Implementation of an intelligent sensor for measurement and prediction of solar radiation and atmospheric temperature

Dissertação de mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2011

Diseño y uso de una paleta háptica para prácticas de teleoperación con simulink

En este artículo se presenta el uso de dispositivos de realimentación de fuerzas de un grado de libertad como herramienta para el desarrollo de aplicaciones docentes en asignaturas de teleoperación y telerrobótica, con el objetivo de disponer de una interfaz física que pueda ser utilizada como equipo de prácticas. Estos dispositivos, conocidos como haptic paddle, ya han sido probados satisfactoriamente para aplicaciones educativas de modelado y simulación de sistemas, ntroducción a los haptics e ingeniería de control en diversas Universidades. Para el desarrollo de los experimentos que se muestran en este artículo se han utilizado dos dispositivos haptic paddle con un controlador basado en Arduino y fabricados mediante tecnologías aditivas de impresión 3D. Gracias a los sensores de fuerza y posición incorporados se pueden implementar esquemas bilaterales de teleoperación de posicón-posición y fuerza-posición.

Un sistema di domotica per il controllo energetico domestico con tecnologie open-source.

Data la sempre maggiore richiesta di fabbisogno energetico, si è sviluppata una nuova filosofia nella gestione dei consumi energetici, il DSM (demand side management), che ha lo scopo di incoraggiare il consumatore ad usare energia in modo più intelligente e coscienzioso. Questo obiettivo, unito all’accumulo di energia da fonti rinnovabili, permetterà un abbassamento dell’utilizzo dell’energia elettrica proveniente dal consumo di fonti non rinnovabili e altamente inquinanti come quelle a combustibili fossili ed una diminuzione sia del consumo energetico, sia del costo per produrre energia che dell’energia stessa. L’home automation e la domotica in ambiente domestico rappresentano un esempio di DSM. L’obiettivo di questa tesi è quello di creare un sistema di home automation utilizzando tecnologie opensource. Sono stati utilizzati device come board Arduino UNO, Raspberry Pi ed un PC con sistema operativo GNU/Linux per creare una simulazione di un sistema di home automation abbinato alla gestione di celle fotovoltaiche ed energy storaging. Il sistema permette di poter spegnere un carico energetico in base a delle particolari circostanze come, per esempio, il superamento di una certa soglia di consumo di energia elettrica. Il software utilizzato è opensource e mira a poter ottimizzare il consumo energetico secondo le proprie finalità. Il tutto a dimostrare che si può creare un sistema di home automation da abbinare con il presente e futuro delle fonti rinnovabili utilizzando tecnologie libere in modo tale da preservare privacy e security oltre che customizzazione e possibilità di adattamento a diverse circostanze. Nella progettazione del sistema è stato implementato un algoritmo per gestire varie situazioni all’interno di un ambiente domestico. La realizzazione di tale algoritmo ha prodotto ottimi risultati nella raggiungimento degli obiettivi prefissati. Il progetto di questa tesi può essere ulteriormente ampliato ed il codice è reperibile in un repository pubblico.

Sviluppo di un sistema integrato per rampe isocrone di temperatura

Lo scopo del presente lavoro è la realizzazione e l'ottimizzazione di un software che, tramite l'utilizzo di un controllo automatico Proporzionale-Integrativo-Derivativo: PID, gestisca la temperatura di un fornetto in camera a vuoto. È necessario che il sistema sia in grado di eseguire rampe regolari di temperatura di diversa pendenza scelta dall'utente, in modo che possa essere utilizzato in futuro per esperimenti di Desorbimento Termico da parte di vari materiali. La tesi è così suddivisa, nel primo capitolo sono illustrati i concetti teorici di base utilizzati nello sviluppo dei controlli automatici. Nel secondo capitolo è descritta la parte hardware: sono mostrate le diverse sezioni che compongono il fornetto e la camera a vuoto, è inoltre illustrato il cablaggio che permette l'interfaccia del forno alla scheda Arduino ed al software LabVIEW. La terza sezione è dedicata agli studi svolti per la realizzazione del sistema di controllo PID e per la sua ottimizzazione. Il quarto capitolo è invece dedicato alla descrizione del software creato per la gestione del fornetto. Nel quinto capitolo sono infine mostrati i metodi utilizzati per il calcolo delle costanti operative del PID ed i risultati sperimentali ottenuti.

Average-case analysis of power consumption in embedded systems

Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.

Cloud Base Height Measurement System Based on Stereo Vision with Automatic Calibration

Clouds are important in weather prediction, climate studies and aviation safety. Important parameters include cloud height, type and cover percentage. In this paper, the recent improvements in the development of a low-cost cloud height measurement setup are described. It is based on stereo vision with consumer digital cameras. The cameras positioning is calibrated using the position of stars in the night sky. An experimental uncertainty analysis of the calibration parameters is performed. Cloud height measurement results are presented and compared with LIDAR measurements.

Épocas de poda e uso de cianamida hidrogenada na brotação de videiras "Merlot" (Vitis vinifera L.) na Região da Campanha Gaúcha.

A Campanha Gaúcha vem sendo classificada entre as regiões vitivinícolas mais promissoras no Rio Grande do Sul, especialmente pelas suas condições edafoclimáticas com maior restrição hídrica e drenagem do solo. Apesar do início da vitivinicultura nesta região datar da década de 70, a maior intensificação dos plantios e produção ocorreu nos últimos dez anos, porém sem muitos subsídios técnicos. Os objetivos deste trabalho foram avaliar os efeitos da antecipação da poda hibernal e concentrações de cianamida hidrogenada (CH) sobre o potencial produtivo da uva ?Merlot?/SO4 conduzida nos sistemas de poda Guyot Duplo (DG) e Cordão Esporonado (CE).

Progettazione, ottimizzazione e sviluppo di un sistema WOPI (Water Out Pressure In) per airbox

Un airbox deve fornire al motore sia aria pura, ovvero priva di particelle estranee (motivo per cui al suo interno viene collocato un elemento filtrante), che priva di gocce d’acqua, la cui presenza è possibile sia a causa della condensazione dell’umidità dell’aria aspirata, sia, in volume anche maggiore, in caso di pioggia, aspetto su cui si focalizzerà questo elaborato. Attualmente, per eliminare la presenza di queste particelle d’acqua, vengono praticati fori, più o meno grandi, sulla parete dell’airbox. Questa semplice tecnica, permette di eliminarla, ma causa anche una depressurizzazione. Per contrastare questo fenomeno, è già noto l’utilizzo di condotti elastici, normalmente chiusi o semichiusi, che, nel frattempo, permettono la lenta discesa gravitazionale dell’acqua. Questo sistema, però, non è in grado di sigillare il foro di scolo, provocando quindi anch’esso un calo della pressurizzazione del box. Inoltre, esso potrebbe intasarsi, rendendo inefficace lo scolo. In più, nel tempo, potrebbe sopraggiungere una perdita di elasticità, causando un peggioramento della funzionalità. Scopo del WOPI è eliminare tutti i precedenti inconvenienti nel modo più efficiente possibile.

Wireless solutions for the industrial internet of things

The fourth industrial revolution is paving the way for Industrial Internet of Things applications where industrial assets (e.g., robotic arms, valves, pistons) are equipped with a large number of wireless devices (i.e., microcontroller boards that embed sensors and actuators) to enable a plethora of new applications, such as analytics, diagnostics, monitoring, as well as supervisory, and safety control use-cases. Nevertheless, current wireless technologies, such as Wi-Fi, Bluetooth, and even private 5G networks, cannot fulfill all the requirements set up by the Industry 4.0 paradigm, thus opening up new 6G-oriented research trends, such as the use of THz frequencies. In light of the above, this thesis provides (i) a broad overview of the main use-cases, requirements, and key enabling wireless technologies foreseen by the fourth industrial revolution, and (ii) proposes innovative contributions, both theoretical and empirical, to enhance the performance of current and future wireless technologies at different levels of the protocol stack. In particular, at the physical layer, signal processing techniques are being exploited to analyze two multiplexing schemes, namely Affine Frequency Division Multiplexing and Orthogonal Chirp Division Multiplexing, which seem promising for high-frequency wireless communications. At the medium access layer, three protocols for intra-machine communications are proposed, where one is based on LoRa at 2.4 GHz and the others work in the THz band. Different scheduling algorithms for private industrial 5G networks are compared, and two main proposals are described, i.e., a decentralized scheme that leverages machine learning techniques to better address aperiodic traffic patterns, and a centralized contention-based design that serves a federated learning industrial application. Results are provided in terms of numerical evaluations, simulation results, and real-world experiments. Several improvements over the state-of-the-art were obtained, and the description of up-and-running testbeds demonstrates the feasibility of some of the theoretical concepts when considering a real industry plant.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

Integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment

The computer controlled screwdriver is a modern technique to perform automatic screwing/unscrewing operations.The main focus is to study the integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment.This thesis describes a concept of automatic screwing mechanism composed by universal robots, in which one arm of the robot is for inserting cables and the other is for screwing the cables on the control panel switch gear box. So far this mechanism is carried out by human operators and is a fairly complex one to perform, due to the multiple cables and connections involved. It's for this reason that an automatic cabling and screwing process would be highly preferred within automotive/automation industries. A study is carried out to analyze the difficulties currently faced and a controller based algorithm is developed to replace the manual human efforts using universal robots, thereby allowing robot arms to insert the cables and screw them onto the control panel switch gear box. Experiments were conducted to evaluate the insertion and screwing strategy, which shows the result of inserting and screwing cables on the control panel switch gearbox precisely.

Design of a wearable platform for PPG analysis with multicore low-power processor

Photoplethysmography (PPG) sensors allow for noninvasive and comfortable heart-rate (HR) monitoring, suitable for compact wearable devices. However, PPG signals collected from such devices often suffer from corruption caused by motion artifacts. This is typically addressed by combining the PPG signal with acceleration measurements from an inertial sensor. Recently, different energy-efficient deep learning approaches for heart rate estimation have been proposed. To test these new solutions, in this work, we developed a highly wearable platform (42mm x 48 mm x 1.2mm) for PPG signal acquisition and processing, based on GAP9, a parallel ultra low power system-on-chip featuring nine cores RISC-V compute cluster with neural network accelerator and 1 core RISC-V controller. The hardware platform also integrates a commercial complete Optical Biosensing Module and an ARM-Cortex M4 microcontroller unit (MCU) with Bluetooth low-energy connectivity. To demonstrate the capabilities of the system, a deep learning-based approach for PPG-based HR estimation has been deployed. Thanks to the reduced power consumption of the digital computational platform, the total power budget is just 2.67 mW providing up to 5 days of operation (105 mAh battery).

An Embedded In-Cabin Lightweight High-Performance 3D Gaze Estimation System

Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.

Embedding Video Object Detection Capabilities on Low-Power Nano-Drones

Our objective for this thesis work was the deployment of a Neural Network based approach for video object detection on board a nano-drone. Furthermore, we have studied some possible extensions to exploit the temporal nature of videos to improve the detection capabilities of our algorithm. For our project, we have utilized the Mobilenetv2/v3SSDLite due to their limited computational and memory requirements. We have trained our networks on the IMAGENET VID 2015 dataset and to deploy it onto the nano-drone we have used the NNtool and Autotiler tools by GreenWaves. To exploit the temporal nature of video data we have tried different approaches: the introduction of an LSTM based convolutional layer in our architecture, the introduction of a Kalman filter based tracker as a postprocessing step to augment the results of our base architecture. We have obtain a total improvement in our performances of about 2.5 mAP with the Kalman filter based method(BYTE). Our detector run on a microcontroller class processor on board the nano-drone at 1.63 fps.

Sperimentazione della piattaforma IoT Cloud per lo sviluppo di sistemi di monitoraggio

L’Internet of Things (IoT) è un termine utilizzato nel mondo della telecomunicazione che fa riferimento all’estensione di Internet al mondo degli oggetti, che acquisiscono una propria identità, venendo così definiti “intelligenti”. L’uomo in questo ambito avrà sempre meno incidenza sul campo poiché sono le macchine ad interagire tra loro scambiandosi informazioni. Gli ambiti applicativi che comprendono IoT sono innumerevoli ed eterogenei; pertanto, non esiste un'unica soluzione tecnologica che possa coprire qualsiasi scenario. Una delle tecnologie che si prestano bene a svolgere lavori in IoT sono le LoRaWAN. Un punto e una sfida essenziali nell'applicazione della tecnologia LoRaWAN è garantire la massima autonomia dei dispositivi ottenendo il più basso consumo di energia possibile e la ricerca di soluzioni di alimentazione efficienti. L'obiettivo in questo elaborato è quello di realizzare un sistema capace di trasmettere un flusso continuo di informazioni senza l'ausilio e il costante monitoraggio dell'uomo. Viene trattato come controllare dei sensori da remoto e come garantire una migliore autonomia dei dispositivi ottenendo un più basso consumo energetico.