Conceptual spatial representations for indoor mobile robots

We present an approach for creating conceptual representations of human-made indoor environments using mobile robots. The concepts refer to spatial and functional properties of typical indoor environments. Following findings in cognitive psychology, our model is composed of layers representing maps at different levels of abstraction. The complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition. The system also incorporates a linguistic framework that actively supports the map acquisition process, and which is used for situated dialogue. Finally, we discuss the capabilities of the integrated system

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions

Ambient intelligence in buildings : design and development of an interoperable Internet of Things platform

During many years, people and governments have been warned about the increasing levels of pollution and greenhouse gases (GHG) emissions that are endangering our lives on this planet. The Information and Communication Technology sector, usually known as the ICT sector, responsible for the computerization of the society, has been pinpointed as one of the most important sectors contributing to such a problem. Many efforts, however, have been put to shift the trend towards the utilization of renewable resources, such as wind or solar power. Even though governments have agreed to follow this path and avoid the usage of non-renewable energies, it is not enough. Although the ICT sector might seem an added problem due to the number of connected devices, technology improvements and hardware optimization enable new ways of fighting against global warming and GHG emissions. The aforementioned computerization has forced companies to evolve their work into a computer-assisted one. Due to this, companies are now forced to establish their main headquarters inside buildings for work coordination, connection and management. Due to this, buildings are becoming one of the most important issues regarding energy consumption. In order to cope with such problem, the Internet of Things (IoT) offers new paradigms and alternatives for leading the change. IoT is commonly defined as the network of physical and virtual objects that are capable of collecting surrounding data and exchanging it between them or through the Internet. Thanks to these networks, it is possible to monitor any thinkable metric inside buildings, and, then, utilize this information to build efficient automated systems, commonly known as Building Energy Management Systems (BEMS), capable of extracting conclusions on how to optimally and efficiently manage the resources of the building. ICT companies have foreseen this market opportunity that, paired with the appearance of smaller, efficient and more durable sensors, allows the development of efficient IoT systems. However, the lack of agreement and standardization creates chaos inside IoT, and the horizontal connectivity between such systems is still a challenge. Moreover, the vast amount of data to process requires the utilization of Big Data techniques to guarantee close to real-time responses. This thesis initially presents a standard Cloud-based IoT architecture that tries to cope with the aforementioned problems by employing a Cloud middleware that obfuscates the underlying hardware architecture and permits the aggregation of data from multiple heterogeneous sources. Also, sensor information is exposed to any third-party client after authentication. The utilization of automated IoT systems for managing building resources requires high reliability, resilience, and availability. The loss of sensor data is not permitted due to the negative consequences it might have, such as disruptive resource management. For this, it is mandatory to grant backup options to sensor networks in order to guarantee correct functioning in case of partial network disconnections. Additionally, the placement of the sensors inside the building must guarantee minimal energy consumption while fulfilling sensing requirements. Finally, a building resource management use case is presented by means of a simulation tool. The tool draws on occupants' probabilistic models and environmental condition models for actuating upon building elements to ensure optimal and efficient functioning. Occupants' comfort is also taken into consideration and the trade-off between the two metrics is studied. All the presented work is meant to deliver insights and tools for current and future IoT system implementations by setting the basis for standardization agreements yet to happen.Durant molts anys, s'ha alertat a la població i als governs sobre l'increment en els nivells de pol·lució i d'emissió de gasos d'efecte hivernacle, que estan posant en perill la nostra vida a la Terra. El sector de les Tecnologies de la Informació i Comunicació, normalment conegut com les TIC, responsable de la