Blockchain and Technologies Matching with the Case of Study of Vegetables Production

Alessandro Massaro, Vincenzo Maritati, Nicola Savino, Angelo Galiano, and Ugo Picciotti

Abstract


The proposed work describes a new approach based on supply chain traceability by blockchain (BC). The basic BC network has been designed and applied for vegetables process monitoring and tracing. The paper proposes some results of an industry research project by describing the whole scenario, the architectures implementing BC, the sequence diagram principle, and the prototype network embedding blocks and transactions. The discussion is also addressed on the possibility to combine different technique such as artificial intelligence, and image processing to improve pre-cut vegetable quality. The paper proposed preliminary results proves that the adopted technologies and the methodologies found in the literature are suitable for the sanitation process certification and for quality traceability. The mentioned approaches are useful to apply the suggested frameworks for other supply chains.

Keywords


Blockchain, Production Process monitoring, Production Quality Improvement, Supply Chain.

References


A. Massaro, N. Contuzzi and A. Galiano, “Intelligent Processes in Automated Production Involving Industry 4.0 Technologies and Artificial Intelligence," book chapter: Advanced Robotics and Intelligent Automation in Manufacturing, IGI GLOBAL, ISSN: 2327-0411, DOI: 10.4018/978-1-7998-1382-8.ch004, ch.4, pp. 97- 122, 2020.

M. A. Alsheyab and A. H. Muñoz, “Reducing the formation of trihalomethanes (THMs) by ozone combined with hydrogen peroxide (H2O2/O3),” Desalination, Vol. 194, 2006, No. 1-3, pp. 121–126.

A. Gopal, J. Coventry, J. Wan, H. Roginski, S. Ajlouni, “Alternative disinfection techniques to extend the shelf life of minimally processed iceberg lettuce,” Food Microbiology, Vol. 27, No. 2, 2010, pp. 210–219.

M. A. Khawarizmi and Phebe, Ding, “Ozone Application in Fresh Fruits and Vegetables,” Pertanika Journal of Scholarly Research Reviews, Vol. 4, No. 2, 2018, pp. 29-35.

A. Ippolito, L. Schena, I. Pentimone and F. Nigro, “Control of postharvest rots of sweet cherries by pre- and postharvest applications of Aureobasidium pullulans in combination with calcium chloride or sodium bicarbonate,” Postharvest Biology and Technology , Vol. 36, No. 3, 2005, pp. 245–252.

L. Pinto, A. Ippolito and F. Baruzzi, “Control of spoiler Pseudomonas spp. on fresh cut vegetables by neutral electrolyzed water,” Food Microbiology, Vol. 50, 2015, pp. 102-108.

G. Romanazzi, F. Nigro andA. Ippolito, “Effetto di trattamenti pre- e post- raccolta con chitosano sui marciumi della fragola in conservazione,” Frutocoltura, Vol. 62, No.5, 2000, pp. 71-75.

A. El-Ghaouth, J. L. Smilanick, G. E. Brown, M. Wisniewski and C. L. Wilson, “Application of Candida saitoana and Glycolchitosan for the control of postharvest diseases of apple and citrus fruit under semi-commercial conditions,” Plant Disease, Vol. 84, No. 3, pp. 244-248.

F. Nigro, L. Schena, A. Ligorio, I. Pentimone, A. Ippolito and M. G. Salerno, “Control of table grape storage rots by pre-harvest applications of salts,” Postharvest Biology and Technology, Vol. 42, No. 2, 2006, pp. 142–149.

G. Romanazzi, F. Nigro, A. Ippolito, D. Di Venere and M. Salerno, “Effects of pre- and postharvest chitosan treatments to ControlnStorage grey mold of table grapes,” Journal of Food Science, Vol. 67, No. 5, 2002, pp. 1862-1867.

P. Bertolini and D. Missere, “Metodi innovativi di gestione dei frutti nella fase post-raccolta,”Rete interregionale per la ricerca agraria, forestale, acquacoltura e pesca, Regione Emilia Romagna, 2010.

Z. Zheng, S. Xie, H. Dai, X. Chen and H. Wang, “An overview of blockchain technology: architecture, consensus, and future trends,” Proceeding of IEEE 6th International Congress on Big Data, 2017 , pp. 559- 564.

D. Puthal, N. Malik, S. P. Mohanty, E. Kougianos and G. Das, “Everything you wanted to know about the blockchain: its promise, components, processes, and problems,” IEEE Consumer Electronics Magazine, Vol. 7, No. 4, 2018, pp. 6-14.

