Business Intelligence Improved by Data Mining Algorithms and Big Data Systems: An Overview of Different Tools Applied in Industrial Research

Massaro, Alessandro; Vitti, Valeria; Galiano, Angelo; Morelli, Alessandro

doi:10.13189/csit.2019.070101

“…In this direction neural networks such as Long Short Term Memory (LSTM) [39] and Artificial Neural Networks (ANNs) [40] could also be applied for: • processing production inefficiencies: the LSTM/ANNs networks could predict sanitation inefficiencies by processing and crossing data of the experimental test of cultivation (in Fig. 7 is shown the experimental field used to acquire and to collect data for the preprocessing of vegetables); the BC will include data and information about sanitation test by adopting different no-chemical pre-treatment solutions; • delays in transport: the algorithms predict production according to metrological sales prediction [41], [42]; • risk of persistent contamination: the neural network could predict the contamination evolution by indicating the risk using different approaches for sanitation; • field condition prediction: precision agriculture and data mining [43], [44] could facilitate the data processing by analyzing other factors that could influence product sanitation such as hydric stress, temperature, humidity and evapotranspiration [45]. The production process traceability by BC could activate automatic smart contracts thus accelerating marketing and commercial processes.…”

Section: Discussionmentioning

confidence: 99%

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

Massaro¹

2021

ITII

0

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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.

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“…In this direction neural networks such as Long Short Term Memory (LSTM) [39] and Artificial Neural Networks (ANNs) [40] could also be applied for: • processing production inefficiencies: the LSTM/ANNs networks could predict sanitation inefficiencies by processing and crossing data of the experimental test of cultivation (in Fig. 7 is shown the experimental field used to acquire and to collect data for the preprocessing of vegetables); the BC will include data and information about sanitation test by adopting different no-chemical pre-treatment solutions; • delays in transport: the algorithms predict production according to metrological sales prediction [41], [42]; • risk of persistent contamination: the neural network could predict the contamination evolution by indicating the risk using different approaches for sanitation; • field condition prediction: precision agriculture and data mining [43], [44] could facilitate the data processing by analyzing other factors that could influence product sanitation such as hydric stress, temperature, humidity and evapotranspiration [45]. Fig.…”

Section: Discussionmentioning

confidence: 99%

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

Massaro¹

2020

Preprint

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<div>Alessandro Massaro: Professor Alessandro Massaro (ING/INF/01, FIS/01,FIS/03) carried out scientific research </div><div>at the Polytechnic University of Marche, at CNR, and at Italian Institute of Technology (IIT) as Team Leader by activating laboratories for nanocomposite sensors for </div><div>industrial robotics. He is in MIUR register as scientific expert in competitive Industrial Research and social </div><div>development, and he is currently head of the Research and Development section and scientific director of MIUR Research Institute Dyrecta Lab Srl. Member of the International Scientific Committee of Measurers IMEKO and IEEE Senior member, recently received an award from the National Council of Engineers as Best Engineer of Italy 2018 (Top Young Engineer 2018). </div>

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“…In this direction, in order to optimize logistics patterns can be adopted different algorithms such as (Massaro et al, 2019):…”

Section: Logistic Aspects and Innovation Technologiesmentioning

confidence: 99%

Re-engineering process in a food factory: an overview of technologies and approaches for the design of pasta production processes

Massaro¹,

Galiano²

2020

Production & Manufacturing Research

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Business Intelligence Improved by Data Mining Algorithms and Big Data Systems: An Overview of Different Tools Applied in Industrial Research

Cited by 29 publications

References 24 publications

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

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

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

Re-engineering process in a food factory: an overview of technologies and approaches for the design of pasta production processes

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