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A predictive Decision Support System (DSS) for a microalgae production plant based on Internet of Things paradigm
Author(s) -
Giannino Francesco,
Esposito Serena,
Diano Marcello,
Cuomo Salvatore,
Toraldo Gerardo
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4476
Subject(s) - production (economics) , biochemical engineering , decision support system , computer science , model predictive control , internet of things , process engineering , control (management) , engineering , artificial intelligence , world wide web , economics , macroeconomics
Summary The production of microalgae represents a large and rapidly expanding market with several applications in the fields of food, pharmaceutics, cosmetics, and energy. Microalgae are photosynthetic aquatic microorganisms whose growth is mainly controlled by a few environmental parameters: temperature, light, pH, and nutrient availability. For this reason, monitoring and controlling such parameters is crucial for their production. At the same time, the development of mathematical models to simulate the behavior of biological systems has become a major predictive and control tool of production processes. In this paper, we present an Internet of Things (IoT) system that can couple sensor data collected directly by biotechnological cultivations with a predictive simulation model. The IoT system constitutes the core of a Decision Support System developed to help the end‐user in the management of industrial production processes.