A smart voltage and current monitoring system for three phase inverters using an android smartphone application

In this paper, a new smart voltage and current monitoring system (SVCMS) technique is proposed. It monitors a three phase electrical system using an Arduino platform as a microcontroller to read the voltage and current from sensors and then wirelessly send the measured data to monitor the results using a new Android application. The integrated SVCMS design uses an Arduino Nano V3.0 as the microcontroller to measure the results from three voltage and three current sensors and then send this data, after calculation, to the Android smartphone device of an end user using Bluetooth HC-05. The Arduino Nano V3.0 controller and Bluetooth HC-05 are a cheap microcontroller and wireless device, respectively. The new Android smartphone application that monitors the voltage and current measurements uses the open source MIT App Inventor 2 software. It allows for monitoring some elementary fundamental voltage power quality properties. An effort has been made to investigate what is possible using available off-the-shelf components and open source software

Electrify Atwater Kent

The Electrify Atwater Kent project aims to breathe new life into the dull, dreary building of Atwater Kent. LED stairs, bringing a modern look to the front stairwell, as well as the RasPiano, with customizable filters and visualizations to demonstrate the discipline of signal processing, will be installed in the building. With a full installation the project aimsto make Atwater Kent not just a more welcoming space that students feel comfortable studying in, but an inspiration for future engineers as well

A Wireless, Multi-Channel Printed Capacitive Strain Gauge System for Structural Health Monitoring

Structural health monitoring of soft structural textiles plays a key role within the space industry to ensure the safety and integrity of space habitats, parachutes, and decelerator systems. Strain monitoring could be an effective means to evaluate structural integrity, but conventional monitoring systems are not suitable because they are intended for large, rigid structures. To overcome the limitations of rigid sensors, we recently proposed using printed capacitive strain gauges (CSGs) on flexible substrates to monitor the structural health of soft structure materials. Here, we present a strategy and implementation of a wireless, multi-channel readout system for distributed monitoring of soft structural textiles with printed CSGs. The system is comprised of localized sensor motes and a wireless Bluetooth hub. The sensor mote employs a relaxation oscillator frontend to convert capacitance to frequency with a high dynamic range using only three interface wires per mote. The mote’s high dynamic range ensures compatibility with various gauge designs and accommodates significant process variation associated with printed gauges. Each hub enables users to read 8 channels of data wirelessly at a sampling rate of 100Hz and can be scaled to higher channel counts through the use of additional hubs. The sensor motes and wireless hub are miniaturized to accommodate flexible substrates, such as a Kevlar strap. The system is tested and exhibits excellent linearity and dynamic range

