Waste level detection and HMM based collection scheduling of multiple bins.
In this paper, an image-based waste collection scheduling involving a node with three waste bins is considered. First, the system locates the three bins and determines the waste level of each bin using four Laws Masks and a set of Support Vector Machine (SVM) classifiers. Next, a Hidden Markov Model...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2018-01-01
|
| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC6114775?pdf=render |
| _version_ | 1819100081022828544 |
|---|---|
| author | Fayeem Aziz Hamzah Arof Norrima Mokhtar Noraisyah M Shah Anis S M Khairuddin Effariza Hanafi Mohamad Sofian Abu Talip |
| author_facet | Fayeem Aziz Hamzah Arof Norrima Mokhtar Noraisyah M Shah Anis S M Khairuddin Effariza Hanafi Mohamad Sofian Abu Talip |
| author_sort | Fayeem Aziz |
| collection | DOAJ |
| description | In this paper, an image-based waste collection scheduling involving a node with three waste bins is considered. First, the system locates the three bins and determines the waste level of each bin using four Laws Masks and a set of Support Vector Machine (SVM) classifiers. Next, a Hidden Markov Model (HMM) is used to decide on the number of days remaining before waste is collected from the node. This decision is based on the HMM's previous state and current observations. The HMM waste collection scheduling seeks to maximize the number of days between collection visits while preventing waste contamination due to late collection. The proposed system was trained using 100 training images and then tested on 100 test images. Each test image contains three bins that might be shifted, rotated, occluded or toppled over. The upright bins could be empty, partially full or full of garbage of various shapes and sizes. The method achieves bin detection, waste level classification and collection day scheduling rates of 100%, 99.8% and 100% respectively. |
| first_indexed | 2024-12-22T00:57:06Z |
| format | Article |
| id | doaj.art-e89b233ef1114ce288e247b18ec32b73 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-22T00:57:06Z |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-e89b233ef1114ce288e247b18ec32b732022-12-21T18:44:17ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01138e020209210.1371/journal.pone.0202092Waste level detection and HMM based collection scheduling of multiple bins.Fayeem AzizHamzah ArofNorrima MokhtarNoraisyah M ShahAnis S M KhairuddinEffariza HanafiMohamad Sofian Abu TalipIn this paper, an image-based waste collection scheduling involving a node with three waste bins is considered. First, the system locates the three bins and determines the waste level of each bin using four Laws Masks and a set of Support Vector Machine (SVM) classifiers. Next, a Hidden Markov Model (HMM) is used to decide on the number of days remaining before waste is collected from the node. This decision is based on the HMM's previous state and current observations. The HMM waste collection scheduling seeks to maximize the number of days between collection visits while preventing waste contamination due to late collection. The proposed system was trained using 100 training images and then tested on 100 test images. Each test image contains three bins that might be shifted, rotated, occluded or toppled over. The upright bins could be empty, partially full or full of garbage of various shapes and sizes. The method achieves bin detection, waste level classification and collection day scheduling rates of 100%, 99.8% and 100% respectively.http://europepmc.org/articles/PMC6114775?pdf=render |
| spellingShingle | Fayeem Aziz Hamzah Arof Norrima Mokhtar Noraisyah M Shah Anis S M Khairuddin Effariza Hanafi Mohamad Sofian Abu Talip Waste level detection and HMM based collection scheduling of multiple bins. PLoS ONE |
| title | Waste level detection and HMM based collection scheduling of multiple bins. |
| title_full | Waste level detection and HMM based collection scheduling of multiple bins. |
| title_fullStr | Waste level detection and HMM based collection scheduling of multiple bins. |
| title_full_unstemmed | Waste level detection and HMM based collection scheduling of multiple bins. |
| title_short | Waste level detection and HMM based collection scheduling of multiple bins. |
| title_sort | waste level detection and hmm based collection scheduling of multiple bins |
| url | http://europepmc.org/articles/PMC6114775?pdf=render |
| work_keys_str_mv | AT fayeemaziz wasteleveldetectionandhmmbasedcollectionschedulingofmultiplebins AT hamzaharof wasteleveldetectionandhmmbasedcollectionschedulingofmultiplebins AT norrimamokhtar wasteleveldetectionandhmmbasedcollectionschedulingofmultiplebins AT noraisyahmshah wasteleveldetectionandhmmbasedcollectionschedulingofmultiplebins AT anissmkhairuddin wasteleveldetectionandhmmbasedcollectionschedulingofmultiplebins AT effarizahanafi wasteleveldetectionandhmmbasedcollectionschedulingofmultiplebins AT mohamadsofianabutalip wasteleveldetectionandhmmbasedcollectionschedulingofmultiplebins |