B. Koteska, E. Karafiloski and A. Mishev, “Blockchain implementation quality challenges: a literature review,” Proceedings of the SQAMIA 2017, 6thWorkshop of Software Quality, Analysis, Monitoring, Improvement, and Applications, Belgrade, Serbia, 11-13.9.2017.

K. Biswas, V. Muthukkumarasamy and W. L. Tan, “Blockchain based wine supply chain traceability system,” Future Technologies Conference (FTC) 2017, 29-30 November 2017,Vancouver, Canada, pp. 56-62.

A. Lei, H. Cruickshank, Y. Cao, P. Asuquo, C. P. A. Ogah, and Z. Sun, “Blockchain-based dynamic key management for heterogeneous intelligent transportation systems,” IEEE Internet Things J., Vol. 4, No. 6, 2017, pp. 1832–1843.

M. Raya, P. Papadimitratos, and J. p. Hubaux, “Securing vehicular communications,” IEEE Wireless Communications, Vol. 13, No. 5, 2006, pp. 8–15.

P. Verhoeven, F. Sinn and T. T. Herden, “Examples from blockchain implementations in logistics and supply chain management: exploring the mindful use of a new technology,” Logistics, Vol .2, No. 2, 2018.

M. Dobrovnik, D. M. Herold, E. Fürst and S. Kummer, “Blockchain for and in logistics: what to adopt and where to start,” Logistics , Vol. 2, No. 18, 2018.

N. Hackius and M. Petersen, “Blockchain in logistics and supply chain: trick or treat?,” Published in: Digitalization in Supply Chain Management and Logistics; Wolfgang Kersten, Thorsten Blecker and Christian M. Ringle (Eds.), ISBN 9783745043280, Oktober 2017, epubli.

Y. Yanovich, I. Shiyanov, T. Myaldzin, I. Prokhorov, D. Korepanova and S. Vorobyov, “Blockchain-based supply chain for postage stamps,” Informatics, Vol. 5, No. 42, 2018.

I. Karamitsos, M. Papadaki, N. B. Al Barghuthi, “Design of the blockchain smart contract: a use case for real estate,” Journal of Information Security, Vol. 9, No. 3, 2018, pp. 177-190.

T. Marwala and B. Xing, “Blockchain and artificial intelligence,” SSRN Electronic Journal, 2018.

A. Garg and A. Garg, “Blockchain for artificial intelligence,” International Journal for Research in Applied Science & Engineering Technology (IJRASET), Vol. 5, No. 11, 2017.

K. Salah, M. H. Rehman, N. Nizamuddin, and A. Al-Fuqaha, “Blockchain for AI: review and open research challenges,” IEEE Access, Vol. 7, 2019, pp. 10127-10149.

S. Makridakis, A. Polemitis, G. Giaglis and S. Louca, “Blockchain: the next breakthrough in the rapid progress of AI,” Robot Autom. Eng. J., Vol. 2, No. 4, 2018, pp .1-12.

R. Pulungan, S. Pulung Nugroho, N. El Maidah, T. B. Atmojo, P. D. Hardo and P. Pawenang, “Design of an intelligent warehouse management system,” Information Systems International Conference (ISICO), 2 – 4 December 2013.

R. Kamath, “Food Traceability on blockchain: Walmart’s pork and mango pilots with IBM,” The Journal of the British Blockchain Association, Vol. 1, No. 1, 2018, pp.47-53.

D. Mao, Zhihao Hao, Fan Wang, and Haisheng Li, “Innovative blockchain-based approach for sustainable and credible environment in food trade: a case study in shandong province, China,” Sustainability, Vol. 10, No. 3149, 2018, pp. 1-17.

I.-C. Lin, H. Shih, J.-C. Liu, Y.-X. Jie, “Food Traceability System using Blockchain,” inProceedings of 79th IASTEM International Conference, Tokyo, Japan, 6th-7 th October 2017, pp. 59-64.

A. Massaro, I. Manfredonia, A. Galiano, L. Pellicani, and V. Birardi, “Sensing and Quality Monitoring Facilities Designed for Pasta Industry Including Traceability, Image Vision and Predictive Maintenance,” in Proceeding of IEEE International Workshop on Metrology for Industry 4.0 and IoT, 2019, pp. 68-72, https://doi.org/10.1109/METROI4.2019.8792912.

A. Massaro, N. Contuzzi, A. Galiano, I. Manfredonia, and B. Xhahysa, “A Preliminar Research Industry Project: a Case of Study defining Requirements for Knowledge Base Gain and Technological Upgrade in Industry Working in Train Parts Processing and Testing,” in Proceeding of IEEE International Workshop on Metrology for Industry 4.0 and IoT, pp. 172-176, https://doi.org/10.1109/METROI4.2019.8792850.

