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Abstract
Precision agriculture is a management strategy of agricultural activities based on data-driven decisions. This enables smarter usage of the available resources (e.g., water and crop) and ensures higher productivity. Following the integration of precision farming with the internet of things, big data, and artificial intelligence, we are witnessing the rise of ``Agriculture 5.0”. In this context, WeLASER is a European project that aims to create a system for managing weeding tasks by the adoption of robots equipped with laser technology that recognizes and burns weeds; this prevents the usage of chemical pesticides that can cause environmental damages. Such application involves the joint usage of robotic agents and data from IoT devices (e.g., weather stations) to perform effective weeding tasks. The goal of this thesis is to design, create, and test a data platform that enables the interoperability of IoT devices and robotic agents as well as data-intensive analytics on streaming data. Such data platform provides unified interfaces to collect, integrate, and analyze real-time data as well as to manage historical data.
Abstract
Precision agriculture is a management strategy of agricultural activities based on data-driven decisions. This enables smarter usage of the available resources (e.g., water and crop) and ensures higher productivity. Following the integration of precision farming with the internet of things, big data, and artificial intelligence, we are witnessing the rise of ``Agriculture 5.0”. In this context, WeLASER is a European project that aims to create a system for managing weeding tasks by the adoption of robots equipped with laser technology that recognizes and burns weeds; this prevents the usage of chemical pesticides that can cause environmental damages. Such application involves the joint usage of robotic agents and data from IoT devices (e.g., weather stations) to perform effective weeding tasks. The goal of this thesis is to design, create, and test a data platform that enables the interoperability of IoT devices and robotic agents as well as data-intensive analytics on streaming data. Such data platform provides unified interfaces to collect, integrate, and analyze real-time data as well as to manage historical data.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Montelli, Francesco
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
cloud computing,internet of things,robotics,precision agriculture,big data
Data di discussione della Tesi
16 Dicembre 2021
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Montelli, Francesco
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
cloud computing,internet of things,robotics,precision agriculture,big data
Data di discussione della Tesi
16 Dicembre 2021
URI
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