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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-09082023-112422


Tipo di tesi
Tesi di laurea magistrale
Autore
BUA, CRISTIAN
URN
etd-09082023-112422
Titolo
AN HYDROPONIC GREENHOUSE SYSTEM AS A MODULAR SMALL SCALE TEST BED FOR SMART AGRICULTURE
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA DELLE TELECOMUNICAZIONI
Relatori
relatore Giordano, Stefano
correlatore Adami, Davide
Parole chiave
  • Node-RED.
  • hydroponic green house
  • NGSI-LD
  • LoRa
  • smart agriculture
  • Internet of Things
Data inizio appello
28/09/2023
Consultabilità
Non consultabile
Data di rilascio
28/09/2093
Riassunto
In the agricultural sector, climate change with water bombs and drought periods, leads us to search solutions in terms of efficient use of resources, especially water, and to create weather independent systems. Monitor and control the growth of the plants and environmental parameters is essential in Smart Agriculture for making farms and greenhouses more intelligent and efficient. Farmers must be equipped with specific and customized monitoring system that they can access remotely to analyze data. This thesis proposes a new modular system architecture that allows to create new services without starting over and redesigning the whole system from scratch whenever it is necessary to add new monitoring devices or new functionalities, such as closed control loop or GUI, to increment rapidly new services for precision agriculture. We implement an autonomous hydroponic greenhouse that keeps environmental parameters stable and grows tomato plants in an ideal environment. Environmental conditions are automatically regulated through actuators that receive commands from a cloud application. For making decisions, this application leverage a PID control algorithm and control commands are transmitted via the MQTT protocol with NGSI-LD message format. In addition, LoRa modulation at 2.4 GHz is used to connect IoT devices to a gateway. All monitored data are made available to the end-users through a dashboard of a smartphone app.
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