A predictive Decision Support System (DSS) for a microalgae production plant based on Internet of Things paradigm. (30th March 2018)

• Record Type: Journal Article
• Authors: Giannino, Francesco; Esposito, Serena; Diano, Marcello; Cuomo, Salvatore; Toraldo, Gerardo
• Other Names: Piccialli Francesco guestEditor.; Jung Jason J. guestEditor.
• Is Part Of: Concurrency and computation. Volume 30:Number 15(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-03-30
• Subjects: biological modeling -- Internet of Things -- microalgae cultivation -- system dynamic; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4476
• Languages: English
• ISSNs: 1532-0626

Abstract

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.