Building appliances energy performance assessment

Trabalho de Projeto de Mestrado, Informática, 2021, Universidade de Lisboa, Faculdade de CiênciasO consumo de energia tem vindo a crescer na União Europeia todos os anos, sendo de prever que, a curto prazo, se torne insustentável. No sentido de prevenir este cenário, a Comissão Europeia decidiu definir uma Estratégia Energética para a União Europeia, destacando dois objetivos: aumentar a eficiência energética e promover a descarbonização. Atualmente, cerca de 72% dos edifícios existentes na União Europeia não são energeticamente eficientes. Este problema motivou-nos à pesquisa e criação de soluções que permitam uma melhor avaliação do consumo energético por dispositivos elétricos em edifícios residenciais. Neste contexto, o trabalho desenvolvido nesta tese consiste no desenho de uma solução de monitorização remota que recolhe informações de consumo energético recorrendo a técnicas de intrusive load monitoring, onde cada dispositivo elétrico individual é continuamente monitorizado quanto ao seu consumo energético. Esta abordagem permite compreender o consumo de energia, em tempo real e no dia-a-dia. Este conhecimento oferece-nos a capacidade de avaliar as diferenças existentes entre as medições laboratoriais (abordagem utilizada no sistema de rotulagem de equipamentos elétricos de acordo com a sua eficiência energética) e os consumos domésticos estimados. Para tal, nesta tese exploram-se abordagens de machine learning que pretendem descrever padrões de consumo, bem como reconhecer marcas, modelos e que funções os dispositivos elétricos estarão a executar. O principal objetivo deste trabalho é desenhar e implementar um protótipo de uma solução de IoT flexível e de baixo custo para avaliar equipamentos elétricos. Será utilizado um conjunto de sensores que recolherá dados relacionados com o consumo de energia e os entrega à plataforma SATO para serem posteriormente processados. O sistema será usado para monitorar aparelhos comumente encontrados em residências. Além disso, o sistema terá a capacidade de monitorizar o consumo de água de aparelhos que necessitem de abastecimento de água, como máquinas de lavar e de lavar louça. Os dados recolhidos serão usados para classificação dos aparelhos e modos de operação dos mesmos, em tempo real, permitindo fornecer relatórios sobre o consumo energético e modo de uso dos aparelhos, com grande grau de detalhe. Os relatórios podem incluir o uso de energia por vários ciclos de operação. Por exemplo, um aparelho pode executar vários ciclos de operação, como uma máquina de lavar que consume diferentes quantidades de energia elétrica e água consoante o modo de operação escolhido pelo utilizador. Toda a informação recolhida pode ser posteriormente utilizada em novos serviços de recomendação que ajudaram os utilizadores a definir melhor as configurações adequadas a um determinado dispositivo, minimizando o consumo energético e melhorando a sua eficiência. Adicionalmente toda esta informação pode ser utilizada para o diagnóstico de avarias e/ou manutenção preventiva. Em termos de proposta, o trabalho desenvolvido nesta tese tem as seguintes contribuições: Sistema de monitorização remota: o sistema de monitorização desenhado e implementado nesta tese avança o estado da arte dos sistemas de monitorização propostos pela literatura devido ao facto de incluir uma lista aprimorada de sensores que podem fornecer mais informações sobre os aparelhos, como o consumo de água da máquina de lavar. Além disso, é altamente flexível e pode ser implementado sem esforço em dispositivos novos ou antigos para monitorização de consumo de recursos. Conjunto de dados de consumo de energia de eletrodomésticos: Os dados recolhidos podem ser usados para futura investigação científica sobre o consumo de consumo de energia, padrões de uso de energia pelos eletrodomésticos e classificação dos mesmos. Abordagem de computação na borda (Edge Computing): O sistema de monitorização proposto explora o paradigma de computação na borda, onde parte da computação de preparação de dados é executada na borda, libertando recursos da nuvem para cálculos essenciais e que necessitem de mais poder computacional. Classificação precisa de dispositivos em tempo real: Coma proposta desenhada nesta tese, podemos classificar os dispositivos com alta precisão, usando os dados recolhidos pelo sistema de monitorização desenvolvido na tese. A abordagem proposta consegue classificar os dispositivos, que são monitorizados, com baixas taxas de falsos positivos. Para fácil compreensão do trabalho desenvolvido nesta tese, de seguida descreve-se a organização do documento. O Capítulo 1 apresenta o problema do consumo de energia na União Europeia e discute o aumento do consumo da mesma. O capítulo apresenta também os principais objetivos e contribuições do trabalho. No Capítulo 2 revê-se o trabalho relacionado em termos de sistema de monitorização remota, que inclui sensores, microcontroladores, processamento e filtragem de sinal. Por fim, este capítulo revê os trabalhos existentes na literatura relacionados com o problema de classificação de dispositivos usando abordagens de machine learning. No Capítulo 3 discutem-se os requisitos do sistema e o projeto de arquitetura conceitual do sistema. Neste capítulo é proposta uma solução de hardware, bem como, o software e firmware necessários à sua operação. Os algoritmos de machine learning necessários à classificação são também discutidos, em termos de configurações necessárias e adequadas ao problema que queremos resolver nesta tese. O Capítulo 4 representa a implementação de um protótipo que servirá de prova de conceito dos mecanismos discutidos no Capítulo 3. Neste capítulo discute-se também a forma de integração do protótipo na plataforma SATO. Com base na implementação feita, no Capítulo 5 especificam-se um conjunto de testes funcionais que permitem avaliar o desempenho da solução proposta e discutem-se os resultados obtidos a partir desses testes. Por fim, o Capítulo 6 apresenta as conclusões e o trabalho futuro que poderá ser desenvolvido partindo da solução atual.Energy consumption is daily growing in European Union (EU). One day it will become hardly sustainable. For this not to happen European Commission decided to implement a European Union Strategy, emphasizing two objectives: increasing energy efficiency and decarbonization. About 72% of all buildings in the EU are not adapted to be energy efficient. This problem encourages us to create solutions that would help assess the energy consumption of appliances at residential houses. In this thesis, we proposed a system that collects data using an intrusive load monitoring approach, where each appliance will have a dedicated monitoring rig to collect the energy consumption data. The proposed solution will help us understand the real-life consumption of each device being monitored and compare the laboratory measurements observed versus domestic consumption estimated by the energy consumption based on the EU energy efficiency labelling system. The system proposed detects device consumption patterns and recognize its brand, model and what actions that appliance is executing, e.g., program of washing in a washing machine. To achieve our goal, we designed a hardware solution capable of collecting sensor data, filtering and send it to a cloud platform (the SATO platform). Additionally, in the cloud, we have a Machine Learning solution that deals with the data and recognizes the appliance and its operation modes. This recognition allows drawing a device/settings profile, which can detect faults and create a recommendation service that helps users define the better settings for a specific appliance, minimizing energy consumption and improving efficiency. Finally, we examine our prototype approach of the system implemented for targeted objectives in this project report. The document describes the experiments that we did and the final results. Our results show that we can identify the appliance and some of its operation modes. The proposed approach must be improved to make the identification of all operation modes. However, the current version of the system shows exciting results. It can be used to support the design of a new labelling system where daily operation measures can be used to support the new classification system. This way, we have an approach that allows improving the energy consumption, making builds more efficient

