://id.nii.ac.jp/1001/00145415/
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- 本文言語コード
- en
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- 資料種別
- article
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- データソース種別
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- IRDB
- CiNii Articles