Smart Sensors and Artificial Intelligence Driven Alert System for Optimizing Red Peppers Drying in Southern Italy

Costanza Fiorentino (), Paola D’Antonio (), Francesco Toscano, Nicola Capece, Luis Alcino Conceição, Emanuele Scalcione, Felice Modugno, Maura Sannino, Roberto Colonna, Emilia Lacetra and Giovanni Di Mambro
Additional contact information
Costanza Fiorentino: Department of Agriculture, Forest, Food and Environmental Sciences, University of Basilicata, Via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Paola D’Antonio: Department of Agriculture, Forest, Food and Environmental Sciences, University of Basilicata, Via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Francesco Toscano: Department of Agriculture, Forest, Food and Environmental Sciences, University of Basilicata, Via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Nicola Capece: Department of Engineering, University of Basilicata, Via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Luis Alcino Conceição: VALORIZA—Research Center for Endogenous Resource Valorization, Polytechnic Institute of Portalegre, 7300-110 Portalegre, Portugal
Emanuele Scalcione: Lucanian Agency of Innovation and Development in Agriculture (ALSIA), Via Annunziatella, 75100 Matera, Italy
Felice Modugno: Department of Agriculture, Forest, Food and Environmental Sciences, University of Basilicata, Via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Maura Sannino: Department of Agricultural Sciences, University of Naples Federico II, Via Università, 100, Portici, 80055 Naples, Italy
Roberto Colonna: Department of Engineering, University of Basilicata, Via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Emilia Lacetra: Department of Agriculture, Forest, Food and Environmental Sciences, University of Basilicata, Via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Giovanni Di Mambro: Elaisian SRL, Via Ostiense, 92, 00154 Roma, Italy

Sustainability, 2025, vol. 17, issue 4, 1-21

Abstract: The Senise red pepper, known as peperone crusco, is a protected geographical indication (PGI) product from Basilicata, Italy, traditionally consumed dried. Producers use semi-open greenhouses to meet PGI standards, but significant losses are caused by rot from microorganisms thriving in high moisture, temperature, and humidity, which also encourage pest infestations. To minimize losses, a low-cost alert system was developed. The study, conducted in summer 2022 and 2023, used external parameters from the ALSIA Senise weather station and internal sensors monitoring the air temperature and humidity inside the greenhouse. Since rot is complex and difficult to model, an artificial intelligence (AI)-based approach was adopted. A feed forward neural network (FFNN) estimated greenhouse climate conditions as if it were empty, comparing them with actual values when peppers were present. This revealed the most critical period was the first 3–4 days after introduction and identified a critical air relative humidity threshold. The system could also predict microclimatic parameters inside the greenhouse with red peppers, issuing warnings one hour before risk conditions arose. In 2023, it was tested by comparing predicted values with previously identified thresholds. When critical levels were exceeded, greenhouse operators were alerted to adjust conditions. In 2023, pepper rot decreased.

Keywords: red pepper; weather station; machine learning; smart sensors; greenhouse (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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