Open source SCADA systems for small renewable power generation

Low cost monitoring and control is essential for small renewable power systems. While large renewable power systems can use existing commercial technology for monitoring and control, that is not cost-effective for small renewable generation. Such small assets require cost-effective, flexible, secure, and reliable real-time coordinated data monitoring and control systems. Supervisory control and data acquisition (SCADA) is the perfect technology for this task. The available commercial SCADA solutions are mostly pricey and economically unjustifiable for smaller applications. They also pose interoperability issues with the existing components which are often from multiple vendors. Therefore, an open source SCADA system represents the most flexible and the most cost-effective SCADA solution. This thesis has been done in two phases. The first phase demonstrates the design and dynamic simulation of a small hybrid power system with a renewable power generation system as a case study. In the second phase, after an extensive study of the proven commercial SCADA solutions and some open source SCADA packages, three different secure, reliable, low-cost open source SCADA options are developed using the most recent SCADA architecture, the Internet of Things. The implemented prototypes of the three open source SCADA systems were tested extensively with a small renewable power system (a solar PV system). The results show that the developed open source SCADA systems perform optimally and accurately, and could serve as viable options for smaller applications such as renewable generation that cannot afford commercial SCADA solutions

Light Fidelity (Li-Fi) prototype with Raspberry Pi

With globalisation and the thirst for connectivity across society, the demand placed on wireless infrastructure and the associated resource is growing exponentially. Very soon this resource will reach saturation point, due to the finite bandwidth available in the Radio Frequency (RF) spectrum. A method of countering the impending saturation needs to be found. That method can be Visible Light Communication (VLC). Light Fidelity (Li-Fi) is a research field within VLC that utilises the visible light band within the electromagnetic wave spectrum. This band is 10,000 times larger than the RF band and cannot be ‘leased’ or saturated with users. Light waves can be modulated to carry an enormous amount ofsimultaneous data, at speeds faster than current consumer equipment can handle. This Dissertation describes in detail the research, construction and testing of a Li-Fi prototype using Raspberry Pi. The prototype is compact, low cost, uses accessible components and provides a solid foundation for other students to follow on with further work in this field. The prototype successfully demonstrates the principle of Visible Light Communication and shows the viability of using Python for coding, SPI for data transfer and lists suitable electronic components to process bit-wise data signals. The prototype shows that while it is possible to use addressable LED’sas the transmitting element, the Dissertation concludes that they are not suitable outside of a heavily constrained environment

A more efficient technique to power home monitoring systems using controlled battery charging

Home energy monitoring has recently become a very important issue and a means to reduce energy consumption in the residential sector. Sensors and control systems are deployed at various locations in a house and an intelligent system is used to efficiently manage the consumed energy. Low power communication systems are used to provide low power consumption from a smart meter. Several of these systems are battery operated. Other systems use AC/DC adapters to supply power to sensors and communication systems. However, even using low-power technology, such as ZigBee, the power consumption of a router can be high because it must always be powered on. In this work, to evaluate power consumption, a system for monitoring energy usage and indoor air quality was developed. A technique is proposed to efficiently supply power to the components of the system. All sensor nodes are battery operated, and relays are used to control the battery charging process. In addition, an energy harvesting system based on solar energy was developed to power the proposed system.info:eu-repo/semantics/publishedVersio

A Communications Testbed for Testing Power Electronic Agent Systems

As power electronic system (PES) continue to incorporate complex intra-system communication, understanding and characterizing this communication has become a complex task. Knowing how a system’s communication will behave is vital to ensuring proper operation of these systems. This thesis proposes and outlines a communication testbed that streamlines the development and testing of the communications between the components of PES, and further presents the characterization of communication protocol utilized in these multi-agent PESs. These communication protocols include MQTT, Modbus, or User Datagram Protocol (UDP). Understanding the different behavior of these protocols presents is paramount for the design of PESs

Development of a Raspberry Pi based, SDI-12 sensor environmental data logger

SDI-12 is a powerful tool for sensor networking and environmental data acquisition (EDA). Sensory networks are employed by many commercial and non-commercial entities across a wide range of applications to achieve better outcomes for the environment, the investing parties or the wider community. Monitoring systems can reduce operation costs and improve quality of products or produce. Many applications for sensor networks are of ethical significance for example, applications related to sustainable living, education, scientific research and food production. Despite the potential benefits, whether people adopt a system is largely dependent on associated costs and complexity. Consequently an inexpensive, reliable and easy to use system is more likely to be adopted. The Raspberry Pi is a powerful and inexpensive computing platform for embedded projects which incorporates a 40 pin general purpose input output (GPIO) header for connecting to digital peripherals, which is used as the basis of this project. The prototype SDI-12 logger software is written in C++ and uses an existing Arduino SDI12 C++ library that has been modified for use with the Raspberry Pi computer. The system is evaluated for its suitability as a simple easy to configure (plug-and-play) type logger. The SDI-12 software developed, while functional, has only a subset of the features that a market ready device will need. Future work includes adding control outputs for automation, a graphical user interface and also leveraging the Raspberry Pi’s network capabilities to allow remote access for setting and disabling alarms and also for uploading of data to an online database for remote access

Hybrid RFID Sensors: Design, Implementation and Application

The fields of Wireless sensor networks and RFID technology are two examples of the current move to ubiquitous computing. Wireless sensor networks has emerged as a tool for long term remote monitoring for applications ranging from agriculture to military. While in RFID we have already seen it being used in everyday life from access control to asset tracking. The integration of these two fields allows for a whole range of new applications, the focus of this dissertation is to present a wireless sensor network platform which incorporates a hybrid RFID sensor mote for the detection of environmental conditions and the locating of objects or personnel within an environment. The solution that is proposed comprises of both hardware and software but focuses on the design of the platforms’ prototype wireless sensor mote which provides object detection through the use of an RFID reader and environmental conditions by using low cost slave sensors. The solution was then applied to solving the problem of locating mining personnel and detecting hazardous levels of methane gas for use in underground mines