Journal:A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model

Full article title	A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model
Journal	High-Confidence Computing
Author(s)	Manisha, Noothi; Jagadeeshwar, Madiraju
Author affiliation(s)	Chaitanya Deemed to be University
Primary contact	noothimanisha6 at gmail dot com
Year published	2023
Volume and issue	3(3)
Article #	100121
DOI	10.1016/j.hcc.2023.100121
ISSN	2667-2952
Distribution license	Attribution-NonCommercial-NoDerivs 4.0 International
Website	https://www.sciencedirect.com/science/article/pii/S2667295223000193
Download	https://www.sciencedirect.com/science/article/pii/S2667295223000193/pdfft (PDF)

Abstract

Food traceability is a critical factor that can ensure food safety while enhancing the credibility of the manufactured product, thus achieving heightened user satisfaction and loyalty. The perishable food supply chain (PFSC) requires paramount care for ensuring quality owing to the limited product life. The PFSC comprises of multiple organizations with varied interests and is more likely to be hesitant in sharing the traceability details among one another owing to a lack of trust, which can be overcome by using blockchain. In this research, an efficient scheme using a blockchain-enabled deep residual network (BC-DRN) is developed to provide food traceability for dairy products. Here, food traceability is determined by using various modular tools, like the internet of things (IoT), blockchain data management, food traceability blockchain architecture, and DRN-based food quality evaluation tools. The devised BC-DRN-based food quality traceability system is examined based on performance metrics such as sensitivity, response time, and testing accuracy, and it has attained better values of 0.939, 109.564 s, and 0.931, respectively.

Keywords: perishable food supply chain, blockchain, internet of things, food traceability, deep learning

Introduction

In supply chains, the process of perishable products management is extremely complex. This process differs from other products based on various aspects, like deterioration rate, cold storage requirement, and shelf life, from the production unit to the end user. [1][2] Among the various foods in the perishable food supply chain (PFSC), milk and dairy products are the major sources of nutrients. However, poor work practices, animal feed, and the environment may introduce chemical components and contaminants in those milk and dairy products, putting consumers at risk. [3] Increasingly, consumers have become more attentive towards the quality, source, transport [4][5], and shipping regulations surrounding purchasable food items. [6] Depending on the scenario, there is a varying necessity to trace those food items for achieving better supply chain management (SCM). [7] While globalization has complicated SCM and the traceability of food items [8], blockchain, a type of distributed ledger technology (DLT), may have a role to play in solving such problems.

Blockchain is considered to be a significant DLT technology impacting commerce, wherein information can be stored in a database and shared among organizations, which have no mutual trust. [9] Blockchain is an underdeveloped technology [10], where few of the applications require trust, which is already devised. [11][12] The data in blockchain cannot be falsified [13] and has the capability for providing trustworthy, secure, and transparent data in public as well as private domains. [14] It is founded on a distributed ledger that is not controlled or owned by a single user. The major benefit of using blockchain is that it can be employed in the PFSC for enhancing the integrity of data gathered from multiple entities in the supply chain. [15]

Food traceability is component of PFSC logistics, where the data regarding any food item at every stage is captured, stored, and transmitted across the supply chain for enabling quality checks of the product at various points. Moreover, it also provides a way for tracking the product at any required time. [3][16] The primary step for providing traceability is the adequate depiction of traceable resource units (TRUs) for identifying the logistic and production units, traceability of products, and so on for managing the PFSC. [17]

Various studies have focused on developing traceability solutions in the PFSC for various products. For instance, Bumblauskas et al. proposed a blockchain-oriented traceability scheme considering the eggs, wherein the eggs were tracked from farms to the end users. [18] Cao et al. described a traceability scheme for strengthening the trust in the existing supply chain between China and Australia. [6] Similarly, Khan et al. proposed a food provenance system for handling data on the traceability of meat products using blockchain, internet of things (IoT), and sophisticated deep learning approaches [19], each with their own complexities. [20–23] Other similar approaches have considered a variety of perishable products, like beef, fish, and other agricultural products. [24] A dairy case study was considered by Casino et al., wherein a distributed trustless and secure scheme was devised for tracing the dairy products of a company. Additionally, Cocco et al. developed a blockchain-based model for managing the supply chain of a traditional bakery. Finally, the major critical aspects affecting the safety and quality of food, while storing and distributing the products, demand monitoring the humidity and temperature. The utilization of radio frequency identification (RFID) traceability schemes can be highly effective during monitoring of these and other processes. [27][28]

This research work mainly focuses on the development of a food quality traceability system using blockchain, IoT, and deep learning architecture. Here, the devised food traceability scheme is implemented using various modular tools, like the internet of things (IoT), blockchain data management, food traceability blockchain architecture, and deep residual network (DRN)-based food quality evaluation tools. Data from dairy product manufacturing and its associated supply chains are collected using IoT technologies. The collected data is then transformed into a sequence of blocks in the blockchain network, wherein each node represents the entity involved. The food traceability blockchain is developed by considering the consumers’ purchases of dairy products, product IDs, etc. This blockchain-driven IoT-based deep learning system for improving the food traceability process is designed to monitor the effects of dairy product supply chains, wherein DRN techniques are employed for grading the milk.

The remaining portions of this work are as such. The next section details the related works in food traceability, while the third section elaborates on the system model of IoT-based blockchain-driven food traceability schemes, and the fourth section discusses the methodology used to develop those schemes. The results and discussion of the developed method are discussed in the penultimate section, followed by conclusions about the work.

Literature review

Though several studies have been carried out for developing effective food traceability systems for edible goods, only eight works are considered for review here. Mondal et al. [15] used an RFID-based sensor with blockchain for producing a more transparent PFSC. Here, a consensus algorithm named Proof-of-Object (PoO) was applied, which made use of the variation found in cryptocurrency as well as supply chain for avoiding needless transactions added to the blockchain. This technique was highly efficient in making the blockchain immune to cyber attacks. However, this method suffered from having inadequate security. Bechtsis et al. [29] developed a containerized food supply chain framework for securing the information shared in the PFSC. Here, a double-staged containerized food supply chain was implemented by considering the Hyperledger Fabric open-source framework. This system offered enhanced traceability and process control, and prevented possible risks. However, the huge amount of information exchanged resulted in high costs. Hao et al. [12] developed a visual analysis technique for detecting the food safety risks in the PFSC. This scheme utilized the combination of visualization and blockchain technology, wherein features such as tamper-resistance and distribution were utilized for ensuring the authenticity of data. This scheme provided a scientific platform for managing the PFSC with the minimization of potential risks, but it suffered from low scalability. Gao et al. [30] proposed a Hyperledger Fabric-based traceability system in the PFSC using blockchain technology. Governors were introduced by the system for strengthening the regulation, and a market was introduced for providing a platform to search for information regarding food and transactions. This system was effective in achieving high throughput, but it achieved poor system functionality and efficiency.

Behnke and Janssen [16] devised a blockchain-driven technology for providing an effective solution for food traceability. The approach utilized a set of boundary criteria for providing agriculture and food traceability, thereby assuring information sharing. This method was successful in achieving high transparency, thus gaining user trust; however, this method needed to find boundary criteria for determining the changes in blockchain ahead of its adoption and had high complexity. Rambhia et al. [31] introduced Agrichain, a system for managing the PFSC using blockchain. Here, SCM activities were streamlined by using smart contracts and the Ethereum blockchain. Moreover, the interaction among different entities was captured, thus guaranteeing authenticity, traceability, and transparency. This approach was effective in ensuring authenticity by disallowing illegal changes, but it failed in handling real-time applications.

Shahbazi and Byun [7] developed a machine learning (ML) technology and fuzzy logic for tracing the products in the PFSC. This system was implemented using three parts: prediction of expiry date by using ML approaches, blockchain-based data sharing, and fuzzy-oriented food quality evaluation. The scheme was highly efficient in improving the shelf life in the PFSC. However, the supply chain formed by this scheme was insecure and unreliable, thus affecting the effectiveness of the approach. Greater reliability was provided by Ehsan et al. [32], wherein they developed a conceptual model for developing a centralized scheme for ensuring the traceability of the supply chain. Here, a blockchain-oriented scheme was developed, wherein the supply chain was effectively managed using a multi-agent system. This approach was utilized for optimizing any supply chain with high efficiency and security. However, this method was ineffective when trying to handle distinct supply chains in different formats.

System model

This section contains a detailed description of the system model of the devised food traceability system, specifically for milk and other dairy products. The system model is depicted in Fig. 1. The traceability system model is devised for ensuring the products are delivered with good quality and safety in the PFSC. The milk and dairy products collected from the dairy manufacturers are tagged with RFID tags, which enable end-to-end tracing of the products. The RFID tag comprises of data concerning the product in read-only or read–write format. The electromagnetic (EM) energy triggers the RFID tags, when they enter the range of the scanning antenna, and the data is sent in the form of radio waves. The antenna picks up the radio wave and it is forwarded to the RFID reader, where the waves are converted into digital data. The data acquired by the RFID reader/gateway is gathered by the IoT data collector. The collected data is converted into the block at the blockchain data management module, wherein the blocks comprise of records for all the activities that occurred during its creation. Moreover, every block is provided with a field containing the hash value of the prior blockhead, thus ensuring that all blocks can effectively point to their prior blocks. The generated blockchain data is fed to the food traceability blockchain architecture, wherein the multiple entities through which the transfer of products happen is considered. Every time the product goes through a new entity in the supply chain, a block is added to the blockchain, thereby providing a way to trace the product. After effective food traceability is determined, a food quality evaluation is performed for grading the milk to determine its quality.

Figure 1. System model of the food quality traceability module.

Blockchain-based food traceability prediction

The data collected by the IoT data collector is converted into the blockchain format, wherein the initial block contains the information related to the product along with the timestamp and hash value. The blockchain assists in enabling the flexibility of the system. The milk or dairy products are initially supplied by the manufacturer. The products are assigned with a batch ID [7] in the genesis block, and the tracking information stored in the cloud is contained in the supply chain process. The product can be traced by considering batch/ID as well as container ID. The blockchain data is updated throughout every stage in the supply chain, and this data is stored in the database. The supply chain forms initially send the food traceability data to the regulatory bodies, which in turn send the qualified check-up certificate. Once the certificate is received, the traceability data along with the hash value is forwarded to the blockchain nodes, which maintain the shared ledger. The nodes verify the credibility of the data received and based on the credibility, blockchain nodes transmit a reject or accept message to the supply chain. If an accepted message is received, then the original traceability matrix is added to the database. Later, the shipment process is notified as waiting, ready, transporting, or received. As the blockchain is updated at each and every event, the consumers can back trace the products by using the blockchain.

Notes

This presentation is faithful to the original, with only a few minor changes to presentation and updates to spelling and grammar (including to the title). In some cases important information was missing from the references, and that information was added. Some citations were vague as to how they contributed, or some statements didn't match well with their citations; minor tweaks were made to have the text and citations match up better. The key contribution portion of the introduction was removed for this version, as it was redundant and simply repeated the prior paragraph. No other changes were made in accordance with the "No-Derivatives" portion of the distribution license.