Analysis of household power consumption data for social safety net services
Much interest in lonely death and activity of daily living (ADL) monitoring services through analysis from household power consumption data is increasing. For this, anomaly detection and power disaggregation are needed, respectively. However, the existing technologies suffer from inaccuracy problem,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723006224 |
| _version_ | 1797688411348271104 |
|---|---|
| author | Gyubaek Kim Sanghyun Park |
| author_facet | Gyubaek Kim Sanghyun Park |
| author_sort | Gyubaek Kim |
| collection | DOAJ |
| description | Much interest in lonely death and activity of daily living (ADL) monitoring services through analysis from household power consumption data is increasing. For this, anomaly detection and power disaggregation are needed, respectively. However, the existing technologies suffer from inaccuracy problem, so they are not widely used. In this study, activity perception-based anomaly detection and appliance activation profile-based disaggregation methods are newly presented to improve accuracy. According to the experimental results, the proposed methods showed better performance than the existing methods. |
| first_indexed | 2024-03-12T01:31:32Z |
| format | Article |
| id | doaj.art-af6a9703fab94ed49b7511847ae749ec |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-12T01:31:32Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-af6a9703fab94ed49b7511847ae749ec2023-09-12T04:15:44ZengElsevierEnergy Reports2352-48472023-09-0191824Analysis of household power consumption data for social safety net servicesGyubaek Kim0Sanghyun Park1AI Robotics Development Team, SK Telecom, 65 Eulji-ro Jung-gu, Seoul, 04539, Republic of Korea; Department of Computer Science, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Republic of KoreaDepartment of Computer Science, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Republic of Korea; Corresponding author.Much interest in lonely death and activity of daily living (ADL) monitoring services through analysis from household power consumption data is increasing. For this, anomaly detection and power disaggregation are needed, respectively. However, the existing technologies suffer from inaccuracy problem, so they are not widely used. In this study, activity perception-based anomaly detection and appliance activation profile-based disaggregation methods are newly presented to improve accuracy. According to the experimental results, the proposed methods showed better performance than the existing methods.http://www.sciencedirect.com/science/article/pii/S2352484723006224Lonely deathActivity of daily livingActivity perceptionAnomaly detectionAppliance activation profilePower disaggregation |
| spellingShingle | Gyubaek Kim Sanghyun Park Analysis of household power consumption data for social safety net services Energy Reports Lonely death Activity of daily living Activity perception Anomaly detection Appliance activation profile Power disaggregation |
| title | Analysis of household power consumption data for social safety net services |
| title_full | Analysis of household power consumption data for social safety net services |
| title_fullStr | Analysis of household power consumption data for social safety net services |
| title_full_unstemmed | Analysis of household power consumption data for social safety net services |
| title_short | Analysis of household power consumption data for social safety net services |
| title_sort | analysis of household power consumption data for social safety net services |
| topic | Lonely death Activity of daily living Activity perception Anomaly detection Appliance activation profile Power disaggregation |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723006224 |
| work_keys_str_mv | AT gyubaekkim analysisofhouseholdpowerconsumptiondataforsocialsafetynetservices AT sanghyunpark analysisofhouseholdpowerconsumptiondataforsocialsafetynetservices |