-
Giulia Oddi
Ph.D. Student
email:giulia.oddi[at]unipr.it
mailing address:
Department of Engineering and Architecture
Parco Area delle Scienze, 181/A
I-43124 ParmaGiulia Oddi was born in Parma on February 11st, 1999.
She received a Bachelor’s Degree in Information Systems Engineering on October 4, 2021, from the University of Parma (Italy).
She received a Master’s Degree cum laude in Computer Engineering on December 11, 2023, from the University of Parma (Italy) with a thesis entitled “Design and implementation of an IoT data collection and analysis platform for Smart Agriculture.”
Since November 2024, she is a member of the Internet of Things (IoT) Lab group as a Ph.D. Student at the Department of Engineering and Architecture of the University of Parma. -
- Internet of Things
- Data Analysis
- Machine Learning
- Data Management
2025
Laura Belli; Luca Davoli; Giulia Oddi; Luca Preite; Martina Galaverni; Tommaso Ganino; Gianluigi Ferrari
Smart agriculture dataset in a tomato cultivation under different irrigation regimes Journal Article
In: Data in Brief, 60 , pp. 111521, 2025, ISSN: 2352-3409.
@article{bedaodprgagafe:2025:dib,
title = {Smart agriculture dataset in a tomato cultivation under different irrigation regimes},
author = {Laura Belli and Luca Davoli and Giulia Oddi and Luca Preite and Martina Galaverni and Tommaso Ganino and Gianluigi Ferrari},
doi = {10.1016/j.dib.2025.111521},
issn = {2352-3409},
year = {2025},
date = {2025-04-08},
urldate = {2025-01-01},
journal = {Data in Brief},
volume = {60},
pages = {111521},
abstract = {This dataset contains data collected in a tomato cultivation (namely, a Solanum lycopersicum L. cv. HEINZ 1301 cultivation) located at the “Azienda Sperimentale Stuard,” Parma, Italy, through an IoT infrastructure featuring Long Range Wide Area Network (LoRaWAN)-enabled commercial devices deployed in the crop during the summer 2023 period (June 29–September 13). The IoT architecture also controls the irrigation system deployed to manage the watering conditions in the tomato crop, in detail considering three different experimental lines (each one associated with a different irrigation regime): (i) line #1 was irrigated with a water quantity equal to the irrigation recommendation provided by a national cloud service, denoted as Irriframe and developed by the Water Boards Italian Association (ANBI); (ii) line #2 was irrigated with a water quantity equal to 60% of line #1; (iii) line #3 was irrigated with a water quantity equal to 30% of line #1. The dataset comprises 4 different CSV files. The first three files (named as “stuard_environmental_data.csv,” “stuard_water_meter_data.csv,” and “stuard_soil_data.csv”) contain the information sampled every 10 minute by the IoT devices deployed in the crop—one environmental sensor, three water meters, and three soil sensors. The fourth CSV file (named as “indicators.csv”) contains the values of agronomic indicators of interest, calculated daily and mainly depending on daily air temperature values: (i) the Growing Degree Days (GDD) index and (ii) the Heat Units indicators, both calculated on the collected experimental tomato crop data.},
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This dataset contains data collected in a tomato cultivation (namely, a Solanum lycopersicum L. cv. HEINZ 1301 cultivation) located at the “Azienda Sperimentale Stuard,” Parma, Italy, through an IoT infrastructure featuring Long Range Wide Area Network (LoRaWAN)-enabled commercial devices deployed in the crop during the summer 2023 period (June 29–September 13). The IoT architecture also controls the irrigation system deployed to manage the watering conditions in the tomato crop, in detail considering three different experimental lines (each one associated with a different irrigation regime): (i) line #1 was irrigated with a water quantity equal to the irrigation recommendation provided by a national cloud service, denoted as Irriframe and developed by the Water Boards Italian Association (ANBI); (ii) line #2 was irrigated with a water quantity equal to 60% of line #1; (iii) line #3 was irrigated with a water quantity equal to 30% of line #1. The dataset comprises 4 different CSV files. The first three files (named as “stuard_environmental_data.csv,” “stuard_water_meter_data.csv,” and “stuard_soil_data.csv”) contain the information sampled every 10 minute by the IoT devices deployed in the crop—one environmental sensor, three water meters, and three soil sensors. The fourth CSV file (named as “indicators.csv”) contains the values of agronomic indicators of interest, calculated daily and mainly depending on daily air temperature values: (i) the Growing Degree Days (GDD) index and (ii) the Heat Units indicators, both calculated on the collected experimental tomato crop data.2024
Giulia Oddi; Laura Belli; Luca Davoli; Martina Galaverni; Ilaria Marchioni; Margherita Rodolfi; Deborah Beghé; Federico Solari; Giuseppe Vignali; Tommaso Ganino; Gianluigi Ferrari
Optimizing Tomato Production through IoT-based Smart Data Collection and Analysis Inproceedings
In: 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pp. 45-50, Bari, Italy, 2024.
