CottonTrace for Seed to Cloth Traceability with IoT and Digital Product Passports

Cotton production involves repeated changes in material form, ownership and quantity, making a garment difficult to trace using disconnected records. We present CottonTrace, a web-based prototype that links eight material stages through quantity-labelled lot genealogy, contract-based validation, an application-managed permissioned-ledger model, off-chain evidence, Internet of Things ingestion and a QR-accessible Digital Product Passport. An explainable detection layer combines robust statistics with domain rules to route suspicious records to auditors. The design is examined against the implementation and the project-reported synthetic evaluation of 18 lots, 61 blocks and 2,488 sensor readings. That evaluation records rejection of invalid operations, detection of edited evidence, eight findings corresponding to planted irregularities, and verification of 12 upstream lots for a garment passport. These observations demonstrate functional integration within the pilot. They do not establish distributed consensus, field accuracy, calibrated fraud probabilities or a complete environmental life-cycle assessment. The main contribution is a transparent workflow connecting deterministic validation, evidence integrity, material attribution and human review in a single cotton traceability prototype.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2026-11-04
DOI
https://doi.org/10.22214/ijraset.2026.85507
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CottonTrace for Seed to Cloth Traceability with IoT and Digital Product Passports

Palkesh Prajapati, Puja Gupta, Ayush Sharma, Darshil Vatyani
International Journal for Research in Applied Science and Engineering Technology
Food Supply Chain Traceability
article

CottonTrace for Seed to Cloth Traceability with IoT and Digital Product Passports

Palkesh Prajapati, Puja Gupta, Ayush Sharma, Darshil Vatyani
article en

Abstract

Cotton production involves repeated changes in material form, ownership and quantity, making a garment difficult to trace using disconnected records. We present CottonTrace, a web-based prototype that links eight material stages through quantity-labelled lot genealogy, contract-based validation, an application-managed permissioned-ledger model, off-chain evidence, Internet of Things ingestion and a QR-accessible Digital Product Passport. An explainable detection layer combines robust statistics with domain rules to route suspicious records to auditors. The design is examined against the implementation and the project-reported synthetic evaluation of 18 lots, 61 blocks and 2,488 sensor readings. That evaluation records rejection of invalid operations, detection of edited evidence, eight findings corresponding to planted irregularities, and verification of 12 upstream lots for a garment passport. These observations demonstrate functional integration within the pilot. They do not establish distributed consensus, field accuracy, calibrated fraud probabilities or a complete environmental life-cycle assessment. The main contribution is a transparent workflow connecting deterministic validation, evidence integrity, material attribution and human review in a single cotton traceability prototype.

International Journal for Research in Applied Science and Engineering TechnologyVol. 14(11)
Openalex Percentile: Top 18%
Food Supply Chain Traceability
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon