Loading…
District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors
Garbage is inextricably linked with our daily lives, and solid waste collection is one of the essential local government services. We investigate a method that estimates regional amounts of garbage using motion sensors mounted on garbage trucks. In this paper, we report the results of our analysis o...
Saved in:
Main Authors: | , , , , , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | 7 |
container_issue | |
container_start_page | 1 |
container_title | |
container_volume | |
creator | Kishino, Yasue Shirai, Yoshinari Takeuchi, Koh Mizutani, Shin Suyama, Takayuki Naya, Futoshi Ueda, Naonori |
description | Garbage is inextricably linked with our daily lives, and solid waste collection is one of the essential local government services. We investigate a method that estimates regional amounts of garbage using motion sensors mounted on garbage trucks. In this paper, we report the results of our analysis of garbage amounts using national census data. By simply mounting motion sensors on garbage trucks and using activity recognition and multiple regression analysis, we were able to obtain significant and illuminating information. |
doi_str_mv | 10.1109/ISC255366.2022.9922487 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_9922487</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9922487</ieee_id><sourcerecordid>9922487</sourcerecordid><originalsourceid>FETCH-LOGICAL-i118t-1105502076e068d17dd7bd617813a474fad42639f9c27f9d7c0ef1705809547c3</originalsourceid><addsrcrecordid>eNotkN1KAzEUhKMgWOo-gSB5ga0nyebvsqy1FiqCtd6WNMm2kXZXkoj07Y3aq4H5DoeZQeiOwIQQ0PeLVUs5Z0JMKFA60ZrSRskLVGmpiBC8UVwQcYlGVChZKyXgGlUpfQAAo8AklyM0PISUY7AZt3sTjc0-FiPYhKe9OZxSSPg75D1-9bswFAfPTdyancfT4_DVZzwrx0eTC8PrFPodfvf7YA--xs-_3Luif3Tl-zTEdIOuOnNIvjrrGK0fZ2_tU718mS_a6bIOhKhcl36cAwUpPAjliHRObp0gpRgzjWw64xoqmO60pbLTTlrwHZHAFWjeSMvG6Pb_b_Debz5jCRlPm_NE7Ads8lvB</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors</title><source>IEEE Xplore All Conference Series</source><creator>Kishino, Yasue ; Shirai, Yoshinari ; Takeuchi, Koh ; Mizutani, Shin ; Suyama, Takayuki ; Naya, Futoshi ; Ueda, Naonori</creator><creatorcontrib>Kishino, Yasue ; Shirai, Yoshinari ; Takeuchi, Koh ; Mizutani, Shin ; Suyama, Takayuki ; Naya, Futoshi ; Ueda, Naonori</creatorcontrib><description>Garbage is inextricably linked with our daily lives, and solid waste collection is one of the essential local government services. We investigate a method that estimates regional amounts of garbage using motion sensors mounted on garbage trucks. In this paper, we report the results of our analysis of garbage amounts using national census data. By simply mounting motion sensors on garbage trucks and using activity recognition and multiple regression analysis, we were able to obtain significant and illuminating information.</description><identifier>EISSN: 2687-8860</identifier><identifier>EISBN: 9781665485616</identifier><identifier>EISBN: 1665485612</identifier><identifier>DOI: 10.1109/ISC255366.2022.9922487</identifier><language>eng</language><publisher>IEEE</publisher><subject>Activity recognition ; DNN ; Motion detection ; Multiple regressions ; Production ; Sensors ; Smart cities ; Sociology ; Waste materials ; Waste reduction</subject><ispartof>2022 IEEE International Smart Cities Conference (ISC2), 2022, p.1-7</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9922487$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9922487$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Kishino, Yasue</creatorcontrib><creatorcontrib>Shirai, Yoshinari</creatorcontrib><creatorcontrib>Takeuchi, Koh</creatorcontrib><creatorcontrib>Mizutani, Shin</creatorcontrib><creatorcontrib>Suyama, Takayuki</creatorcontrib><creatorcontrib>Naya, Futoshi</creatorcontrib><creatorcontrib>Ueda, Naonori</creatorcontrib><title>District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors</title><title>2022 IEEE International Smart Cities Conference (ISC2)</title><addtitle>ISC2</addtitle><description>Garbage is inextricably linked with our daily lives, and solid waste collection is one of the essential local government services. We investigate a method that estimates regional amounts of garbage using motion sensors mounted on garbage trucks. In this paper, we report the results of our analysis of garbage amounts using national census data. By simply mounting motion sensors on garbage trucks and using activity recognition and multiple regression analysis, we were able to obtain significant and illuminating information.