informatització de la societat, ha estat senyalat com un dels sectors més importants encarregat d'agreujar tal problema. Però, molt esforç s'està posant per revertir aquesta situació mitjançant l'ús de recursos renovables, com l'energia eòlica o solar. Tot i que els governs han acordat seguir dit camí i evitar l'ús d'energia no renovable tant com sigui possible, no és suficient per erradicar el problema. Encara que el sector de les TIC pugui semblar un problema afegit donada la gran quantitat i l'increment de dispositius connectats, les millores en tecnologia i en hardware estan habilitant noves maneres de lluitar contra l'escalfament global i l'emissió de gasos d'efecte hivernacle. La informatització, anteriorment mencionada, ha forçat a les empreses a evolucionar el seu model de negoci cap a un més enfocat a la utilització de xarxes d'ordinadors per gestionar els seus recursos. Per això, dites companyies s'estan veient forçades a establir les seves seus centrals dintre d'edificis, per tenir un major control sobre la coordinació, connexió i maneig dels seus recursos. Això està provocant un augment en el consum energètic dels edificis, que s'estan convertint en un dels principals problemes. Per poder fer front al problema, la Internet de les Coses o Internet of Things (IoT) ofereix nous paradigmes i alternatives per liderar el canvi. IoT es defineix com la xarxa d'objectes físics i virtuals, capaços de recol·lectar la informació per construir sistemes automatitzats, coneguts com a Sistemes de Gestió Energètica per Edificis, capaços d'extreure conclusions sobre com utilitzar de manera eficient i òptima els recursos de l'edifici. Companyies pertanyents a les TIC han previst aquesta oportunitat de mercat que, en sincronia amb l'aparició de sensors més petits, eficients i duradors, permeten el desenvolupament de sistemes IoT eficients. Però, la falta d'acord en quant a l'estandardització de dits sistemes està creant un escenari caòtic, ja que s'està fent impossible la connectivitat horitzontal entre dits sistemes. A més, la gran quantitat de dades a processar requereix la utilització de tècniques de Big Data per poder garantir respostes en temps acceptables. Aquesta tesi presenta, inicialment, una arquitectura IoT estàndard basada en la Neu, que tracta de fer front als problemes anteriorment presentats mitjançant l'ús d'un middleware allotjat a la Neu que ofusca l'arquitectura hardware subjacent i permet l'agregació de la informació originada des de múltiples fonts heterogènies. A més, la informació dels sensors s'exposa perquè qualsevol client de tercers pugui consultar-la, després d'haver-se autenticat. La utilització de sistemes IoT automatitzats per gestionar els recursos dels edificis requereix un alt nivell de fiabilitat, resistència i disponibilitat. La perduda d'informació no està permesa degut a les conseqüències negatives que podría suposar, com una mala presa de decisions. Per això, és obligatori atorgar opcions de backup a les xarxes de sensors per garantir un correcte funcionament inclús quan es produeixen desconnexions parcials de la xarxa. Addicionalment, la col·locació dels sensors dintre de l'edifici ha de garantir un consum energètic mínim dintre de les restriccions de desplegament imposades. Finalment, presentem un cas d'ús d'un Sistema de Gestió Energètica per Edificis mitjançant una eina de simulació. Dita eina utilitza com informació d'entrada models probabilístics sobre les accions dels ocupants i models sobre la condició ambiental per actuar sobre els elements de l'edifici i garantir un funcionament òptim i eficient. A més, el confort dels ocupants també es considera com mètrica a optimitzar. Donada la impossibilitat d’optimitzar les dues mètriques de manera conjunta, aquesta tesi també presenta un estudi sobre el trade-off que existeix entre elles. Tot el treball presentat està pensat per atorgar idees i eines pels sistemes IoT actuals i futurs, i assentar les bases per l’estandardització que encara està per arribar.Durante muchos años, se ha alertado a la población y a los gobiernos acerca del incremento en los niveles de polución y de emisión de gases de efecto invernadero, que están poniendo en peligro nuestra vida en la Tierra. El sector de las Tecnologías de la Información y Comunicación, normalmente conocido como las TIC, responsable de la informatización de la sociedad, ha sido señalada como uno de los sectores más importantes encargado de agravar tal problema. Sin embargo, mucho esfuerzo se está poniendo para revertir esta situación mediante el uso de recursos renovables, como la energía eólica o solar. A pesar de que los gobiernos han acordado seguir dicho camino y evitar el uso de energía no renovable tanto como sea posible, no es suficiente para erradicar el problema. Aunque el sector de las TIC pueda parecer un problema añadido dada la gran cantidad y el incremento de dispositivos conectados, las mejoras en tecnología y en hardware están