@inproceedings{odbedagamarobesovigafe:2024:case,
title = {Optimizing Tomato Production through IoT-based Smart Data Collection and Analysis},
author = {Giulia Oddi and Laura Belli and Luca Davoli and Martina Galaverni and Ilaria Marchioni and Margherita Rodolfi and Deborah Beghé and Federico Solari and Giuseppe Vignali and Tommaso Ganino and Gianluigi Ferrari},
doi = {10.1109/CASE59546.2024.10711738},
year = {2024},
date = {2024-10-23},
urldate = {2024-01-01},
booktitle = {2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)},
pages = {45-50},
address = {Bari, Italy},
abstract = {The always-growing diffusion and adoption of Internet of Things (IoT) technologies is revolutionizing heterogeneous scenarios (e.g., home, industry, safety, etc.), including the agricultural/farming: this paves the way to the Smart Agriculture (SA) paradigm. In detail, this approach leverages the exploitation of IoT smart objects (e.g., sensors, actuators, ground robots, and flying drones) to optimize and improve agricultural practices, eventually improving both sustainability and efficiency. This paper presents an IoT-based data collection and analysis architecture expedient to acquire and manage IoT data streams generated from the field. The proposed approach has been applied to a real experimental use case to optimize tomato production in the Äzienda Sperimentale Stuard" farm located in Parma, Italy. The obtained results highlight the feasibility, sustainability, and gain margins (i.e., in terms of cost/benefits) returned by such a deployment in a real scenario, enabling farmers to make informed decisions based on on-field data acquisition (e.g., reducing water consumption during the growing season).},
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The always-growing diffusion and adoption of Internet of Things (IoT) technologies is revolutionizing heterogeneous scenarios (e.g., home, industry, safety, etc.), including the agricultural/farming: this paves the way to the Smart Agriculture (SA) paradigm. In detail, this approach leverages the exploitation of IoT smart objects (e.g., sensors, actuators, ground robots, and flying drones) to optimize and improve agricultural practices, eventually improving both sustainability and efficiency. This paper presents an IoT-based data collection and analysis architecture expedient to acquire and manage IoT data streams generated from the field. The proposed approach has been applied to a real experimental use case to optimize tomato production in the Äzienda Sperimentale Stuard" farm located in Parma, Italy. The obtained results highlight the feasibility, sustainability, and gain margins (i.e., in terms of cost/benefits) returned by such a deployment in a real scenario, enabling farmers to make informed decisions based on on-field data acquisition (e.g., reducing water consumption during the growing season).Laura Belli; Luca Davoli; Gianluigi Ferrari; Giulia Oddi
IoT in agricoltura: vantaggi e casi d’uso reali Online
Agenda Digitale 2024, visited: 20.08.2024.
@online{bedafeod:2024:agri,
title = {IoT in agricoltura: vantaggi e casi d’uso reali},
author = {Laura Belli and Luca Davoli and Gianluigi Ferrari and Giulia Oddi},
url = {https://www.agendadigitale.eu/mercati-digitali/iot-in-agricoltura-vantaggi-e-casi-duso-reali/},
year = {2024},
date = {2024-08-20},
urldate = {2024-08-20},
organization = {Agenda Digitale},
abstract = {L’integrazione di tecnologie IoT in agricoltura permette un monitoraggio preciso delle coltivazioni, ottimizzando l’uso delle risorse idriche e prevedendo informazioni agronomiche fondamentali. Uno studio dell’Università di Parma esplora i benefici di tali tecnologie, presentando due casi d’uso reali: l’ottimizzazione dell’irrigazione del pomodoro e la predizione del periodo di raccolta del luppolo.},
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L’integrazione di tecnologie IoT in agricoltura permette un monitoraggio preciso delle coltivazioni, ottimizzando l’uso delle risorse idriche e prevedendo informazioni agronomiche fondamentali. Uno studio dell’Università di Parma esplora i benefici di tali tecnologie, presentando due casi d’uso reali: l’ottimizzazione dell’irrigazione del pomodoro e la predizione del periodo di raccolta del luppolo.
Giulia Oddi
-
Giulia Oddi
Ph.D. Student
email:giulia.oddi[at]unipr.it
mailing address:
Department of Engineering and Architecture
Parco Area delle Scienze, 181/A
I-43124 ParmaGiulia Oddi was born in Parma on February 11st, 1999.
She received a Bachelor’s Degree in Information Systems Engineering on October 4, 2021, from the University of Parma (Italy).
She received a Master’s Degree cum laude in Computer Engineering on December 11, 2023, from the University of Parma (Italy) with a thesis entitled “Design and implementation of an IoT data collection and analysis platform for Smart Agriculture.”
Since November 2024, she is a member of the Internet of Things (IoT) Lab group as a Ph.D. Student at the Department of Engineering and Architecture of the University of Parma. -
- Internet of Things
- Data Analysis
- Machine Learning
- Data Management
2025
Smart agriculture dataset in a tomato cultivation under different irrigation regimes Journal Article
In: Data in Brief, 60 , pp. 111521, 2025, ISSN: 2352-3409.
2024
Optimizing Tomato Production through IoT-based Smart Data Collection and Analysis Inproceedings
In: 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pp. 45-50, Bari, Italy, 2024.
IoT in agricoltura: vantaggi e casi d’uso reali Online
Agenda Digitale 2024, visited: 20.08.2024.