</description><subject>Activity recognition</subject><subject>DNN</subject><subject>Motion detection</subject><subject>Multiple regressions</subject><subject>Production</subject><subject>Sensors</subject><subject>Smart cities</subject><subject>Sociology</subject><subject>Waste materials</subject><subject>Waste reduction</subject><issn>2687-8860</issn><isbn>9781665485616</isbn><isbn>1665485612</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2022</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotkN1KAzEUhKMgWOo-gSB5ga0nyebvsqy1FiqCtd6WNMm2kXZXkoj07Y3aq4H5DoeZQeiOwIQQ0PeLVUs5Z0JMKFA60ZrSRskLVGmpiBC8UVwQcYlGVChZKyXgGlUpfQAAo8AklyM0PISUY7AZt3sTjc0-FiPYhKe9OZxSSPg75D1-9bswFAfPTdyancfT4_DVZzwrx0eTC8PrFPodfvf7YA--xs-_3Luif3Tl-zTEdIOuOnNIvjrrGK0fZ2_tU718mS_a6bIOhKhcl36cAwUpPAjliHRObp0gpRgzjWw64xoqmO60pbLTTlrwHZHAFWjeSMvG6Pb_b_Debz5jCRlPm_NE7Ads8lvB</recordid><startdate>20220926</startdate><enddate>20220926</enddate><creator>Kishino, Yasue</creator><creator>Shirai, Yoshinari</creator><creator>Takeuchi, Koh</creator><creator>Mizutani, Shin</creator><creator>Suyama, Takayuki</creator><creator>Naya, Futoshi</creator><creator>Ueda, Naonori</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20220926</creationdate><title>District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors</title><author>Kishino, Yasue ; Shirai, Yoshinari ; Takeuchi, Koh ; Mizutani, Shin ; Suyama, Takayuki ; Naya, Futoshi ; Ueda, Naonori</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i118t-1105502076e068d17dd7bd617813a474fad42639f9c27f9d7c0ef1705809547c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Activity recognition</topic><topic>DNN</topic><topic>Motion detection</topic><topic>Multiple regressions</topic><topic>Production</topic><topic>Sensors</topic><topic>Smart cities</topic><topic>Sociology</topic><topic>Waste materials</topic><topic>Waste reduction</topic><toplevel>online_resources</toplevel><creatorcontrib>Kishino, Yasue</creatorcontrib><creatorcontrib>Shirai, Yoshinari</creatorcontrib><creatorcontrib>Takeuchi, Koh</creatorcontrib><creatorcontrib>Mizutani, Shin</creatorcontrib><creatorcontrib>Suyama, Takayuki</creatorcontrib><creatorcontrib>Naya, Futoshi</creatorcontrib><creatorcontrib>Ueda, Naonori</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kishino, Yasue</au><au>Shirai, Yoshinari</au><au>Takeuchi, Koh</au><au>Mizutani, Shin</au><au>Suyama, Takayuki</au><au>Naya, Futoshi</au><au>Ueda, Naonori</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors</atitle><btitle>2022 IEEE International Smart Cities Conference (ISC2)</btitle><stitle>ISC2</stitle><date>2022-09-26</date><risdate>2022</risdate><spage>1</spage><epage>7</epage><pages>1-7</pages><eissn>2687-8860</eissn><eisbn>9781665485616</eisbn><eisbn>1665485612</eisbn><abstract>Garbage is inextricably linked with our daily lives, and solid waste collection is one of the essential local government services. We investigate a method that estimates regional amounts of garbage using motion sensors mounted on garbage trucks. In this paper, we report the results of our analysis of garbage amounts using national census data. By simply mounting motion sensors on garbage trucks and using activity recognition and multiple regression analysis, we were able to obtain significant and illuminating information.</abstract><pub>IEEE</pub><doi>10.1109/ISC255366.2022.9922487</doi><tpages>7</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | EISSN: 2687-8860 |
ispartof | 2022 IEEE International Smart Cities Conference (ISC2), 2022, p.1-7 |
issn | 2687-8860 |
language | eng |
recordid | cdi_ieee_primary_9922487 |
source | IEEE Xplore All Conference Series |
subjects | Activity recognition DNN Motion detection Multiple regressions Production Sensors Smart cities Sociology Waste materials Waste reduction |
title | District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T16%3A19%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=District%20Characteristics%20Analysis%20with%20Regional%20Garbage%20Amount%20Estimation%20Using%20Vehicle-%20Mounted%20Motion%20Sensors&rft.btitle=2022%20IEEE%20International%20Smart%20Cities%20Conference%20(ISC2)&rft.au=Kishino,%20Yasue&rft.date=2022-09-26&rft.spage=1&rft.epage=7&rft.pages=1-7&rft.eissn=2687-8860&rft_id=info:doi/10.1109/ISC255366.2022.9922487&rft.eisbn=9781665485616&rft.eisbn_list=1665485612&rft_dat=%3Cieee_CHZPO%3E9922487%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i118t-1105502076e068d17dd7bd617813a474fad42639f9c27f9d7c0ef1705809547c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=9922487&rfr_iscdi=true |