habilitando nuevas maneras de luchar contra el calentamiento global y la emisión de gases de efecto invernadero. Durante las últimas décadas, compañías del sector público y privado conscientes del problema han centrado sus esfuerzos en la creación de soluciones orientadas a la eficiencia energética tanto a nivel de hardware como de software. Las nuevas redes troncales están siendo creadas con dispositivos eficientes y los proveedores de servicios de Internet tienden a crear sistemas conscientes de la energía para su optimización dentro de su dominio. Siguiendo esta tendencia, cualquier nuevo sistema creado y añadido a la red debe garantizar un cierto nivel de conciencia y un manejo óptimo de los recursos que utiliza. La informatización, anteriormente mencionada, ha forzado a las empresas a evolucionar su modelo de negocio hacia uno más enfocado en la utilización de redes de ordenadores para gestionar sus recursos. Por eso, dichas compañías se están viendo forzadas a establecer sus sedes centrales dentro de edificios, para tener un mayor control sobre la coordinación, conexión y manejo de sus recursos. Esto está provocando un aumento en el consumo energético de los edificios, que se están convirtiendo en uno de los principales problemas. Para poder hacer frente al problema, el Internet de las Cosas o Internet of Things (IoT) ofrece nuevos paradigmas y alternativas para liderar el cambio. IoT se define como la red de objetos físicos y virtuales, capaces de recolectar la información del entorno e intercambiarla entre los propios objetos o a través de Internet. Gracias a estas redes, es posible monitorizar cualquier métrica que podamos imaginar dentro de un edificio, y, después, utilizar dicha información para construir sistemas automatizados, conocidos como Sistemas de Gestión Energética para Edificios, capaces de extraer conclusiones sobre cómo utilizar de manera eficiente y óptima los recursos del edificio. Compañías pertenecientes a las TIC han previsto esta oportunidad de mercado que, en sincronía con la aparición de sensores más pequeños, eficientes y duraderos, permite el desarrollo de sistemas IoT eficientes. Sin embargo, la falta de acuerdo en cuanto a la estandarización de dichos sistemas está creando un escenario caótico, ya que se hace imposible la conectividad horizontal entre dichos sistemas. Además, la gran cantidad de datos a procesar requiere la utilización de técnicas de Big Data para poder garantizar respuestas en tiempos aceptables. Esta tesis presenta, inicialmente, una arquitectura IoT estándar basada en la Nube que trata de hacer frente a los problemas anteriormente presentados mediante el uso de un middleware alojado en la Nube que ofusca la arquitectura hardware subyacente y permite la agregación de la información originada des de múltiples fuentes heterogéneas. Además, la información de los sensores se expone para que cualquier cliente de terceros pueda consultarla, después de haberse autenticado. La utilización de sistemas IoT automatizados para manejar los recursos de los edificios requiere un alto nivel de fiabilidad, resistencia y disponibilidad. La pérdida de información no está permitida debido a las consecuencias negativas que podría suponer, como una mala toma de decisiones. Por eso, es obligatorio otorgar opciones de backup a las redes de sensores para garantizar su correcto funcionamiento incluso cuando se producen desconexiones parciales de la red. Adicionalmente, la colocación de los sensores dentro del edificio debe garantizar un consumo energético mínimo dentro de las restricciones de despliegue impuestas. En esta tesis, mejoramos el problema de colocación de los sensores para redes heterogéneas de sensores inalámbricos añadiendo restricciones de clustering o agrupamiento, para asegurar que cada tipo de sensor es capaz de obtener su métrica correspondiente, y restricciones de protección mediante la habilitación de rutas de transmisión secundarias. En cuanto a grandes redes homogéneas de sensores inalámbricos, esta tesis estudia aumentar su resiliencia mediante la identificación de los sensores más críticos. Finalmente, presentamos un caso de uso de un Sistema de Gestión Energética para Edificios mediante una herramienta de simulación. Dicha herramienta utiliza como información de entrada modelos probabilísticos sobre las acciones de los ocupantes y modelos sobre la condición ambiental para actuar sobre los elementos del edificio y garantizar un funcionamiento óptimo y eficiente. Además, el comfort de los ocupantes también se considera como métrica a optimizar. Dada la imposibilidad de optimizar las dos métricas de manera conjunta, esta tesis también presenta un estudio sobre el trade-off que existe entre ellas. Todo el trabajo presentado está pensado para otorgar ideas y herramientas para los sistemas IoT actuales y futuros, y asentar las bases para la estandarización que todavía está por llegar.Postprint (published version

A Comprehensive Indoor Environment Dataset from Single-family Houses in the US

The paper describes a dataset comprising indoor environmental factors such as temperature, humidity, air quality, and noise levels. The data was collected from 10 sensing devices installed in various locations within three single-family houses in Virginia, USA. The objective of the data collection was to study the indoor environmental conditions of the houses over time. The data were collected at a frequency of one record per minute for a year, combining over 2.5 million records. The paper provides actual floor plans with sensor placements to aid researchers and practitioners in creating reliable building performance models. The techniques used to collect and verify the data are also explained in the paper. The resulting dataset can be employed to enhance models for building energy consumption, occupant behavior, predictive maintenance, and other relevant purposes

A Low-Cost IoT Based Buildings Management System (BMS) Using Arduino Mega 2560 And Raspberry Pi 4 For Smart Monitoring and Automation

This work presents an internet of things (IoT) based building management system (BMS) for monitoring, control, and energy management in buildings to provide an efficient way of energy utilization. Existing systems mainly provide monitoring of different parameters with limited controlling/automation functions. Existing solutions also do not provide automatic decision-making, advanced safety management, and resource tracking. However, the proposed system provides a comprehensive way of monitoring, controlling, and automatic decision making regarding different environmental and electrical parameters in buildings, i.e., temperature, humidity, dust, volt, etc., by using a low-cost wireless sensor network (WSN). The architecture of the proposed system consists of five layers and uses analog sensors which are connected to Arduino Mega 2560 microcontrollers for data collecting, NodeMCUs ESP8266 for wireless communication, Raspberry Pi4 microcomputers for decision making, and nod-RED dashboard which runs locally on a Raspberry Pi 4to provide a friendly end-user interface. The system also uses the Message Queuing Telemetry Transport (MQTT) communication protocol through Wi-Fi and completely relies on the local devices in the architecture and does not need cloud computing services. The proposed system provides two different kinds of automation, i.e., safety automation for the safety of different devices with advanced features, and energy automation. The proposed system is also able to provide humidity control inside a room and to track and count the available resources in any facility. The proposed system is low cost, scalable, and can be used in any building. Simulation results show that the proposed system is highly efficient

Navigation, Path Planning, and Task Allocation Framework For Mobile Co-Robotic Service Applications in Indoor Building Environments

Recent advances in computing and robotics offer significant potential for improved autonomy in the operation and utilization of today’s buildings. Examples of such building environment functions that could be improved through automation include: a) building performance monitoring for real-time system control and long-term asset management; and b) assisted indoor navigation for improved accessibility and wayfinding. To enable such autonomy, algorithms related to task allocation, path planning, and navigation are required as fundamental technical capabilities. Existing algorithms in these domains have primarily been developed for outdoor environments. However, key technical challenges that prevent the adoption of such algorithms to indoor environments include: a) the inability of the widely adopted outdoor positioning method (Global Positioning System - GPS) to work indoors; and b) the incompleteness of graph networks formed based on indoor environments due to physical access constraints not encountered outdoors. The objective of this dissertation is to develop general and scalable task allocation, path planning, and navigation algorithms for indoor mobile co-robots that are immune to the aforementioned challenges. The primary contributions of this research are: a) route planning and task allocation algorithms for centrally-located mobile co-robots charged with spatiotemporal tasks in arbitrary built environments; b) path planning algorithms that take preferential and pragmatic constraints (e.g., wheelchair ramps) into consideration to determine optimal accessible paths in building environments; and c) navigation and drift correction algorithms for autonomous mobile robotic data collection in buildings. The developed methods and the resulting computational framework have been validated through several simulated experiments and physical deployments in real building environments. Specifically, a scenario analysis is conducted to compare the performance of existing outdoor methods with the developed approach for indoor multi-robotic task allocation and route planning. A simulated case study is performed along with a pilot experiment in an indoor built environment to test the efficiency of the path planning algorithm and the performance of the assisted navigation interface developed considering people with physical disabilities (i.e., wheelchair users) as building occupants and visitors. Furthermore, a case study is performed to demonstrate the informed retrofit decision-making process with the help of data collected by an intelligent multi-sensor fused robot that is subsequently used in an EnergyPlus simulation. The results demonstrate the feasibility of the proposed methods in a range of applications involving constraints on both the environment (e.g., path obstructions) and robot capabilities (e.g., maximum travel distance on a single charge). By focusing on the technical capabilities required for safe and efficient indoor robot operation, this dissertation contributes to the fundamental science that will make mobile co-robots ubiquitous in building environments in the near future.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143969/1/baddu_1.pd

