The modern age is characterized by the rapid birth of new technologies, one of which is the Internet of Flying Things (IoFT), allowing us to explore new horizons for data acquisition. As an offshoot of the Internet of Things (IoT), this new IoFT paradigm considers the placement of sensors in previously unthinkable positions, permitting, for example, the direct measurement of pollutants coming from flare stacks without risk to human life. While IoT solutions are typically limited by cost and battery life, IoFT are more concerned with overall weight, which directly impacts flight time. In this Thesis, a prototype IoFT system capable of measuring the major pollutants is introduced. This platform can provide insight on Greenhouse Gases' (GHGs) concentrations over a specific area and may also be used to localize sources of pollution from their emissions, as well as localize leaks in pipelines. Drones permit these operations and many more while keeping operators far away from such sources of pollution, improving their health and allowing for closer measurements. The platform developed consists in an Arduino micro-controller tasked with digitizing analog sensor data and a lightweight Raspberry Pi, tasked with running a data collection Client. This latter can wirelessly connect to a Server, deployed for our tests on a laptop, which acts as a ground station, enabling the operator to see measured variables in real time and adjusting the drone trajectory as needed. The usage of standard Internet Protocols (IPs) for the interconnection between Client and Server provides the capability to remotely monitor the platform and achieve true to name IoFT capabilities.
L'era moderna è caratterizzata da una rapida nascita di nuove tecnologie, una di queste è l'Internet of Fly Things (IoFT), che ci permette di esplorare nuovi orizzonti nell'acquisizione di dati. Considerata come una branca dell'Internet of Things (IoT), il modello IoFT considera il posizionamento di sensori in luoghi prima impensabili, permettendo, ad esempio, misurazioni dirette di sostanze inquinanti provenienti da punti pericoli, non compromettendo la vita umana. Mentre le soluzioni IoT sono limitate dai costi e dalla durata di batteria, quelle inerenti IoFT sono più influenzate dal peso complessivo del modello prodotto, che impatta negatimanete anche sul tempo di volo. In questa Tesi, è stato introdotto un prototipo di modellizzazione IoFT capace di misurare i maggiori agenti nocivi nell'aria. Questa piattaforma può provvedere ad acquisizioni di Gas Serra in uno specifico campo di applicazione e può anche essere usato per localizzare sorgenti inquinanti dalla loro emissione, così come perdite in processi di produzione. I droni permettono queste e molte altre operazioni, mentre gli operatori sono tenuti a distanza da sorgenti tossiche, salvaguardando la loro salute e garantendo misuazioni più accurate. Il modello è stato sviluppato con Arduino, sul quale vengono convertiti in digitale i dati analogici provenienti dai sensori. Una scheda leggera Raspberry Pi, coordina l'acquisizione dei dati sul Client. Quest'ultimo può essere connesso da remoto ad un Server, sviluppato per i nostri test su un computer portatile, il quale agisce da stazione a terra, dando la possibilità all'operatore di visualizzare le variabili misurate in tempo reale e quindi aggiustando la traiettoria del drone al bisogno. Lo sfruttamento di Protolli Internet (IPs) standard per l'interconnessione tra Client e Server, fornisce la potenzialità di monitorare remotamente la piattaforma e raggiungere veramente le proprietà di una tecnologia IoFT.
Environmental variables monitoring through a lightweight sensor platform for UAV applications
NIGRO, FEDERICO
2022/2023
Abstract
The modern age is characterized by the rapid birth of new technologies, one of which is the Internet of Flying Things (IoFT), allowing us to explore new horizons for data acquisition. As an offshoot of the Internet of Things (IoT), this new IoFT paradigm considers the placement of sensors in previously unthinkable positions, permitting, for example, the direct measurement of pollutants coming from flare stacks without risk to human life. While IoT solutions are typically limited by cost and battery life, IoFT are more concerned with overall weight, which directly impacts flight time. In this Thesis, a prototype IoFT system capable of measuring the major pollutants is introduced. This platform can provide insight on Greenhouse Gases' (GHGs) concentrations over a specific area and may also be used to localize sources of pollution from their emissions, as well as localize leaks in pipelines. Drones permit these operations and many more while keeping operators far away from such sources of pollution, improving their health and allowing for closer measurements. The platform developed consists in an Arduino micro-controller tasked with digitizing analog sensor data and a lightweight Raspberry Pi, tasked with running a data collection Client. This latter can wirelessly connect to a Server, deployed for our tests on a laptop, which acts as a ground station, enabling the operator to see measured variables in real time and adjusting the drone trajectory as needed. The usage of standard Internet Protocols (IPs) for the interconnection between Client and Server provides the capability to remotely monitor the platform and achieve true to name IoFT capabilities.File | Dimensione | Formato | |
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Environmental Variables Monitoring Through a Lightweight Sensor Platform for UAV Applications.pdf
non accessibile
Descrizione: Thesis
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25.86 MB
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Adobe PDF
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25.86 MB | Adobe PDF | Visualizza/Apri |
Environmental Variables Monitoring Through a Lightweight Sensor Platform for UAV Applications (Execturive Summary).pdf
non accessibile
Descrizione: Executive Summary
Dimensione
8.69 MB
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Adobe PDF
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8.69 MB | Adobe PDF | Visualizza/Apri |
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https://hdl.handle.net/10589/215243