Melola Discovery

← Melola Discovery

Journal SINTA 1

Design of An Automatic Follower Shopping Trolley Based on Image Processing

Teknomekanik · Vol. 2 No. 2 (2019) · pp. 48–54

DOI
10.24036/tm.v2i1.3472
ISSN
2621-8720, 2621-9980
Published
2019-12-15
Publisher
Universitas Negeri Padang
Language
eng

Abstract

In the era of industrial revolution 4.0, all human activities are replaced by machines. Humans are required to optimize brain function than muscle function. All human work is facilitated by robots or tools work automatically. For example, shopping activities in the modern market. Consumers prefer to shop in the modern market than the traditional market, because the items are complete, neatly arranged, and they have facilities like trolleys as transporters. Trolleys can be pushed and pulled easily. But when shopping, parents have a problem with pushing or pulling a trolley when they carrying their children. Therefore, we created a design for automatic follower shopping trolley based on image processing which can follow the consumers when shopping. This trolley has a webcam camera as a sensor to take pictures of the objects or special accessories that used by consumers. The result of data are processed in such a way and then it will be obtained the x and y coordinates positions of the consumer and the next data will be sent to the Raspberry Pi 3 which will automatically determine the movement of the trolley. The test results showed that the distance range detected between trolleys and consumers ranged from 0.5 meters to 2 meters, and trolleys can move according to the point where the object was detected. Thus, the trolley can follow the user well.

Keywords

Collaboration network of the authors

40 authors · 78 co-authorship links · 2 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Indonesia
  • Universitas Halu Oleo
  • IPB University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Syaiful IslamiAffiliation unknown2
Anggi Agni ZausAffiliation unknown2
Mahesi Agni ZausAffiliation unknown2
Mustarum MusaruddinUniversitas Halu Oleo1
Eng. Lukas Kano ManggallaAffiliation unknown1
Sartiah YusranAffiliation unknown1
Lymbran TinaAffiliation unknown1
Veronika TebaiAffiliation unknown1
Octavian Bayu Surya HaribansahAffiliation unknown1
Hadi Rahmat PurnamaAffiliation unknown1
Mujiono MujionoAffiliation unknown1
Jayanti Yudha PertiwiAffiliation unknown1
Sri SusilaningsihAffiliation unknown1
Dian Ristanto RistantoAffiliation unknown1
Lilinda KoyimahAffiliation unknown1
Suyatmin SuyatminAffiliation unknown1
Deny IsmantoAffiliation unknown1
Muhammad ErfanAffiliation unknown1
Muhammad Archi MaulydaAffiliation unknown1
Vivi Rahmatul HidayatiAffiliation unknown1
Lalu Hamdian AffandiAffiliation unknown1
Moh. FadliAffiliation unknown1
Dhiana PuspitawatiAffiliation unknown1
Diah Pawestri MaharaniAffiliation unknown1
Mustafa LuthfiAffiliation unknown1
Dodi Jaya WardanaAffiliation unknown1
M. IsmailAffiliation unknown1
Ni Made Novi SuryantiAffiliation unknown1
Gunarhadi GunarhadiAffiliation unknown1
Djono DjonoAffiliation unknown1
Muhammad RomliIPB University1
Ani SuryaniAffiliation unknown1
Yeti WidyawatiAffiliation unknown1
Nizwardi JalinusAffiliation unknown1
Rizki Hadian SaktiAffiliation unknown1
Husnuzhan HusnuzhanAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://teknomekanik.ppj.unp.ac.id/index.php/teknomekanik/oai, first harvested 10 Nov 2026, last seen 10 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Design of An Automatic Follower Shopping Trolley Based on Image Processing</dc:title>
	<dc:creator xml:lang="en">Ananda, Gheri Febri</dc:creator>
	<dc:creator xml:lang="en">Wahyuni, Cici</dc:creator>
	<dc:creator xml:lang="en">Sania, Ellsa</dc:creator>
	<dc:creator xml:lang="en">Sukardi, Sukardi</dc:creator>
	<dc:subject xml:lang="en">Automatic Trolley</dc:subject>
	<dc:subject xml:lang="en">Image</dc:subject>
	<dc:subject xml:lang="en">Processing</dc:subject>
	<dc:description xml:lang="en">In the era of industrial revolution 4.0, all human activities are replaced by machines. Humans are required to optimize brain function than muscle function. All human work is facilitated by robots or tools work automatically. For example, shopping activities in the modern market. Consumers prefer to shop in the modern market than the traditional market, because the items are complete, neatly arranged, and they have facilities like trolleys as transporters. Trolleys can be pushed and pulled easily. But when shopping, parents have a problem with pushing or pulling a trolley when they carrying their children. Therefore, we created a design for automatic follower shopping trolley based on image processing which can follow the consumers when shopping. This trolley has a webcam camera as a sensor to take pictures of the objects or special accessories that used by consumers. The result of data are processed in such a way and then it will be obtained the x and y coordinates positions of the consumer and the next data will be sent to the Raspberry Pi 3 which will automatically determine the movement of the trolley. The test results showed that the distance range detected between trolleys and consumers ranged from 0.5 meters to 2 meters, and trolleys can move according to the point where the object was detected. Thus, the trolley can follow the user well.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Padang</dc:publisher>
	<dc:date>2019-12-15</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>http://teknomekanik.ppj.unp.ac.id/index.php/teknomekanik/article/view/34</dc:identifier>
	<dc:identifier>10.24036/tm.v2i1.3472</dc:identifier>
	<dc:source xml:lang="en">Teknomekanik; Vol. 2 No. 2 (2019): Regular Issue; 48-54</dc:source>
	<dc:source>2621-8720</dc:source>
	<dc:source>2621-9980</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>http://teknomekanik.ppj.unp.ac.id/index.php/teknomekanik/article/view/34/13</dc:relation>
</oai_dc:dc>