Thanks to the spread of the Internet of Things (IoT) devices such as smartphones, sensors, cameras and RFIDs, it is possible to collect big amount of data and use them in different areas of application, as for example energy efficiency in smart buildings, industrial automation, systems for emergency management and medical systems, etc. The key for all these IoT applications is the ability of these objects to interact with the physical world thanks to communication and computation capabilities. The latter, with the technological evolution of mobile and wireless platforms enable to execute complex tasks in a distributed way on the sensor nodes, reducing the overhead in the sensor network (WSN) and increasing the architectural scalability. However, each of these sensor nodes is resource constrained in terms of computation, because of low capacity memories, and energy, because mostly powered with batteries. Furthermore, they are prone to malfunctions due to their unreliability or problems within the communication network. For this reason, the data they provide is not always accurate or may be incomplete. It is therefore necessary to consider beyond the data, both the quality of service (QoS) that is more about the characteristics of the sensor, and the QoD (Quality of Data), also called quality of Information (QoI) which defines the features of the measured data by the sensor. The purpose of this essay is therefore to provide the user, in addition to the data, an estimate of the quality of service and data of a wireless sensor network or a sensor itself, in order to have a clearer understanding of the data. QoS and QoD are important because those data are often the key for making decisions and applying some actions after the detection of some event, for example turn on the air condition unit if the temperature of the room is greater than 26 °C and there is someone in that room. Therefore, in this essay a model will be proposed that interacts with the queries made by the user to the wireless sensor network or a sensor to provide the latter, in addition to the requested data, also a combination of metadata in terms of QoS and QoD with the aim of obtaining a quality rating. The building are the primary area chosen for the application of this model as currently they are a hot topic of research. There is a lot of work developing or proposing frameworks for smart buildings controlled by a sensor network to reduce the waste of energy. Today there is much more awareness about the climate changes and the necessity of reducing the pollution and the energy consumption. The buildings are a good starting point, because they are responsible for almost 70% of the electrical energy and 10 % of water consumption, and produce 40% of non-industrial garbage [1].
Con la proliferazione dell’IoT, apparecchi come gli smartphone, sensori, telecamere e RFID è possibile raccogliere numerosi dati da usare in diversi ambiti di applicazione, tra cui per esempio l’efficienza energetica negli smart buildings, automazione industriale, sistemi di gestione delle emergenze e sistemi medici, etc. La chiave di tutte queste applicazioni sta nella capacità degli oggetti di interagire con il mondo fisico tramite le capacità di comunicazione e computazione. Quest’ultima con lo sviluppo tecnologico delle piattaforme mobili e wireless permette di eseguire compiti anche complessi in modo distribuito sui nodi remoti, riducendo così l’overhead nelle reti di sensori (WSN) e migliorando la scalabilità della rete. Tuttavia, ciascuno di questi nodi sensore è dotato di limitate capacità energetiche, in quanto sono spesso alimentati da batterie, e computazionali, poiché sono dotati di memorie di piccole dimensioni e a basso consumo energetico. Inoltre, sono inclini a malfunzionamenti dati dalla loro inaffidabilità o da problemi inerenti alla rete di comunicazione. A tale ragione, i dati che questi forniscono non sono sempre esatti o potrebbero essere incompleti. È dunque necessario considerare al di là del singolo dato, sia la QoS (Qualità del servizio) che si occupa principalmente delle caratteristiche del sensore, sia la QoD (Qualità del dato), detta anche QoI (Qualità dell’informazione), che esprime le caratteristiche del dato rilevato dal sensore. Lo scopo del presente elaborato è dunque fornire all’utente, oltre al dato, una stima della qualità del servizio e del dato di un sensore o una rete di sensori, in modo da avere una visuale più completa dei dati che vengono forniti. La QoS e QoD sono importanti perché spesso i dati sono la chiave per prendere decisioni in merito alle azioni da attuare di conseguenza, come ad esempio accendere il sistema di condizionamento se la temperatura è superiore a 26 °C e si rileva almeno una persona nella stanza. Nel seguente elaborato verrà dunque proposto un modello che si interfaccia alle interrogazioni effettuate dall’utente al sensore o rete di sensori per fornire a quest’ultimo oltre al dato richiesto, anche una combinazione di metadati in ambito QoS e QoD con l’obbiettivo di ottenere una valutazione sulla qualità. L’ambito principale scelto per l’applicazione di questo modello sono gli edifici. La ricerca scientifica è molto attiva in questo campo per sviluppare edifici intelligenti controllati da sensori per ridurre gli sprechi. Infatti con la presa di coscienza sui cambiamenti climatici e la necessità di ridurre le emissioni, gli edifici rappresentano un buon punto di partenza in quanto responsabili di quasi il 70% del consumo elettrico totale, 10 % di acqua e produttori del 40% di rifiuti non industriali [1].
Applicazione a supporto dell'analisi della qualità dei dati in ambito sensoristico
Hlaca, Mario
2019/2020
Abstract
Thanks to the spread of the Internet of Things (IoT) devices such as smartphones, sensors, cameras and RFIDs, it is possible to collect big amount of data and use them in different areas of application, as for example energy efficiency in smart buildings, industrial automation, systems for emergency management and medical systems, etc. The key for all these IoT applications is the ability of these objects to interact with the physical world thanks to communication and computation capabilities. The latter, with the technological evolution of mobile and wireless platforms enable to execute complex tasks in a distributed way on the sensor nodes, reducing the overhead in the sensor network (WSN) and increasing the architectural scalability. However, each of these sensor nodes is resource constrained in terms of computation, because of low capacity memories, and energy, because mostly powered with batteries. Furthermore, they are prone to malfunctions due to their unreliability or problems within the communication network. For this reason, the data they provide is not always accurate or may be incomplete. It is therefore necessary to consider beyond the data, both the quality of service (QoS) that is more about the characteristics of the sensor, and the QoD (Quality of Data), also called quality of Information (QoI) which defines the features of the measured data by the sensor. The purpose of this essay is therefore to provide the user, in addition to the data, an estimate of the quality of service and data of a wireless sensor network or a sensor itself, in order to have a clearer understanding of the data. QoS and QoD are important because those data are often the key for making decisions and applying some actions after the detection of some event, for example turn on the air condition unit if the temperature of the room is greater than 26 °C and there is someone in that room. Therefore, in this essay a model will be proposed that interacts with the queries made by the user to the wireless sensor network or a sensor to provide the latter, in addition to the requested data, also a combination of metadata in terms of QoS and QoD with the aim of obtaining a quality rating. The building are the primary area chosen for the application of this model as currently they are a hot topic of research. There is a lot of work developing or proposing frameworks for smart buildings controlled by a sensor network to reduce the waste of energy. Today there is much more awareness about the climate changes and the necessity of reducing the pollution and the energy consumption. The buildings are a good starting point, because they are responsible for almost 70% of the electrical energy and 10 % of water consumption, and produce 40% of non-industrial garbage [1].File | Dimensione | Formato | |
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https://hdl.handle.net/10589/173883