A. Massaro, I. Manfredonia, A. Galiano, and B. Xhaysa, “Advanced Process Defect Monitoring Model and Prediction Improvement by Artificial Neural Network in Kitchen Manufacturing Industry: a Case of Study,” in Proceeding of IEEE International Workshop on Metrology for Industry 4.0 and IoT, 2019, pp. 64-67,https://doi.org/10.1109/METROI4.2019.8792872.

N. Contuzzi, A. Massaro, I. Manfredonia, A. Galiano, and B. Xhahysa, “A Decision Making Process Model based on a Multilevel Control Platform Suitable for Industry 4.0,” in Proceeding of IEEE International Workshop on Metrology for Industry 4.0 and IoT, 2019, pp.127-131, https://doi.org/10.1109/METROI4.2019.8792854.

A. Massaro, V. Maritati, A. Galiano, V. Birardi, and L. Pellicani, “ESB Platform Integrating KNIME Data Mining Tool oriented on Industry 4.0 Based on Artificial Neural Network Predictive Maintenance,” International Journal of Artificial Intelligence and Applications(IJAIA), Vol.9, No.3, May 2018, pp. 1-17, doi: 10.5121/ijaia.2018.9301.

A. Massaro, and A. Galiano, A., “Re-Engineering Process in a Food Factory: An Overview of Technologies and Approaches for the Design of Pasta Production Processes,”Production & Manufacturing Research,Vol. 8, No. 1, 2020, pp. 80-100, https://doi.org/10.1080/21693277.2020.1749180.

A. Massaro, G. Dipierro, A. Saponaro, and A. Galiano, “Data Mining Applied in Food Trade Network,” International Journal of Artificial Intelligence and Applications (IJAIA), Vol.11, No.2, 2020, pp. 15-34, doi: 10.5121/ijaia.2020.11202.

A. Massaro, and Galiano, “Image Processing and Post-Data Mining Processing for Security in Industrial Applications: Security in Industry,” IGI Global 2020, Handbook of Research on Intelligent Data Processing and Information Security Systems, Ch. 6, pp117-146, doi: 10.4018/978-1-7998-1290-6.ch006.

A. Massaro, V. Maritati, D. Giannone, D. Convertini, and A. Galiano, (2019) “LSTM DSS Automatism and Dataset Optimization for Diabetes Prediction,” Applied Sciences, Vol. 9, No. 17, 2019, pp. 1-22, https://doi.org/10.3390/app9173532.

A. Massaro, V. Maritati, N. Savino, A. Galiano, D. Convertini, E. De Fonte, M. Di Muro, “A Study of a Health Resources Management Platform Integrating Neural Networks and DSS Telemedicine for Homecare Assistance,” Information, Vol. 9, No. 7, 2018, pp. 1-20, https://doi.org/10.3390/info9070176.

A. Massaro, D. Barbuzzi, V. Vitti, A. Galiano, M. Aruci, and G. Pirlo, “Predictive Sales Analysis According to the Effect of Weather,” in Proceeding of the 2nd International Conference on Recent Trends and Applications in Computer Science and Information Technology, Tirana, Albania, November 18 - 19, 2016, pp. 53-55, http://ceur-ws.org/Vol-1746/paper-09.pdf.

A. Massaro, V. Vitti, A. Galiano, and A. Morelli, A., “Business Intelligence Improved by Data Mining Algorithms and Big Data Systems: an Overview of Different Tools Applied in Industrial Research,” Computer Science and Information Technology, Vol. 7, No.1, 2019, pp. 1-21, doi: 10.13189/csit.2019.070101.

A. Massaro, G. Meuli, N. Savino, and A. Galiano, “A Precision Agricolture DSS Based on Sensor Threshold Management for Irrigation Field,” Signal & Image Processing: An International Journal (SIPIJ), Vol. 9, 2018, pp. 39-58, doi: 10.5121/sipij.2018.9604.

A. D’Accolti, S. Maggio, A. Massaro, A. Galiano, V. Birardi, L. Pellicani, “Assessment of Data Fusion Oriented on Data Mining Approaches to Enhance Precision Agriculture Practices aimed at Increase of Durum Wheat (Triticum turgidum L. var. durum) Yield,” Journal of Food, Nutrition and Agriculture, Vol. 1, No. 1, 2018, pp. 47-54, http://dx.doi.org/10.21839/jfna.2018.v1i1.229.

E. Obada, E. A. Alamou, A. Chabi, J. Zandagba, A. Afouda, “Trends and Changes in Recent and Future Penman-Monteith Potential Evapotranspiration in Benin (West Africa),” Hydrology, Vol. 4, No. 3, pp. 1-18, https://doi.org/10.3390/hydrology4030038.


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