Phone-based Ambient Temperature Measurement with a New Confidence-based Truth Inference Model

Chen, Dayin1; Shi, Xiaodan2; Song, Xuan1; Chen, Zhiheng2; Zhang, Haoran3

2022-12-01

10.1145/3570347

PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT   影响因子和分区

2474-9567

Monitoring the indoor temperature can help saving of energy and improve the comfort level. Smartphone, as a ubiquitous device, can be an additional data source to provide the ambient temperature estimation. However, the estimation results sometimes can be unreliable due to the different phone using states. How to integrate multiple estimation results in one area to get a more accurate prediction result is still a challenge. In this work, we proposed one phone-based ambient temperature measurement system which contains two models. The first temperature prediction model takes easily accessible phone state features as inputs and outputs ambient temperature prediction with a confidence value. The second truth inference model takes multiple prediction results with confidences as inputs and outputs a referred final prediction result. Our temperature prediction model reaches 0.253.C with MAE in our testing set. We also proved by transfer learning our model can be used in other new type of phones. We evaluate the truth inference model in our testing dataset and it reaches 0.128 degrees C, which outperforms the state-of-the-art truth inference algorithms. We believe this work can contribute to energy conservation and provide new ideas for crowdsourcing.

crowdsourcing truth inference phone energy conservation attention

ESCI ; EI

英语

第一 ; 通讯

National Key Research and Development Program of China[2018AAA0101100] ; National Key Research and Development Project[2021YFB1714400] ; Guangdong Provincial Key Laboratory[2020B121201001]

Computer Science ; Engineering ; Telecommunications

Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications

WOS:000910841900053

ASSOC COMPUTING MACHINERY

20230413420363

Crowdsourcing ; Deep learning ; Energy conservation ; Inference engines ; Statistical tests ; Telephone sets ; Temperature ; Temperature measurement

Ergonomics and Human Factors Engineering:461.4 ; Energy Conservation:525.2 ; Thermodynamics:641.1 ; Telephone Systems and Equipment:718.1 ; Expert Systems:723.4.1 ; Mathematical Statistics:922.2 ; Temperature Measurements:944.6

Web of Science

1.Southern Univ Sci & Technol SUSTech, SUSTech UTokyo Joint Res Ctr Super Smart City, Res Inst Trustworthy Autonomous Syst, Dept Comp Sci & Engn, 1088 Xueyuan Ave, Shenzhen 518055, Peoples R China
2.Univ Tokyo, Ctr Spatial Informat Sci, 5-1-5 Kashiwanoha, Chiba 2778568, Japan
3.Peking Univ, Sch Urban Planning & Design, Shenzhen 100871, Peoples R China

Chen, Dayin,Shi, Xiaodan,Song, Xuan,et al. Phone-based Ambient Temperature Measurement with a New Confidence-based Truth Inference Model[J]. PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT,2022,6(4).

Chen, Dayin,Shi, Xiaodan,Song, Xuan,Chen, Zhiheng,&Zhang, Haoran.(2022).Phone-based Ambient Temperature Measurement with a New Confidence-based Truth Inference Model.PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT,6(4).

Chen, Dayin,et al."Phone-based Ambient Temperature Measurement with a New Confidence-based Truth Inference Model".PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 6.4(2022).