Modelling Indoor Air Quality Using Sensor Data and Machine Learning Methods

Ubiquitous sensing is transforming our societies and how we interact with our surrounding envi- ronment; sensors provide large streams of data while machine learning techniques and artificial intelligence provide the tools needed to generate insights from the data. These developments have taken place in almost every industry sector with topics such as smart cities and smart buildings becoming key topical issues as societies seek more sustainable ways of living. Smart buildings are the main context of this thesis. These are buildings equipped with various sensors used to collect data from the surrounding environment allowing the building to adapt itself and increasing its operational efficiency. Previously, most efforts in realizing smart buildings have focused on energy management and au- tomation where the goal is to improve costs associated with heating, ventilation, and air condi- tioning. A less studied area involves smart buildings and their indoor environments especially relative to sub-spaces within a building. Increased developments in low-cost sensor technologies have created new opportunities to sense indoor environments in more granular ways that provide new possibilities to model finer attributes of spaces within a building. This thesis focuses on modeling indoor environment data obtained from a multipurpose building that serves primarily as a school. The aim is to explore the quality of the indoor environment relative to regulatory guidelines and also exploring suitable predictive models for thermal comfort and indoor air quality. Additionally, design science methodology is applied in the creation of a proof of concept software system. This system is aimed at demonstrating the use of Web APIs to provide sensor data to clients that may use the data to render analytics among other insights to a building’s stakeholders. Overall, the main technical contributions of this thesis are twofold: (i) a potential web-application design for indoor air quality IoT data and (ii) an exposition of modeling of indoor air quality data based on a variety of sensors and multiple spaces within the same building. Results indicate a software-based tool that supports monitoring the indoor environment of a building would be beneficial in maintaining the correct levels of various indoor parameters. Further, modeling data from different spaces within the building shows a need for heterogeneous models to predict variables in these spaces. This implies parameters used to predict thermal comfort and air quality are different in varying spaces especially where the spaces differ in size, indoor climate control settings, and other attributes such as occupancy control

