Early Detection of Events as a Decision Support in the Milk Collection Planning

Zakeri, A; Saberi, M; Hussain, OK; Chang, E

Early Detection of Events as a Decision Support in the Milk Collection Planning

Zakeri, A Saberi, M

Hussain, OK Chang, E

Permalink

Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Industrial Engineering and Engineering Management, 2019, 2019-December, pp. 516-520
Issue Date:: 2019-01-09

Closed Access

	Filename	Description	Size
	08607443.pdf	Published version	135.44 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Zakeri, A
dc.contributor.author	Saberi, M https://orcid.org/0000-0002-5168-2078
dc.contributor.author	Hussain, OK
dc.contributor.author	Chang, E
dc.date	2018-12-16
dc.date.accessioned	2020-04-30T21:25:43Z
dc.date.available	2020-04-30T21:25:43Z
dc.date.issued	2019-01-09
dc.identifier.citation	IEEE International Conference on Industrial Engineering and Engineering Management, 2019, 2019-December, pp. 516-520
dc.identifier.isbn	9781538667866
dc.identifier.issn	2157-3611
dc.identifier.issn	2157-362X
dc.identifier.uri	http://hdl.handle.net/10453/140371
dc.description.abstract	© 2018 IEEE. Milk is a highly perishable product which needs to go through an almost perfect cold chain in a milk supply chain to maintain its highest quality. To satisfy the ever-increasing demand from dairy processors to be provided with raw milk at highest quality, transporters need to ensure the milk which is collected from farms has been stored properly before the pickup occurs; i.e., from the starting point of the production in the farm until the pickup event. To address this issue, in this paper, we have proposed a model for early detection of events in a milking cycle. Using the online data coming from IoT sensors, we detect and recognize various events in a milking cycle as close as possible to their real happening in the tank. This provides the transporter with a comprehensive, clear picture of the milk cooling performance while being stored in the farm. It also assists them in making smart decisions on pickup planning and scheduling.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	IEEE International Conference on Industrial Engineering and Engineering Management
dc.relation.ispartof	IEEE International Conference on Industrial Engineering and Engineering Management
dc.relation.isbasedon	10.1109/IEEM.2018.8607443
dc.rights	© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Early Detection of Events as a Decision Support in the Milk Collection Planning
dc.type	Conference Proceeding
utslib.citation.volume	2019-December
utslib.location.activity	Bangkok, Thailand
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0908 Food Sciences
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2020-04-30T21:25:41Z
pubs.finish-date	2018-12-19
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2018-12-16
pubs.volume	2019-December
utslib.start-page	516
dc.location	Piscataway, USA

Abstract:

© 2018 IEEE. Milk is a highly perishable product which needs to go through an almost perfect cold chain in a milk supply chain to maintain its highest quality. To satisfy the ever-increasing demand from dairy processors to be provided with raw milk at highest quality, transporters need to ensure the milk which is collected from farms has been stored properly before the pickup occurs; i.e., from the starting point of the production in the farm until the pickup event. To address this issue, in this paper, we have proposed a model for early detection of events in a milking cycle. Using the online data coming from IoT sensors, we detect and recognize various events in a milking cycle as close as possible to their real happening in the tank. This provides the transporter with a comprehensive, clear picture of the milk cooling performance while being stored in the farm. It also assists them in making smart decisions on pickup planning and scheduling.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/140371