BLE-data:a smartphone-based BLE-data collection tool

Abstract. Smart phones together with plethora of different sensors create a massive data collection system. This system can be also used for storing, analyzing, and broadcasting data. Data can be anything that can be metered or derived, from chemical compounds to traffic congestion to advertisement data to users’ activity or health statistics. Using the sensors already present in smartphones together with Bluetooth capable controller chips to add more sophisticated sensors, user creates an easily extendable monitoring system that does not require an internet connection. After embedded initialization programming, configuring and managing these chips can be done with a smartphone using Bluetooth communication stack. This study presents an Android-library for managing BLE peripherals and an app to collecting and store the recorded data. Bluetooth devices are scanned and connected through Bluetooth Low Energy interface and data is stored to persistent Room database.Tiivistelmä. Älypuhelimet yhdessä lukuisten eri antureiden kanssa luovat massiivisen järjestelmän tietojen keräämiseksi, tallentamiseksi, lähettämiseksi ja analysoimiseksi. Nämä tiedot voivat olla mitä tahansa kemiallisista yhdisteistä liikenteen ruuhkautumiseen ja mainosdatan esittämisestä käyttäjän aktiivisuuteen ja terveystilastoihin. Käyttämällä älypuhelimen valmiiksi olemassa olevia sensoreita ja yhdistelemällä niitä Bluetooth -ominaisuudella varustettuun ohjaussiruun kehittyneempien sensorien kanssa, käyttäjä saa luotua helposti laajennettavan monitorointi verkoston, joka ei vaadi internet yhteyttä. Käyttöönotettaessa tarvitun sulautetun ohjelmakoodin jälkeen, sensorilaitteita voi ohjata älypuhelimella, käyttäen Bluetooth radiota. Tässä tutkimuksessa esitellään Android-kirjasto BLE sensorien hallintaan, yhdistettynä tietojen keräämiseksi ja tallentamiseksi rakennettuun appiin. Bluetooth-laitteet skannataan ja liitetään Bluetooth Low Energy -rajapinnan kautta ja näistä luettu data tallennetaan paikalliseen Room-tietokantaan

SAGA: Smart gateway for adaptive environments

The development of adaptive environments has the main objective of providing well-being to an individual, improving the environmental conditions of indoor environments and facilitating/automating any activity. In order to implement such systems, the use of devices capable of intercommunication and acquisition of environment-related parameters around the user is essential. Using wireless sensor networks, it is possible to monitor the various quality indices of indoor environments that can be used to develop strategies to improve quality of life of the users in personalized way. In this dissertation, a system based on a wireless sensor network that analyses and improves the environmental quality of indoor spaces, as well as evaluating the health status of an individual is presented. The system acquires and acts upon air quality and illumination quality-related parameters, as well as physiological data of a user, using sensor nodes and actuators distributed throughout the environment. Several wireless communication protocols have been implemented to enable intercommunication between the several elements present in the sensor network, such as actuators, sensor nodes and a coordinating / gateway node. Several warning mechanisms have been configured to alert the user to the presence of factors that may endanger their health, namely the presence of pollutants and thermal conditions that may trigger respiratory distress. In order to provide real-time system control including additional warning mechanisms, data analysis, a dedicated web application has been developed for this system. The user can control the environment according with his own needs and preferences through profiles configuration. The whole process of system development, hardware, software, experimental tests and contributions are included in this dissertation.A criação de ambientes adaptativos tem o principal objetivo de providenciar o bem-estar a um indivíduo, melhorar as condições do ambiente em seu redor e de facilitar/automatizar qualquer atividade. De forma a implementar tais sistemas, a utilização de dispositivos com capacidade de intercomunicação e de recolha de parâmetros relacionados com o ambiente em redor do utilizador é essencial. Com a utilização de redes de sensores sem fios, é possível monitorizar os diversos índices de qualidade de um ambiente interior e dessa forma melhorar a qualidade de vida. Nesta dissertação será apresentado um sistema baseado numa rede de sensores sem fios que permite analisar e melhorar a qualidade ambiental de espaços interiores e avaliar o estado de saúde de um indivíduo. O sistema adquire e atua sobre parâmetros relacionados com a qualidade do ar e qualidade de iluminação, assim como dados fisiológicos de um utilizador, através da utilização de nós de sensores e atuadores distribuídos pelo ambiente. Foram implementados diversos protocolos de comunicação sem fios para possibilitar a intercomunicação com outros elementos da rede, nomeadamente o nó coordenador/gateway. Foram configurados diversos mecanismos de alerta de forma a avisar o utilizador para a presença de fatores que possam colocar em risco a sua saúde, nomeadamente a presença de poluentes e condições térmicas que possam desencadear desconforto respiratório. De forma a proporcionar uma análise de dados em tempo real, controlo do sistema e dispor de mecanismos de alerta adicionais, foi desenvolvida uma aplicação Web dedicada a este sistema. Através desta, o utilizador poderá tornar o ambiente adaptável às suas características e de acordo com as suas preferências, através da configuração de perfis. Todo o processo de desenvolvimento do sistema, hardware, software, testes experimentais e contribuições serão incluídos nesta dissertação